Digital Lab #12 – ๐Ÿ˜€

I thought about writing this blog post entirely with emojis, but I realized how difficult that would ๐Ÿ…ฑ๏ธ, so I opted to use standard English (mostly). Many people underestimate the power of emojis to convey ideas, while others may use them too liberally, effectively obscuring meaning, so attempting to write an entire literary piece using only the images was quite a difficult challenge. Instead of creating a linear narrative, like Xu Bing’s Book from the Ground, however, I decided to ๐Ÿ…ฑ๏ธ a little more abstract with my work, with emojis not always representing what they initially portray and by using figurative “language.” I think it was successful, and I am extremely grateful for the two friends who were brave enough to write translations, as I am sure it was a difficult task.

Here is my emoji poem:

๐Ÿงโ€โ™‚๏ธโ›ฐ๐Ÿ—ฃ:
โ€œ๐Ÿ—บ๐Ÿ™โšฐ๐Ÿ•ณ.โ€
๐Ÿ˜Ž
๐Ÿƒ๐Ÿ”Š,
๐Ÿฟ๐Ÿฆ…,
๐Ÿ”Š๐Ÿ‘‚,๐ŸŒ๐Ÿ—ฃ
โ€œ๐Ÿ™๐Ÿ˜ˆโ“
โš–๐Ÿ’ฒ๐Ÿ’€
๐Ÿคœโ›๐Ÿ’Ž
๐Ÿ•ณ๐Ÿ˜’
๐Ÿฅบ,๐Ÿ“
๐Ÿฆถ๐Ÿ˜‡,
๐Ÿค,๐Ÿ˜ข,๐Ÿ’ช
๐Ÿ‹๏ธโ€โ™€๏ธ๐ŸŒ๐Ÿคโ”โ€
 
๐Ÿงโ€โ™€๏ธโ›ฐ๐Ÿ—ฃ: โ€œโณ
๐Ÿ˜”
๐Ÿ™‚๐Ÿ™‚๐Ÿ™‚๐Ÿ™‚๐Ÿ™‚๐Ÿ™‚๐Ÿ™‚๐Ÿ™‚๐Ÿ™‚๐Ÿ™‚๐Ÿ™‚๐Ÿ™‚
๐Ÿคข๐Ÿคข๐Ÿคข๐Ÿคข๐Ÿคข๐Ÿคข๐Ÿคข๐Ÿคข๐Ÿคข๐Ÿคข๐Ÿคข๐Ÿคข
๐ŸŒŽ๐Ÿ˜ฑ.
โŒ›๐Ÿ˜ฒ๐Ÿ’€๐Ÿ’€
โšฐ๐ŸŒณ๐ŸŒท๐ŸŒธ๐ŸŒน๐ŸŒบ๐ŸŒผ๐ŸŒป๐Ÿ’ฎ๐Ÿต.
โค๐Ÿ’™๐Ÿ’š๐Ÿ’›๐Ÿ’œโ˜ .
๐ŸŒผ๐Ÿ’€๐Ÿ‘ถ,
๐Ÿ˜ด๐Ÿ๐Ÿ‘ญ,
๐Ÿ”Š๐Ÿถ๐Ÿ˜๐Ÿ‘จโ€โš–๏ธ,
๐Ÿคฅโœจ,
๐ŸŒฑ๐Ÿง 
๐ŸŒธ๐Ÿ˜“๐Ÿ.
 
โ€œโณ,๐Ÿ˜‡๐Ÿ˜ˆ
โณ๐ŸŽ—,
๐Ÿ˜จ๐Ÿ‘Ž๐Ÿ”
๐Ÿ˜ซ๐Ÿ’ฒ.
๐Ÿ’ณ๐Ÿ’ธ,๐Ÿค‘,
๐Ÿ‘‰๐Ÿ‘‰๐Ÿ‘‰๐Ÿ‘‰๐Ÿ‘ˆ๐Ÿ‘ˆ๐Ÿ‘ˆ๐Ÿ‘ˆ
๐Ÿ˜‹๐Ÿ™ƒ๐Ÿ˜ต๐Ÿฅด๐Ÿคฌ๐Ÿคฌ๐Ÿคฌ๐Ÿคฌ
๐Ÿšซโ˜ฎ.๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡
๐Ÿ˜ ๐Ÿ˜ ๐Ÿ˜’๐Ÿ˜’๐Ÿ˜ก๐Ÿ˜ก๐Ÿ’ข๐Ÿ’ข
โŒ›โŒ›.โŒš;
๐ŸŽ.๐Ÿ‘ฟ
๐Ÿ’€๐Ÿ’€.
๐Ÿ•Š๐Ÿ•Š๐ŸŒ,๐Ÿ˜€๐Ÿ˜๐Ÿ˜ƒ๐Ÿ˜„๐Ÿ˜Š๐Ÿ˜๐Ÿ˜˜๐Ÿฅฐโ˜บ๐Ÿค—.โ€
 
๐ŸŒโ˜ฎ,๐Ÿ˜ญ,
๐Ÿ˜”.

Here is one of the two translations:

A boy went to the mountains and said:
โ€œI hope the map is right and we donโ€™t fall into a pothole and die.โ€
Sunglasses on
Leaves crunching,
Squirrels and birds,
I heard, the world said
โ€œYou pray to the devil?
Try to find balance and not work to death
Work hard for jewels
Look into the dark hole and be sad
Oh no, measure yourself
Youโ€™ll set foot in heaven,
Take things, cry, and be strong
Youโ€™ll lift the world for friends?โ€

A girl went to the mountains and said: โ€œTime
I am sad
I am very very happy
I am very very sick
Oh look at the world.
Time is running out and I will die
And be buried in the pretty flowers.
With lots of love in death.
Flowers bloom and death turns into life,
I sleep and thereโ€™s a snake and two women,
I hear the dog of the businessman,
I see snow,
Thoughts grow
There are flowers and Iโ€™m sad because of the snake.

โ€œTime, angel and devil
Time takes lives,
Oh no we must go again
I need more money.
I found money, happy,
Itโ€™s not my fault itโ€™s your fault
Iโ€™m happy but itโ€™s getting bad again
No time for peace. I go down
Iโ€™m angry and soon I will cease to exist
Time runs out. Quickly;
Present. Devil
Death.
Doves bring peace to the world, and people are happy and loving.โ€

World peace, tears of joy,
Sadness.

And here is the other translation:

A man climbed a mountain and then said
โ€œI hope to travel everywhere before I inevitably die and fade into black.โ€
He was confident that he would.
But then he listened to sound of the leaves in the wind
The gnawing of the squirrels and the screech of the eagles,
Just listened and listened, and nature said
โ€œDo you know of the evils of travel?
The injustice and greed and death
The violence and resource overuse
The pits it creates hidden off to the side
I beg of you, can you measure
Your footsteps in a pure way,
In small steps, in tears wiped away, in strength used
To lift up the world and create agreements?โ€
 
A woman climbed a mountain and said: โ€œTime passes
And itโ€™s a sad truth that in life
There is both sheer happiness in
And overwhelming disgust at
The shocking state of the world.
One day it struck me that soon I would die.
I pictured myself buried in a coffin covered with daisies and tulips and sunflowers    and hibiscuses.
And thought about how with my death so too would die my love for not just men but also women.
Thoughts of flowers and death and life,
They awoke within me a thirst for forbidden knowledge and so I pursued a woman I fancied,
And eventually we welcomed a dogโ€™s bark into our family as we pursued marriage before a judge,
But society lied and the stars we had chased twinkled out of existence,
And so grew in my mind
The image of flowers on my coffin as a reminder that society forbids me the knowledge of free marriage.

โ€œTime passed, and neither angels nor devils favoured me for
After an endless wait we learned that my lover had stage two breast cancer,
With shock and frustration I felt as though my world had been spun on its head
For at our darkest time we also struggled for money.
Mounting credit card bills had flown all of our money away, yet we continued to spend,
And then we fought and pointed fingers with accusations
Of gluttony of frivolity of ignorance of confusion that grew increasingly hostile
And it felt like we wouldnโ€™t find peace. And so the downward spiral continued
Of anger and mistrust until we both exploded
And so time passed and passed. We watched the clocks;
Until finally we got a gift. That evil cancer
Had at long last died.
We exchanged olive branches and reconnected, and in elation and celebration fell back in sweet love.โ€
 
The world may never find peace, unfortunately,
A disappointing truth.

Composition

In composing my emoji poem, I first wrote down my ideas in English (which I am not reproducing here, because I do not want to influence the reader’s interpretation), and then I attempted to portray them as accurately as possible using the image-based language. I would type the main words and concepts into an emoji keyboard, hoping they would have equivalents, but more often then not, I had to resort to using emojis which represented similar, but not identical ideas. In some cases, I would use a sequence or collection of emojis, as in the line “โšฐ๐ŸŒณ๐ŸŒท๐ŸŒธ๐ŸŒน๐ŸŒบ๐ŸŒผ๐ŸŒป๐Ÿ’ฎ๐Ÿต,” where I intended the emojis to not ๐Ÿ…ฑ๏ธ read individually but as a single, holistic image.

This process definitely contained more limitations than when reading and translating Bing’s novel, because I was forced to transform my ideas from a subtle, nuanced language into a less descriptive writing system, instead of the other way around. Frequently, I found that there was not a single emoji that would perfectly portray my thoughts, such as there being no emoji for a flower in the process of blooming. Additionally, the concept of time was a central theme for my poem, but the selection of emojis for depicting this idea is rather limited, so I was forced to reuse some of them, reducing the shades of meaning contained in the original text. It is difficult enough to describe complex thoughts and emotions in a nuanced language like English, so forcing myself to explain these in a language with an even more limited vocabulary was somewhat frustrating, at least initially. I eventually became more accustomed to using the emoji keyboard, and by the end, the process became a little more manageable, but surely never completely seamless.

Translation

I decided to have two friends translate my poem, so that I could examine the different ways in which people could interpret emojis. I will readily admit that my text was difficult, maybe even too much so, but I am thrilled at what they both ended up writing. The first translator, whom I will refer to as K, was by far more literal in their interpretation, while the second translator, who will ๐Ÿ…ฑ๏ธ called D, interpolated more from the limited data presented, even though the latter translator still had a fairly literal interpretation. This reveals one of the potential misunderstandings that can arise when using emojis: some people wish to imply much more than others when using the images, leading to varying degrees of understanding. One sees the sequence “๐Ÿ˜ด๐Ÿ๐Ÿ‘ญ” and thinks “I sleep and thereโ€™s a snake and two women” while the other interprets it as, “They awoke within me a thirst for forbidden knowledge and so I pursued a woman I fancied.” The second translator, D, by referencing “forbidden knowledge” may have been thinking of the Garden of Eden during this line (which is quite accurate, because I was thinking a bit about Paradise Lost when writing this poem), but both interpretations are completely valid, as such a text provides as much openness as a work of visual art.

Overall, both translations were relatively accurate to my original text, especially in picking up the themes of time, death, nature, and money, but they each had their own take on some of the more complex segments. For example, the second translator focused on ideas of gender and sexuality in the second and third verses, which was something I wanted to depict, but was not consciously thinking of all the time. It was interesting to see how this narrative arose throughout D’s translation, and I am glad that they were able to catch onto that thread and carry it through more fully than I originally planned.

Meanwhile, I enjoyed K’s more concise interpretation, because it attempted to replicate a potential effect of emojis by throwing out single word images in rapid succession. If we take the translator’s job to present a text in a different language, while attempting to keep it as close to the original as possible, K’s translation seems to do the job nicely. This type of translator has the difficult task of staying close to the original text while completely changing the language, so I respect what they accomplished with the poem.

All that being said, here are three core similarities and differences between the translations and my original poem:

Similarity #1: Themes of Time and Death

This similarity feels somewhat straightforward, as I used several emojis associated with ideas of these themes, meaning there should not ๐Ÿ…ฑ๏ธ any surprise that the translators would pick up on them. I think these ideas are so central to human society and culture, that they are fairly easy to notice in a work, even if the emojis for these concepts are fairly eurocentric (as represented by the coffin and the hourglass).

Difference #1: The Use of Flowers and Nature

I used various flower emojis throughout my poem to convey a sense of nature and its relation to life and death, but both translators interpreted these much more literally than I anticipated. Wherever I used flowers, I thought of them more as a sign for the natural world, and less as literal signifiers for a specific type of fauna, which alters some of the meaning in the poem. I wanted to place nature in conflict with humankind and society, but I do not think that idea came through fully in either of the translations.

Similarity #2: Finance and Jewels

Another important motif throughout the poem is ideas of finance and its relationship to human society. While both translators were somewhat more literal than I intended when using these images, they both recognized its importance and incorporated it nicely into their translations. K focused more on the constant desire for more wealth which society places upon us, while D examined that desire’s effect on the world’s environment and on the individual’s psychological state. Both perspectives are important to consider, and I enjoy how they each portrayed them.

Difference #2: Figurative Language

There were some instances where I attempted to use figurative language and “wordplay” in the poem, which did not quite appear in the translations. I understand that this system partially depends on looking at the world through the structures of the English language, however, which will inevitably create a dissonance in my intentions and another’s interpretation. For example, both translators interpreted the phrase “๐ŸŒฑ๐Ÿง ” as thoughts growing in the mind, while I intended the image to ๐Ÿ…ฑ๏ธ more akin to thoughts being implanted in one’s mind, which eventually grew into general ideologies causing distress, as indicated in the following line: “๐ŸŒธ๐Ÿ˜“๐Ÿ.” While the shade of meaning is slight, some of the forcefulness of language was lost in the translation process.

I am also somewhat disappointed that neither caught my wordplay, “โŒš; / ๐ŸŽ,” which was supposed to mean something akin to “the present is a gift.” It is a somewhat silly joke, but I was a little disheartened that neither of them noticed the pun.

Similarity #3: Sentence Structures

One thing both of the translations mirror perfectly is the use of punctuation and sentence structure (even if they have some comma splices and run-on sentences). This likely stems from the fact that punctuation is an inherent part of our (English) notions of language, so it is something to grab onto and mimic in such a translation exercise. Punctuation generally helps organize our written thoughts, so it is natural to follow this general structure.

Difference #3: The Ending

This may seem subtle, but I think it has an important impact on how one interprets the poem. Specifically, the last stanza in the original emoji poem states, “๐ŸŒโ˜ฎ,๐Ÿ˜ญ, / ๐Ÿ˜”,” which K translates as, “World peace, tears of joy, / Sadness,” and D as, “The world may never find peace, unfortunately, / A disappointing truth.” Both of these are more cynical than I intended, with K’s translation being a little bit closer to my intentions, while D’s maybe picks up on more of the subtext I went for. The crying emoji is ambiguous, as it can ๐Ÿ…ฑ๏ธ interpreted as joy or sorrow, and I was going more for the former. Moreover, I intended the emoji in the final line to depict a sense of relief, but also a feeling of hesitance toward hoping for peace on Earth, but both translators took this image as conveying sadness. As I have implied before, their interpretations are completely valid, and my intentions should not determine how they think about the poem, but I was a little disheartened at their general pessimism.

Digital Humanities

One thing this lab gave me an appreciation for is the potential digital technologies provide in presenting thoughts and ideas to a larger audience, regardless of language barriers. While emojis are still influenced by cultural norms and perceptions of society, they can convey concepts to a wider general audience, breaking through social barriers.

Moreover, this lab shows the variety in forms of ergodic literature, as it does take non-trivial effort to translate emojis into one’s language of thinking. I had previously considered this perspective on literary theory to focus mainly on interactive texts and intense, formally complicated works, like Danielewski’s House of Leaves, but I now realize that even linear and seemingly straightforward works of literature can ๐Ÿ…ฑ๏ธ examined under this lens. Any digital-born text which one cannot simply read as a traditional work can provide a glimpse into how we read and understand texts, demonstrating that our interpretive processes may not ๐Ÿ…ฑ๏ธ as simple as we may initially believe. Any text, whether written in emojis or some traditional language, must necessarily ๐Ÿ…ฑ๏ธ translated in the mind as it is read, because how one thinks of words and language varies from person to person. Sometimes one performs that translation process subconsciously and automatically, as with traditional literature, and sometimes one must consciously examine what the “words” represent, as with an emoji story. But in either case, there is a disconnect between the message that is sent and the one that is received.

Thus, as a digital-born text, an emoji poem demonstrates a fundamental philosophy of Digital Humanities, in attempting to bring the world (i.e. humanity) together through advances in technology, while simultaneously acknowledging a latent futility in truly grasping the subjectivity of another. We are all like robots, connected to each other through a network of ideas and possibilities, but our connections will always ๐Ÿ…ฑ๏ธ limited by inefficient hardware and unforeseen, and sometimes catastrophic, glitches.

Digital Lab #10 – Twitter Bots

Starting this semester, this was probably one of the labs I was looking forward to the most, as Twitter bots have a great potential for both humor and literary intrigue. While some use them for purposes of harassment and the propagation of harmful ideologies (which is an unfortunate potentiality for many digital tools), they can be meaningful and worthwhile when used responsibly. For the purposes of this lab, I created a Twitter profile, which can be found here, and I used this tool to create the JSON code for my bot. Here is what that code ended up looking like:

{
	"origin": [
		"#person1.capitalize# #wish# to #tell# to #person2# the #story# of #storyDesc#.",
		"It #began# in #timePeriod# #country#.",
		"In #country#, there was a #typeOfPerson#, who, despite being a #adj# #typeOfPerson#, was #adv# #adj#.",
		"#person1.capitalize# first #verb# #person2# in #timePeriod# #country#.",
		"But, to #person2#, #person1# #adv2# #verb2# a #adj# #typeOfPerson#."
	],
	"wish": [
		"wish",
		"desire",
		"need",
		"want",
		"have"
	],
	"tell": [
		"tell",
		"show",
		"explain",
		"describe",
		"express"
	],
	"storyDesc": [
		"how #person1# fell in love with #person2#",
		"the war between #country# and #country#"
	],
	"story": [
		"story",
		"tale",
		"narrative",
		"account",
		"yarn",
		"history"
	],
	"person1": [
		"I",
		"you",
		"we",
		"they"
	],
	"person2": [
		"me",
		"you",
		"him",
		"her",
		"us",
		"them"
	],
	"country": [
		"North #country#",
		"South #country#",
		"East #country#",
		"West #country#",
		"America",
		"Canada",
		"Mexico",
		"Brazil",
		"Argentina",
		"Spain",
		"England",
		"France",
		"Germany",
		"Russia",
		"China",
		"India",
		"Japan",
		"Korea",
		"Australia",
		"Egypt",
		"Algeria",
		"#timePeriod# #country#"
	],
	"timePeriod": [
		"ancient",
		"medieval",
		"prehistoric",
		"future",
		"New",
		"Neo",
		"#ordinal#-century"
	],
	"ordinal": [
		"1st",
		"2nd",
		"3rd",
		"4th",
		"5th",
		"6th",
		"7th",
		"8th",
		"9th",
		"10th",
		"11th",
		"12th",
		"13th",
		"14th",
		"15th",
		"16th",
		"17th",
		"18th",
		"19th",
		"20th",
		"21st",
		"22nd",
		"23rd",
		"24th",
		"25th",
		"26th",
		"27th",
		"28th",
		"29th",
		"30th"
	],
	"began": [
		"began",
		"started",
		"gained weight",
		"ended",
		"came to a conclusion"
	],
	"typeOfPerson": [
		"sage",
		"wizard",
		"knight",
		"warrior",
		"professor",
		"student",
		"man",
		"woman",
		"lizardman"
	],
	"adj": [
		"vexatious",
		"pleasant",
		"cheerful",
		"morose",
		"melancholy",
		"phlegmatic",
		"sanguine",
		"choleric"
	],
	"adv": [
		"rather",
		"quite",
		"extremely",
		"incredibly",
		"somewhat"
	],
	"verb": [
		"saw",
		"examined",
		"glimpsed",
		"recognized",
		"beheld",
		"descried"
	],
	"adv2": [
		"merely",
		"simply",
		"completely",
		"honestly"
	],
	"verb2": [
		"appeared as",
		"seemed like",
		"gave the impression of",
		"manifested as"
	]
}

Finally, I used Cheap Bots Done Quick to run the code and post tweets once an hour for about a week. Of the two-hundred-or-so tweets posted as of writing this blog post, here are some of my favorites:

This was the first tweet posted, and I think its absurdity set the stage nicely for what was to follow.
I found the geographical improbability of this scenario quite amusing.
I want to read a sci-fi novel that starts like that.
I will admit that this one, while grammatically correct, makes no logical sense.
This one pairs nicely with the following one, especially given the fact that they were released one right after the other.
It sounds like an interesting plot for a time-travel story.
I think this demonstrates a potential error in the code. It is still funny, though.
This sounds like an interesting fantasy story.
This sounds like part of a complicated love story.
I think this is how the story of Narcissus goes…
Someone retweeted this one. I am not entirely sure why…

I have set the bot to still post once-per-day, and I plan on letting it continue running for a little while longer, just to see if anything else comes from it. Overall, this was a quite enjoyable process, and I may have to create some more bots in the future, because I foresee a great deal of creative potential arising from the media form.

The Process

When developing my bot, I attempted to create scenarios that one could use to begin a story. Accordingly, some of the potential “origins” include someone beginning to tell a story about how two people fell in love or about a war between two nations, or someone making a short, declarative, but somewhat vague, statement about an event beginning or ending, or someone providing a general description of a person that could launch into a greater tale. My goal with structuring the bot like this was to generate potential story ideas that one could expand on in a fully-fledged narrative. While there are computer programs that can generate substantial narrative content, I do not have the coding experience necessary to even begin understanding how they operate, so I figured I would let the computer start the scenario so that I could finish it later if I so desired.

Thus, on their own, the tweets may not appear literarily valuable, because they only tell partial stories, but I believe that even in their incompleteness, they provide something worthy of merit and consideration. In a way, this Twitter bot reminds me of Italo Calvino’s novel “If on a winter’s night a traveler,” because it presents an anthology of story segments, which, when concatenated together, combine into an object of artistic merit. For me, the value of reading lies not in the completion of a story but in the process itself, as that is where the generation of empathy and the understanding of other perspectives becomes available. While one may not find this readily apparent in the tweets shown above, I believe they demonstrate enough intrigue to allow one to pause, even if momentarily, and consider the world they attempt to depict.

The Result

I am grateful for the web application Tracery, which I linked above, as it allowed me to produce the bot in a relatively easy-to-understand manner. While the JSON code is not too difficult to understand, this project would have taken substantially longer, had I needed to code everything manually. That being said, I did encounter a few glitches with the program, including it not always properly saving the work.

In constructing the bot itself, my main focus was on producing grammatically correct tweets, and I believe that I was successful in this endeavor. However, as a consequence, some of my constructions do not make much logical sense, such as the one which states, “You desire to show to me the story of how we fell in love with me.” This may make sense in the context of a science-fiction story, with doppelgangers or deleted memories, but, as an independent thought, it does sound like it was written by a computer that does not fully understand the process of constructing sensical thoughts in a written format. The limitations of the computer program did produce some humorous content as well, such as the tweet which says, “I first examined him in 13th-century 21st-century Neo South North Spain.” I have no justification for this one, but I still find it quite amusing. Although, I am thankful that the bot did not produce many with this form of illogical syntax.

Tweets like this are a consequence of the coding, where functions have a potential to call on themselves for data, so that there lies a possibility of an infinite recursive loop. While this is generally something to avoid in programming (for obvious reasons), I decided to incorporate this methodology in my bot, so that there would be a latent infinity hidden within a seemingly short program. Moreover, this indicates the potential infinity within digital literature, as never-ending loops pervade the stories we encounter every day, even if they are not always readily apparent. Due to this, I consider my bot to have been successful, because it gives rise to an infinity of the finite, or a “vast Infinitude confined” to steal the phrase of another.

Twitter Bots and Twitter Novels

In comparison to the Twitter novel “The Right Sort” by David Mitchell, I consider Twitter bots to have more artistic merit, because they utilize the limitations of the platform more effectively. While Mitchell’s story was enjoyable to read, and I respect it as a general work of literature, it felt more like he wrote a story that just happened to be published on Twitter instead of in a traditional book, rather than him writing a story specifically in consideration for the structures of the website. While my experience may have been different had I read the novel as it was being serialized throughout a week (since it would have been a part of my update feed, as opposed to its own independent webpage), I feel that there are other Twitter projects which make use of the platform much more effectively. Whether one looks at bots imitating historical figures, or real people writing tweets from the perspective of fictional (or fictionalized) characters, a substantial amount of creative energy is present on Twitter, making a standard narrative seem uninteresting.

Again, I greatly enjoyed Mitchell’s novel, and I respect its value as a work of literature, but it did not seem to fully incorporate the structure of Twitter into its presentation. Bots are frequently nonsensical, as mine demonstrates, but they attempt to present considerable information with limited words and structures, paralleling the limited character-count imposed by Twitter. Both the novel and the bots share the same platform, and must obey the same technological restraints, but while the novel appears to fight against these constraints, the bot willingly accepts them.

Bots and Humanity

This segues into a general juxtaposition between human and computer authors, where our digital world blurs the line between the two. While the bot was written by a human (ostensibly) and all the words it utilizes were at one point typed into the computer by a user, its tweets are still considered to by computer-generated. We have entered into an age where programs can automatically create stories, through machine-learning algorithms, leading one to consider humanity’s role in the humanities in the future. I can confidently say that humans will continue creating stories indefinitely, but there may come a day when computer-generated content is regarded seriously by the general public, because now, unfortunately, relatively few people would consider something like a Twitter bot as anything more than an interesting novelty.

Currently, what computers lack in emotional authenticity, they more than makeup for in being fast and efficient at producing content, even if most of that content is ignored as noisy data, lessening the impact when a truly revolutionary work of programming gets produced. While one could view this as computers mass-producing literature, I would disagree, because the prevalence of such programs does not seem to reduce the value of literary works developed by humans. One day, computer-generated literature may be indistinguishable from texts written by humans, but I believe that most people would still feel an affinity for the human-generated content, as it would be seen as more “valuable.” Whether this evaluation is valid is open for debate, but I think that many humans harbor a latent mistrust of digital technology, even today.

In effect, this Twitter bot does not seem uncanny, because it is fairly obvious that a human did not write it, but I have encountered other programs which have produced that simultaneous sense of familiarity and distrust typical of the “unheimlich” (such as this one). Overall, though, we are still far enough away from producing artificial intelligence, so that the results of even the most advanced programs feel more comedic than artistically valid, and they do not yet fully generate that sense of horror typically effectuated by robots in science-fiction movies. While things may be different in the future, for now, we do not have to fear an uprising of our robot overlords.

Digital Lab #8 – Typography

Mark Z. Danielewski has become well-known for experimenting with typography in order to provide additional visual meaning and intrigue to his texts. Nowhere is this more apparent than in Chapter IX of House of Leaves, where form, content, medium, and material all coalesce to depict a labyrinthine structure of text while describing the maze-like qualities of the house itself. Any page in this chapter could be taken as an example of experimental typography, but the ones which struck me the most (pun intended) are presented in the images below:

Page 110 of the novel
And Page 111

In particular, in developing its relationship between content and form, this passage complicates the relationship between Zampanรฒ, Johnny Truant, and the reader and how it mirrors and challenges the mythological relationship between the ancient Greek figures of Minos, Daedalus, and Theseus.

The most obvious typographical element of this passage is its use of red-colored and struck-through font, which already demonstrates a notion of attempting to hide oneโ€™s creation. A note by Truant mentions that the โ€œ[s]truck passages indicate what Zampanรฒ tried to get rid of, but which [Truant], with a little bit of turpentine and a good old magnifying glass managed to resurrectโ€ (Danielewski 111). This quote relates Zampanรฒ to the labyrinth owner Milos, in that both attempt to obscure their creations (the passage itself in the case of the former, and the Minotaur in the case of the latter) within a maze, while Truant, acting like labyrinth-maker Daedalus, allows the passage to live on, albeit within the realm of a maze-like structure. Moreover, his usage of the word โ€œresurrectโ€ seems significant, as it demonstrates Truantโ€™s godlike role as the editor of the work. He has the ultimate say on how the text gets represented, even if it contradicts Zampanรฒโ€™s apparent intentions, so that he, like Ovid’s depiction of Daedalus, โ€œto unimagined arts / โ€ฆ set[s] his mind and alter[s] natureโ€™s lawsโ€ (Ovid VIII.189-190).

Moreover, the supposed evil of the Minotaur and the good of the Minotaur-slayer Theseus is brought into question, by how Zampanรฒ describes the two. Specifically, he mentions that โ€œMinosโ€™ maze really serves as a trope for repressionโ€ (Danielewski 110), which the text itself visually depicts by not only being struck-through, but by also lying within a footnote of a struck-through passage. Zampanรฒ attempts to repress his own work, but we as the readers bring it to the forefront of our attention and do not allow it to lie in peace. We attempt to brave the labyrinth and look past the lines obscuring the text, but in doing so, we risk getting lost in the intricate details of maze of text, ignoring the larger picture. The passage mentions that โ€œmost of the Athenian youths โ€˜fedโ€™ to the Minotaur actually starved to death in the labyrinth, thus indicating their deaths had more to do with the complexity of the maze and less to do with the presumed ferocity of the Minotaurโ€ (Danielewski 110). Extending this metaphor of the readers being like the Athenians traversing the labyrinth, we can easily give up on the text in this chapter, leaving the integrity of the maze whole, accepting its complexity. Conversely, if we wish to plunder the labyrinth of words and slay the textual Minotaur, we would become like Theseus, whom Zampanรฒ describes as a โ€œdrunken, virtually retarded, frat boy โ€ฆ who without a second though hacks the Minotaur to little piecesโ€ (Danielewski 111). If we want to break free of Chapter IX, we will necessarily break through the loop of references and footnotes, ignoring the grand structure it attempts to set up. Moreover, by analyzing individual passages of the text, we cut it up into little pieces, and while these are more manageable, we ultimately forsake the form of the whole. The text seems to leave us with a lose-lose proposition: we either stop reading and perish in the maze, or we force our way through the text and obstinately destroy the sanctity of the work. One of the first things the novel tells is โ€œThis is not for youโ€ (Danielewski ix), and by ignoring this message, we have become intruders in the realm of the novel, inserting ourselves into a place not designed for us.

Works Cited

Danielewski, Mark Z.ย House of Leaves. Pantheon Books, 2000.

Ovid.ย Metamorphoses. Edited by E. J. Kenney. Translated by A. D. Melville, Oxford University Press, 2008.

Digital Lab #7 – Political Data-Mining

As I alluded to toward the end of the previous lab, I consider all writing to be political, regardless of subject matter or authorial intent. To summarize what I described there, I believe that any form of communication contains inherent biases, which we should recognize and not take for granted. While one’s words may seem harmless now, future retrospection will only exacerbate its potential flaws. I believe that this is nowhere more apparent than in the corporate apology. Often texts like these attempt to dispel controversy, but due to their unapologetic rhetoric and ambiguous phrasings, many quickly find fault with these messages, only leading to greater political strife. As an example, consider Blizzard Entertainment‘s response to its decision last October to ban a player named Blitzchung from competing in their tournaments after he made a comment in support of the Hong Kong protests that were then (and still are) raging. The company’s response (the text of which will form the basis of this lab) was criticized for merely apologizing for “acting too quickly,” and many felt that their financial relationships with China directly impacted their decision to not completely rescind their ban. While I understand that the protests occurring in Hong Kong derive from complex social, historical, and political debates, and I am by no means an expert on the subject, I still found Blizzard’s conduct to be overbearing and extremely reactionary, for what was a brief comment. I understand why they would not want players to spout political messages during their events, but I feel that their punishment and subsequent “apology” were rather draconian, and I was curious how data-mining tools could give concrete evidence of the political evasion latent within their rhetoric.

Tools and Data:

Before describing my results, I should explain the tool I used and how it displayed my results. I utilized Voyant, a digital data-mining tool much more powerful than Textalyser, and the results can be seen in the image below:

The results produced by Voyant

I was a fan of this tool’s mix of visual and textual data, as it not only presented useful information, but it did so in an easy to understand format. While the initial page was a little overwhelming, it quickly became understandable, and I was able to preview most of the data effectively. The “Cirrus” text-visualization in the top-left concisely expressed the most commonly used words, giving a quick overview of the main results, and the “Reader” in the top-center provides a handy tool to search for specific words and determine their frequencies. These modules combine to allow one to select a word and see all the places it appears throughout the text. Finally, the block in the top-right was easily modifiable, and it provided a variety of different text-visualization methods, the current one being “Trends,” which displays the frequencies of different terms in different segments of the text. While I did not fully understand the data being presented in many of the text-visualization methods, such as “TextualArc” and “Mandala,” they were all interesting to look at and provided for unique interpretations of the text.

Specific Results:

Now looking at the specific results of the data-mining, I first observed that the most commonly utilized word was “tournament,” the second was “Blizzard,” and the third was “players,” while the phrase “Hong Kong” only appears twice, and the word “China” only once. This fact immediately shows that the apology was more focused on the company and its event and players rather than on the controversy and its potential impacts. One of the author’s main points is that the company wanted Blitzchung’s interview to focus on the game itself and not on any political situations outside the event, and the text correspondingly accomplishes this by focusing more on the tournament than on the political impacts of its decisions. Moreover, the political term “world” mostly appears at the beginning of the text, while the words “tournament” and “players” are much more evenly spaced. This indicates that while the company addressed the potential implications of Blitzchung’s statements at the beginning of the text, it was constantly more focused on its own tournament and the impacts of Blitzchung on the other players. Moreover, the company’s name appears mostly toward the end of the text, so that the text ends with a self-centered exploration of its own values and viewpoints. In effect, the text addresses the political statements only as much as it needs to, and then attempts to enforce Blizzard’s will and justify its actions. The article frequently utilizes plural first-person pronouns (“we” 29 times and “our” 23 times) to enforce its authority, while also obscuring the notion of a singular author (it only uses the word “I” three times, despite supposedly being written by one person). Thus, the text demonstrates the faceless corporate aspect of Blizzard’s decision which was primarily focused on financial implications and ignored any concerns regarding human rights. It lacked humanity in the face of inhumanity.

Poetic Experimentation:

To complete this lab, I took Blizzard’s “apology,” cut it apart, and created my own poetic work in an attempt to provide personality to a faceless text:

My poem taken from Blizzard’s statement

When creating my poem, I applied the data collected by starting off with questions and statements about Hong Kong, and with a hopefulness of people being able to share their opinions without fear of censorship. I allude to a place that Blizzard describes as “safe and inclusive” and where “Every Voice Matters,” but which their actions did not help to create. However, just like the article, I contrast this perspective by ending with an exploration of the greedy corporation which only wishes consumers to think about its products and ignore any potential impacts on the political reality. The article contained three variations of the phrase “focus on the game,” and I wished to include these to highlight the myopic dystopia that the article implies. I end the piece with the phrase “epic entertainment”: a stock and meaningless phrase that summarizes Blizzard’s entire rhetoric. Effectively, my poem demonstrates the transition from political optimism, where we could create a place to explore different ideas and perspectives, to political antipathy, where any mention of “social or political” issues contradicts a corporate ideology. I am trying to return a voice to the silenced.

Digital Lab #6 – Poetic Data-Mining

Jordan Abel’s process in writing “Injun” inspires one to consider and question one’s relationship to the political and ideological undercurrents of historical texts and how they relate to present-day inequalities and injustices. By data-mining novels from and about the “Old West” for instances of such a derogatory term, and then using these texts to craft his own poetry, Abel uses the voices which have historically silenced indigenous peoples in order to develop his own voice and put forward his own perspective on the genocides which occurred on the land we refer to as “North America.” More generally, following Abel’s methodology allows one to examine how any text, regardless of content or region of origin, can be utilized to develop one’s own artistic voice through a personal relationship to the text. Whether one utilizes this methodology for political purposes, for comedic effect, or for some other form of artistic expression, a new and valuable perspective will be realized, even if all the words come from somewhere else. In my case, going into this lab, I wanted to explore facets of my identity as they relate some novel which had a significant impact on my life, and I think I created something worthwhile.

My Process:

For a source text, I chose James Joyce’s Ulysses, and I searched for all instances of the word “Jew.” To explain my word choice, it would be helpful to know that I was raised Jewish (going through many of the traditional ceremonies), but I do not currently practice the religion. I still identify as Jewish, to some extent, but I do not consider Judaism to be in the forefront of how I construct my personal identity. (It is difficult to explain, to be honest, because I myself do not fully understand how Judaism factors into my conscious perception of myself. It plays some role, but it is not central.)

I chose Joyce’s (in)famous novel, because of the strange sense of camaraderie I felt with the protagonist, Leopold Bloom, who also is “technically” Jewish, even if he does not fully identify as such. There are other reasons why I thoroughly enjoyed this novel (despite the fact that I understood only a small percentage of it while reading), which I will not discuss here (as that would necessitate a blog of its own), but I frequently think about its depiction of the effects of an inherently anti-Semitic culture on a Jew’s construction of self-consciousness. Thus, I wanted to use Joyce’s text as a means of developing and considering my own Jewish identity and my relationship with the history of the culture.

After deciding the text and word came the process of actually data-mining the Project Gutenberg edition, which, as you could imagine, was rather tedious. There were eighty-one instances of the letter combination “j” – “e” – “w” (most of these occurrences were the actual word “Jew,” but a few were as part of the word “jewel”), and compiling all these instances took a decent amount of time. One of the unusual circumstances I encountered was the fact that the last chapter of Ulysses contains multi-page spanning sentences, some of which would contained an instance of my chosen word, so I had to copy long strings of text into my source document. In order to incorporate these “sentences” into my poem, I decided to make their font size as small as possible while still being “legible.” Next, I printed out the source document, which can be found here:

Then, I took all the sentences which struck me as particularly meaningful, cut them up, and arranged them on a blank sheet of paper. Feeling satisfied with my end result, I finally recreated the poem digitally in a word processor. Below is a photograph of the physical poem and a PDF of its digital recreation:

The original, paper version

I will not discuss the actual content of the poem, as I want to leave it open to interpretation.

Comparing Methodologies:

While my process in developing this poem was inspired by Abel’s data-mining methodology, there were several key differences. Namely, I only examined one text while he examined many, meaning his work ultimately contains more material (although, my poem technically has more words (nearly 16,000), but most of them are effectively unreadable). However, a more substantial difference is that when crafting the poem itself, I was not as concerned with the ways in which my source text appropriated the word in question, as I focused more on my personal reflection. That is not to say Abel’s poem is not personal (as it most assuredly is). Rather, I mean to say that my poem did not fully (or at least explicitly) take into consideration how Jewish people were represented in early-twentieth-century literature, and how our modern-day conceptions of Judaism were developed by these representations.

In effect, I would say that my poem was politically inspired, but not fully politically motivated. However, I would also argue that any piece of writing is politically inspired, because it will necessitate ideological assumptions which cannot be taken for granted. Even texts which most would not describe as political (such as a children’s book) have inherent biases of what it considers valuable, and one should always consider the causes and effects of these assumptions. For example, some of the novels about the “Old West” which Abel used might have been merely considered popular works in their time, completely disconnected from a political reality: they were just “fun” tales about “Cowboys and Indians.” However, given the retrospective of a hundred years, more people now understand their problematic depictions of indigenous peoples and the importance of challenging these politically motivated representations. Ultimately, there is no way to express oneself without being at least subconsciously political.

Print and Digital Art:

I wanted to develop a digital recreation of my poem, as I thought it would look more visually appealing, since the crooked strips of paper would be replaced by orthogonal text boxes. However, I quickly realized that moving text boxes around a word processor is actually a less precise method than moving around strips of paper. Add to that the fact that the document consists of nearly 16,000 words contained on one page, and you get a computer which started to lag considerably. Considering this, I am not entirely sure why I created a digital reproduction when I have a perfectly nice-looking physical version, but I think this speaks more generally to the relationship between digital and physical texts.

In particular, this lab involved a text originally printed in a book a hundred years ago being converted into a publicly-accessible digital document, which was then data-mined to create a private digital document, which was then printed out and physically modified to create a physical work of art, which was finally recreated using digital means. This constant conversion process between the digital and the physical shows how they are in conversation with each other, but that in each conversion, something has to be lost or omitted. When moving from physical to digital, one loses that tactile sense of paper which can be integral to one’s understanding of a text (just look at the pages in Abel’s “Injun” where the text appears upside-down). Additionally, in the conversion from digital to physical, one loses the wealth of meta-data and computational power stored in electronic files. (A Word file contains more data than a printed-out Word document, even if not all that data is readily accessible). While the physical and digital can imitate each other, they often inaccurately depict each other.

This could be one of the reasons for why Abel chose to physically publish his book: to demonstrate how information is lost in these conversion processes, leaving us with a misrepresentation of the original idea. Historically, indigenous voices have been filtered through a settler ideology, meaning many cultures have been improperly represented in literary culture, leading to grand misconceptions being developed about them. Abel demonstrates this loss of data in his poem and expresses the violence and inequity which result from this lack of communication.

However, there is also a positive relationship between the physical and the digital, as only through their connection could a project like Abel’s or mine be created. Through understanding the strengths and weaknesses of each medium, one can develop a meaningful perspective on how different methods of communication can be effectively utilized to create something meaningful. Through this relationship, new art can be formed.

To be more specific, I believe that anything can be art if one interprets it as such. Thus, due to how my poem depicts my relationship to the physical, the digital, and my Jewish identity, it presents itself as art to me. Moreover, I consider it to be valuable, as it provides insight into my personal perspective of the world, and I believe that any text which attempts that (which is basically every text) has some value. These notions are somewhat ambiguous, and I know many have written countless volumes attempting to define art and value, but I think attempting to create a universal and objective definition becomes a self-contradictory pursuit. Ultimately, the way I determine if something is art and if it is valuable is by asking, “Is this art to me? And is it valuable for me?”

Anything else would be assuming too much.

Digital Lab #5 – Data in Danielewski’s “Clip 4”

Now that we are starting to use data collecting methods in our analyses of literary texts, I have realized how detail-oriented and deliberate the process needs to be in order to discover any meaningful results. While one could take a large amount of text, plug it into some digital tool, and analyze the results, the data would be much too general to make any specific and meaningful claims (although that more general information could have its uses if someone wants to make generalizations or large-scale comparisons). However, to faithfully analyze a text using digital tools to supplement, but not to replace, manual close-reading techniques, one needs to be specific in choosing which data to examine, in order to avoid collecting a surfeit of complex information. Additionally, throughout the process of this lab, I have discovered the value of digital tools in making manual processes more efficient and in diagramming the data developed through reading. In effect, both “traditional” and digital methods have benefits and weaknesses, but they work well in conjunction with each other. But enough generalization; here are some of my results:

Traditional Data-Collecting Methods

In analyzing Danielewski’s “Clip 4,” I considered the ways in which characters directly refer to other individuals, in order to examine any distinguishing characteristics that may give insight into personality types. I also performed this in order to find if there existed any distinguishing factors between how people provide references in academic prose versus in standard conversation, and I considered how this may reflect on academic institutions more generally. In particular, for my traditional data-collecting method, I compiled all the direct references by name to other persons, fictional or real, that I could find in the text, as well as which character made the reference, and a brief description for why that reference may have been made (although, this method used a spreadsheet to organize the information, so it was still rather “digital”). The data is given in the file below:

Reflecting on this data, I made some useful discoveries about the text, such as how the character Toland Ouse (either in a direct quote or as paraphrased by Realic S. Tarnen) makes thirty-eight references to others (not including all of Audra’s pseudonyms), while, in comparison, Tarnen makes twenty-nine. I consider this to be unexpected, because academic prose has a reputation for frequently making references to other texts and their relationships to the objects of study, while normal conversations usually do not feel as referential. This could indicate a misconception of mine in the levels of intertextuality in our communications, or it could indicate an element of Ouse’s character. Specifically, by making so many references to figures of popular and academic culture (some famous, some obscure, some real, some fake) he attempts to situate himself in his surrounding culture, potentially generating a sense of ethos and trust. By indicating his familiarity with significant cultural figures, Ouse cements himself as a member of society who can relate to others on a general level. However, this comes into conflict with Tarnen’s admittance that their “shallow knowledge of music” forced them to “double-check [Ouse’s] references later” (179),1 while Ouse was not familiar with “Darc’s The Zoo: Costruire Paradisi Di Buio” (180). This conflict indicates the difference in social group that Ouse and Tarnen occupy, in that they are unable to fully comprehend each other’s references to what they each perceive as important works.

In academic prose, writers make references to other works in order to situate their own work in a context of research, so that it will be seen as valid and important. This can be seen in the Caroline Weld’s research suggestions in the comment: “Might want to have a looksie at Yi-Fu Tuanโ€™s Topophilia, Randy Malamudโ€™s Reading Zoos and Cary Wolfeโ€™s Animal Rites. Matthew Calarcoโ€™s Zoographies too. Top of my head. We can revisit” (171). This comment could be seen as Weld attempting to further ground Tarnen’s research in already established texts. However, those references are meaningless if the reader does not have any knowledge of them, and, for all intents and purposes, they may as well be fictitious. Thus, “Clip 4” demonstrates the fundamental rift that can exist between different cultural communities when they are unable to understand the significant figures and works in each other’s world. A sense of tension develops between Ouse and Tarnen, as well as between the reader and the text, as each attempts to grapple with the prerequisite knowledge required in order to effectively communicate with the other.

One action that could have further developed this method of data-collecting would have been to search each name referenced and determine the likelihood of it referring to a real person. Determining which character is more grounded in our reality, and which is more based in the fictional world of the story, would have provided great insight into how each character operates in relation to the rest of the text. Unfortunately, this would have been a rather time-intensive project, which I will leave for future considerations.

Digital Data-Collecting Methods

For the digital part of the lab, I utilized Textalyser in order to analyze the same topic as above and to find other significant differences in the ways we reference others in our communications. Specifically, I analyzed all the paragraphs of Tarnen’s academic prose in which they referenced another person or text, and compared the results to all the paragraphs in which Tarnen directly quoted or paraphrased one of Ouse’s references to another person. I also compared these results to all of Weld’s comments that contain a reference to another person (although this data in particular was relatively sparse, so the results should take this into consideration). I recorded data in this manner in order to ascertain if there was a specific distinction between how characters communicated and what kinds of words they utilized when referring to others, and I was curious if this would reflect at all on how the manners in which we communicate differ between an academic setting and a more personal environment.

First, here are Textalyser’s general results for the three pieces of data:

The general readability results for Tarnen’s academic prose.
The general readability results for Ouse’s dialogue.
The general readability results for Weld’s comments.

The first value I noticed was the distinction between the Gunning-Fog Index between the three texts: Ouse and Weld have similar results while Tarnen appears to write substantially more difficult prose. This result is fairly straightforward, however, as any form of intentional writing is likely to be more difficult to parse than a conversation or a handwritten comment. This also relates to the drastic distinction in the average number of words per sentence, because it is easier to craft long, intricate, and complex sentences in a written format as opposed to on-the-spot speech.

One possibly unexpected result is the fact that Tarnen has the lowest value for lexical density (70.8%), while Ouse’s score is slightly higher (73.2%), and Weld’s is drastically greater (93.8%). While Weld’s score could be attributed to the smaller sample of text, and the fact that most of the text analyzed consisted of names of people and titles of works, the relationship between Ouse and Tarnen’s scores is unusual. This could indicate that academic prose is more formulaic than informal speech, and that there is an expected pattern for how we should refer to other works, while conversational speech has a more impromptu feeling (I personally remember learning to cite sources in middle school by using templates). This data could also indicate a more fundamental difference in how Tarnen and Ouse communicate; however, this result can be elucidated much more clearly through the word-frequency tables given here:

Tarnen’s filtered word-frequency results.
Ouse’s filtered word frequency results.
Weld’s unfiltered word frequency results (they are unfiltered due to the limited amount of text).

There is a great deal of information packed into these three tables, and I could not possibly uncover it all, but here are some of my initial observations. First, Tarnen’s prevalence of references to Startle and Caokrai (two scholars) indicates how much of the research on “Clip 4” (the film inside the text) is based on the works of these two individuals. Tarnen could be seen as attempting to situate their work in the research of these two significant academicians, as much of the first half of the text discusses their arguments. Tarnen admits that the film “Clip 4” has not “in any way yielded an academic industry” (170), and this possibly provides justification for why they have to rely primarily on works of Startle and Caokrai.

Second, Ouse frequently utilizes first-person pronouns (“I” and “me”), indicating that his references are made as a reflection on their relationship to himself. Specifically, Ouse could be seen as using his familiarity with others in order to bolster his own reputation and how he relates to these significant individuals, enforcing the previous argument about him desiring to develop a sense of ethos and trust with Tarnen. This fixation on himself can be seen in the text when he describes the video of his daughter Audra drowning. His main takeaway at the end is that “She drowned that night. Alone. Calling out for me. Her lostโ€” last call. Unheard. And yet somehow still witnessedโ€ (184, emphasis added), so that even when reflecting upon her death, he still considers its relation to himself. Even in this traumatic scene, he inserts himself and the relevance the story has to his own existence.

Finally, while the data is limited, Weld’s use of the second-person pronoun “you” indicates that they are primarily focused on Tarnen and the state of the essay. All the references made by Weld are in the service of Tarnen, implying a potential hierarchy between the two characters where the former wishes to please the latter.

More still can be gleaned from this data, such as why Tarnen frequently uses the word “man,” or how Ouse uses the word “too” fairly often. However, exploring these possibilities would likely create even more questions with unclear answers, so I will again leave that for later consideration.

Visualizing Data-Collecting Methods

As a part of this lab, I also utilized the application Gephi in order to graphically visualize the manually-collected data above. I was, fortunately, able to import the spreadsheet into the program, making the data entry process much shorter, and I think the end-diagram nicely captures the information. Here is an image of the final result:

Visualization of data collected from part one. Each node represents a referenced individual, and the arrows indicate the relationship from referencer to referencee.

While no new information is included in the above image that cannot be found in the spreadsheet (and in some sense, the spreadsheet contains more information), the image works well as an accompanying element to clarify the many rows of text in the excel file. Moreover, I think this idea applies in general: visual aids work well to explain and succinctly summarize one’s data, but they should rarely be used as the only means of expressing such information, because some important details will be lost in the process. It would be difficult to develop a diagram that contained all the data collected while still looking pleasant.

Comparing Data-Collecting Methods

Now that all the data-collecting and organizing processes have been completed, it is time to consider each methodological approach’s strengths and weaknesses, because no one method is inherently better than another. The first thing I should mention, however, is that manually collecting data is a rather tedious process. Having to gloss over the entire text looking for named individuals took a decent amount of time to complete, and I do not feel entirely confident that I found every single person mentioned. Humans are generally error-prone when it comes to finding minute details, so all analysis derived from manually-collected data needs to take the potential for mistakes into consideration. Conversely, computers do not make mistakes (except in the rare chance where a cosmic ray changes a byte of data in its memory banks). Any mistake from computer-collected data will likely be due to an issue in the computer’s programming, or an issue in the user’s request.

However, while computer-collected data may be more “reliable,” it is often more general and harder to apply to a specific analysis. Specifically, in this lab, I was able to collect data for a particular question I had about the text, and I was able to choose for myself what was important and what was unnecessary. Even though there may exist some ambiguity as to what should be considered important, I had the personal freedom to make that decision for myself. However, the text-analyzing software utilized in this lab did not provide me with as much freedom to determine what data was significant and should be recorded (there are some options in the program, but they are still rather general). Thus, I was forced to apply more general data to a specific question, and I felt this provided with slightly less analytic opportunities. Thus, to summarize, manually-collected data, while more difficult to collect, has greater variability and can be more easily targeted for a particular question. Conversely, computer-collected data is much easier to collect, but due to this ease, it will generally be less specific and less personally detailed.

However, the above juxtaposition may only work in the context of this lab, as I am still new to considering literature from an analytic, numerical perspective. This is also one of the difficulties of this methodological approach to literary studies: there are some things that are difficult to quantify. While I looked at the number of references utilized by different characters, and examined word counts of different sections of the text, I could not objectively quantify the weight of each reference made, and not each use of a word carries the same weight. Some references seemed more important than others (such as Tarnen’s discussion of Startle and Caokrai), but others could easily disagree with my analysis and provide evidence against it. Unlike a mathematical theorem, there is no way to definitively prove most analyses of a text, and any collected data may be subject to scrutiny and dissent. In effect, any literary study will miss that sense of pure objectivity typically associated with scientific research, and any analysis should take this into consideration. However, this is not an inherently negative concept. What literary studies lose in objectivity, they more than make up for in the opportunity they provide for subjective thinking. While the scientific researcher must always fear not being objective enough, the literary scholar is allowed to consider data subjectively and analyze how personal biases and experiences have value in making conclusions. As I mentioned above, the manually-collected data can be targeted to answer a particular question of my own, and even the digitally-collected data was derived from my own judgments and discretion. I could choose which parts of the text I considered to be important without fear of being “objectively incorrect.” Thus, while this data may lose its value as a purely scientific artifact, it gains value as a human-developed object that one can utilize as a tool for exploring a personal relationship to a text.

Finally, as mentioned above, the process of data visualization helped to clarify and to explain the data, even if it did not technically provide any new information. While I would not go so far as to say that this visualization process was a necessary part of my data analysis, it allowed me to reflect more on what I considered as important, and it gave me the opportunity to numerically weigh that importance against the rest of the data. Overall, I viewed data visualization in the context of this lab as a nice way to quickly explain my analysis in an easy-to-understand diagram, but any detailed analysis will generally require more than just a pretty picture (unless the diagram itself is the focal point of one’s research).

Note:

  1. All references are to Mark Z. Danielewski’s “Clip 4” which can be found here.

Blog Post #2 – All About Data

While analyzing the origins and methods of processing data may seem tedious, I have found that such a discussion carries great importance when considering the humanist’s relationship with the text. In particular, we should always be cognizant of where our data comes from, if it has been processed, and if so, who processed it. Without such considerations, we may confine ourselves to subpar versions of texts when superior ones are accessible, or, conversely, we may spend excessive amounts of money and resources on acquiring high-quality reproductions when free public domain resources suffice for our purposes.

A Warning

Rather than just speaking in generality, though, I will give an example. I am currently in a book club, and we are reading (as strange as it may sound) Laurence Sterne’s The Life and Opinions of Tristram Shandy, Gentleman. A member of the group purchased a copy of the text (which I will not refer you to for reasons that will become apparent momentarily) which seemed strange in comparison to every other person’s version. In particular, the formatting was awkward (e.g. all the page numbers were in Roman numerals), the chapter designations differed from ours (the owner of the text ended up reading twice as much as everyone else because of this), there were no explanatory notes (which are not required, I guess, but are incredibly useful in such an old and confusing novel), and the text did not even have a copyright page or any of the usual prefatory material found in a book (making it seem like something you would find on the black market (who would buy a copy of Tristram Shandy on the black market, however, remains an open question)). We eventually discovered that this person’s version of the text was a mere replication of the public domain Project Gutenberg reproduction, and I am convinced that whoever “published” the text simply copy and pasted from this website. All of us in the book group were rather shocked at the shadiness of “publishing” a text in such a state, and I take it as a lesson to always check for the quality of a text before purchasing it.

I bring up this story to demonstrate that the transition from raw to processed data is not always a positive process, but can diminish one’s ability to understand the material. Thus, when analyzing data, we should always ascertain that our methods of processing always either improve the text or allow for unique interpretations of the text and that we never simply release an inferior version of something already widely available.

The Procession of Data with Particular Reference to Tristram Shandy

I would now like to analyze how this piece of humanities data (i.e. the text of the novel) has been processed. When thinking about how Sterne’s novel has transformed from raw to processed data, I developed the following diagram (which I will admit right now is rather basic, but I think it will help elucidate my thoughts):

Diagram indicating how Tristram Shandy moves from raw to processed data.

At the top of the diagram is data in its rawest possible form: entirely contained within the mind of the author (in this case, Sterne). From there, the author writes these thoughts down, creating a manuscript. This is the rawest data accessible to others (at least if it is made publicly available), and it is processed to the extent of the author’s cognitive filter, which seems to be rather minimal in the case of Sterne. Next, the author publishes the manuscript into a first edition, which is generally the first text available to read. Given the large editing and revision process generally necessary to turn a manuscript into a published book, the data is considerably more processed, but still reminiscent of the urtext. If the work is successful, as Tristram Shandy was, further editions are published which potentially fix any typographical mistakes, include author prefaces or illustrations, and reflect on the work’s success. While these versions are more processed than first editions, they do not differ too drastically. Next, after the text has entered the public domain and established itself as an important historical work, critical editions are published which contain explanatory notes and selections of seminal essays, like the Norton Critical Edition or the Oxford World’s Classics Edition, and online public domain versions are made available through resources like Google Books and Project Gutenberg (although, if my narrative above carries any weight, these versions should only be referenced lightly). The former of these generally are the most processed versions of the text accessible, because of the wealth of information added to the original data, while the latter are frequently reproductions of the early editions of the text, and hence are arguably less processed than earlier efforts. Finally, throughout all these processes of processing, theorists and critics busily analyze the text, using various theoretical frameworks to look for meaning, or using various meanings to justify theoretical frameworks. Analysts may compare how the text has changed throughout the years, or they may be ambivalent as to which version to which they refer. Only at this stage does the data transform into its most processed form, as not only has the text been elaborated upon, but, moreover, only the elements necessary for analysis are included. In effect, the analyst takes a text, determines which parts are most important, and casts asides the rest (not necessarily because the rest is unimportant, but because only a limited amount of the text can be discussed in a reasonable amount of time (if we had all the time in the world, then this would likely not be an issue (but that is going down a rabbit hole way beyond the scope of this blogpost))).

I think this diagram indicates that processing data is the only way to get meaning out of a text, and that while too much processing may hinder one’s ability to successfully interpret a text, everything we do when looking at a work is a system of processing data. One thing this diagram omits, however, is how data becomes processed as it enters into the reader’s mind: transforming from words on a page or screen to a cognitive understanding within the interpreter. In effect, there is no way to observe data without processing it to some extent, as this is the only way to extract meaning.

A Discussion of Digital Data

As a means of investigating the relevance of digital tools to studying literary texts, I put the first two volumes of Tristram Shandy into a text analyzer to see how the results compared with my own experiences (I have to admit that one of the benefits of online public domain versions is how they expedite the process of copy and pasting large amounts of text (I would not have done this part of the assignment if I had to rewrite the entire text)). Overall, I found some not-so-surprising results as well as one result worthy of more investigation. The unsurprising results include the prevalence of masculine pronouns (likely typical of an eighteenth-century novel), the personal pronoun “I” (likely typical of a first-person novel), and the second-person pronoun “you” (again, likely typical of a metafictional novel (I would need more data about novels from similar genres and time-periods for a more accurate analysis, though)). The unexpected result is the prevalence of references to the side-character Uncle Toby, indicating that he may be more important than the work initially lets on, but this would require some more careful close reading in order to find a suitable explanation.

These results demonstrate that digital tools can improve one’s interpretative abilities of shorter works like novels and poems, as long as they are utilized in conjunction with traditional close-reading techniques. Any project which relies on an analysis of a large body of works (something like all the works of Shakespeare), or involves interpretations beyond close reading (like geographical mapping), would likely require a stronger reliance on digital tools, as doing everything manually would be unreasonable. However, for an analysis of a single passage, a digital tool like the one utilized here seems somewhat unnecessary and might not provide any meaningful results. As I am yet unfamiliar with most tools, I am sure ones better suited for smaller selections of data exist, but as it stands, I only see value in the use of digital tools to analyze humanities data in conjunction with traditional methods and as a means of making manual processes more efficient. I am excited, however, to see different ways in which digital tools can interact and interpret literary texts.

Digital Lab #4 – Data and Literature

As part of this lab, I altered code developed by Nick Montfort. Since I do not know a way to upload my HTML file to WordPress without a paid account, I will link to a page containing the code here. (I also submitted the HTML file with this URL for the assignment.) Additionally, here is the source for the photo used in the HTML code: https://www.pinterest.com/pin/391039180123064558/.

General Thoughts

Anyway, this lab allowed me to re-enter into the mind of a programmer, which I have not had to do for about two years. Even then, I was only working with simple Java programs, so it was nice to explore something with a little more depth and purpose, even if I did not have the coding background to give expression to all my thoughts. (In this sense, writing code contains many parallels to writing prose essays, because both require one to give expression to abstract thoughts in a manner understandable to the intended reader. One of the main differences, however, is that in the case of the former, one of the intended readers is the computer processing the code, in addition to the human readers working with the code.) For example, I wanted to display the names of colors in their actual color (so the word “red” would look like “red“), but I could not figure out a practical method of doing so, despite scouring the web for answers. Other than this little snafu, however, I am proud with how my final product turned out, especially with how the text appears to materialize on the page of a blank book. Moreover, I was able to modify the code to allow various nouns with different verb conjugation patterns, which allowed for more freedom of expression while maintaining grammatical accuracy. While it may not be as complex as some of the other remixes of Nick Montfort’s work, I think it went well for my first foray into HTML.

Data in the Digital Humanities

This lab thoroughly demonstrated the different ways data can manifest itself in the Digital Humanities, and highlighted how the distinction between raw and processed data is not always well-defined. For example, Nick Montfort’s original source code was raw data for me, because it was on what I based my own project. Based on Eileen Gardiner and Ronald G. Musto’s definition it was “data in its original format” that had to be processed and modified to fit my purposes (32). However, once one looks at the web-page itself, and not the source code, the distinction between raw and processed data becomes blurred, as one could argue that after the computer runs the code, the data has been “collected and organized” (32). This brings up an interesting question for studies in the digital humanities: what is the “real” data that one analyzes? Is it the text which appears on the screen, or the code written by the programmer? Or, is the “real” data the 1’s and 0’s housed in the computer’s memory banks that neither the analyzer nor the original author ever have direct access to? Are Gardiner and Musto correct in claiming “the digital ‘0’ and ‘1’ reduce all humanistic material to the same common core of data and mode of representation” (36)?

While there are no clear answers to these questions, a significant component lies in how the data is being used. For example, I would argue that the raw data in this lab is the source code, because that was my main focus in developing my program, while the processed web-page was processed data, as this was the final product. However, if someone were to discuss the content of the web page itself, then that would be that person’s raw data, as it is the artifact under investigation. In this case, the object would be studied as a text, like a book or a poem, but because of its non-static nature based on random number generation, the text becomes an independent object of study. As Gardiner and Musto describe, “Human agency traditionally conceived in terms of the active author, passive text and reader must now give way to theories that dethrone both author and reader and grant autonomy to the text as an independent agent, itself presenting and shifting meanings in a multipolar, digital environment” (35). The code itself is a fixed structure, unless I manually change it, but how it is processed depends substantially on the whims of a digital system, giving subjecthood to the computer as an interpretive and creative being.

Montfort’s work also demonstrates a question in how the digital itself relates to our access to data. In particular, while one could simply print-out the program’s code and present that as a text, the “true” work can only be accessed via digital means. Whereas one can fully read and interpret a traditional book through print or through a digital reader, the beauty and purpose of “Taroko Gorge” rely on the random number generation only possible through computers, and thus it can only be fully realized through a web browser. In this case, the computer transforms the text into a document that one can study, as it “places the raw data or text into a more active relationship with the investigative process” (Gardiner and Musto, 37). Like the relationship between “a star in the sky” and “a photograph of it” (qtd. in Gardiner and Musto, 37), the digital transforms code into a work of art that markedly differs from the original while still relying on the original for its existence.

This provides great evidence for Thomas Rommel’s argument that computers have substantial use in humanistic studies. While Rommel mostly focused on digital tools supplementing human readings of traditional literary texts, Montfort’s poem supplies a more literal example of how “computers can supplement the critic’s work with information that would normally be unavailable to a human reader” (Rommel). I say literal, because Montfort’s poem could not possibly be read without a computer. In this sense, while computers allow for greater variety in how one chooses to access and process data, they also limit one’s abilities when the raw data can only be processed through purely digital means. Humanistic data, both raw and processed, can exist an entirely as an immaterial object, which causes “the very notion of material existence [to come] into sharp focus in face of the all-leveling ‘0’ and ‘1’” (Gardiner and Musto, 43), and forces one to ask how data can and should be represented.

Works Cited

Gardiner, Eileen, and Ronald G. Musto. The Digital Humanities: A Primer for Students
        and Scholars
. Cambridge University Press, 2015.

Rommel, Thomas. โ€œLiterary Studies.โ€ A Companion to Digital Humanities, Blackwell
        Publishing, digitalhumanities.org/companion/view?docId=blackwell/97814051
        03213/9781405103213.xml&chunk.id=ss1-2-8.

Digital Lab #3 – Digital Haiku

The traditional Japanese art of haiku, which as we know it is quite modified from its original structure due to European appropriation, has several inherent links to the world of the digital. Both involve one creating something meaningful within limitations (whether that entails the fixed syllable structure in the former or the specific syntax of code in the latter), and this may provide a reason for why Stephanie Barber chose this form of poetry for Status Update — her Facebook experiment turned book. Reading this text allowed me to confront the interrelationship between art and social media, and how they both generally involve one expressing personal ideas in an engaging format, as well as the limitations imposed by one’s choice of form when expressing oneself. In particular, people expect haiku to have a rigid, predictable format, leading me to wonder how an artist can express themselves while staying true to this precise form, as well as how can an artist play with expectations by slightly modifying this form while still staying recognizable as a haiku.

Mad Lib Haiku

To that end, I first looked toward a Mad Lib Haiku generator, which acts exactly as one would suspect. After entering various nouns and adjectives, I generated the following three nonsensical “haiku”:

In the red pencil
these funny mouse
A great clock

In the historical banana
these terrible book
A noteworthy flower

In the difficult time
these outstanding computer
A nonchalant poem

One important factor to notice is that none strictly follow the 5-7-5 syllable pattern most associate with the poem form (although the last is only off by one syllable, I assume that to be more of a coincidence than any indication of correct computer programming). Even more striking, however, is that all three poems conform to the same exact structure:

In the (adjective) (noun)
these (adjective) (noun)
A (adjective) (noun)

This indicates that the term “mad lib” was taken literally, and the program merely inserts one’s chosen words into a predetermined form, which, in a clear manner, makes this program even more restrictive than a normal haiku, but in another manner, and maybe not so obviously, allows for more freedom. Specifically, the program does not check to make sure the words have the correct number of syllables, allowing for a wider variety for choice of words, and the program does not care if the poems make any logical or grammatical sense (the second line in all my poems disagree with the choice of determiner (“these terrible book”)). Moreover, testing the program more shows that it does not recognize if an adjective is actually placed in the correct box, and same for the nouns, so one can generate a haiku containing random characters and words:

In the asdkf hello
these sldnkd23456 yes
A bniuiweoi 1234567890

If I were to take that preceding “haiku” and tell someone I personally wrote it, they would likely think it was a weird joke. Knowing that a computer generated it, though, justifies its meaninglessness. Specifically, people currently do not expect computers to have the capabilities to make any artistic judgments, and programming a true haiku generator would take a substantial amount of processing power and coding expertise, so they cannot know any better when somebody asks them to output a nonsensical string of text. Thus, while the structure of this generator may be more rigid than a traditional haiku, it allows for wider modes of expression, but it does not contain any preconceived notions of good art.

Social Media Haiku

Using another haiku generator on the same website, that attempts to process a string of text into poems, yields some unusual results. I took a few tweets written seven years ago (which I will not replicate here, because they are, for lack of a better term, cringy high-school tweets), and generated the following four haiku:

The
a his so
so.

From been to new
The had had have
To the new.I.

The t
lately his a
.

a's to
hear of the t!
the t's able through

Again, note that none of the haiku even get close to following the 5-7-5 syllable pattern, but this time, they at least do not seem to all fall into one rigid structure like the mad lib haiku. These poems, somewhat reminiscent of something e.e. cummings would have written, are striking in their opaqueness, as well as their unusual choice of punctuation. My tweets were fairly simple sentences, and I am curious as to how the computer morphed them into these incoherent texts. I am particularly interested with the third haiku, and how its third line is simply a period: “.”, possibly indicating complete silence after the “t.”

I asked Nelson Sing to choose one of the haiku and write a potential illustration, and he chose the second and wrote the following: “The Elysium gardens, the ‘new’ I which makes me think of some sort of new world, the been to new like a transition from a dead winter garden to a spring flower garden.” I appreciated his earnestness in creating this picture, because it made me reconsider the poem as something that could be evocative. What I initially took as an incoherent string of nonsensical text was given value and some meaning by Nelson’s perspective, and it made me reflect on how every individual can look at the same poem with a unique perspective. Similarly, in Stephanie Barber’s Status Update, there were several instances when my initial reading of the poem was rather superficial, and the accompanying illustration made me rethink the haiku’s value. For example, on July 21, 2010, Barber wrote:

seat 31 e
regales one with an array
of varied bald spots

and Lauren Bender’s illustration is simply the word “dad” (202). This simple response made me look back to the poem and consider what could remind one of one’s father. There’s the superficial possibility that the phrase “bald spots” recalls to mind the typical male-pattern baldness many fathers undergo, but I also wonder if there is some other paternal element of the poem. Regardless, this example, as well as Nelson’s illustration, demonstrates the ability of poetry, even if computer-generated, to elicit a personal emotional response.

The Imagery of Haiku

The third tool utilized was a text-to-image generator which attempts to output an image relevant to what one writes. I started by writing a haiku in the program, which led to the following result (the haiku is in the caption):

In the red garden,
An aspen tree stands behind.
It’s not always so.

I am impressed that the image generated resembles a Japanese watercolor painting of a garden (even if it is green and not red). While it may be a coincidence, I think the image complements the text. For comparison, I expanded the haiku into a longer prose passage and generated the following image:

Once in a garden brimming with the deep reds of roses, the striking yellows of daisies, and the cool indigos of orchids, an aspen tree stood behind and above all the other plants. Things, however, have changed since then, and the aspen tree no longer stands as it once did.

Again, I appreciated the image’s relevance to the passage, and I perceive what appears to be a tree falling and a barren garden. In this sense, the first image demonstrates the garden initially, while the second resembles a passage of time. While I may be reading too much into these images, they demonstrate artistic merit, even if they were not created by a human artist. Out of curiosity, I also generated an image for an English translation of a poem written by the famous Basho:

The old pond
A frog leaps in.
Splash!

In this instance, the image seems to stand in stark contrast to the imagery generated by the poem. I have a difficult time seeing anything reminiscent of a pond, a frog, or the sound of water, but I may just not be looking at it from the correct perspective. Finally, to obtain a better understanding of the image-generating program, I took a ten-page essay I wrote last semester about Walden by Henry David Thoreau, and received this image:

How the computer interpreted my essay on Walden.

I am interested in the image’s sparse color, which could relate to the more academic style of writing which foregoes detailed imagery, or it could be related to the specific language I used in my essay. I see some elements similar to wildlife and water in the image, which relate to the text, and the image leaves itself open to interpretation. The images also remind me of the potential contrast set up between Stephanie Barber’s poems and Lauren Bender’s illustrations, where the latter can diverge from my own expectations set up by the former. For example, on February 20, 2010, Barber’s poem reads:

that silver of moon
is a thrushes' warbling song
all silvery highs

while Bender’s illustration reads “my new alarm clock or a night-bird but we know better” (51). Personally, this poem brought to mind images of nature and a forested environment at night, while Bender appears to focus more on the song and relates it to an alarm clock. The divergence in interpretation indicates the social nature of poetry, and how more value can be gained by individuals sharing their perspectives. Moreover, as this tool indicates, computers themselves can enter into the discussion, even if their images are nearly indecipherable. Regardless of any deeper meaning, however, this experimental tool showed me the variety of imagery that can be generated by computer programs. In effect, computers already can demonstrate interpretive powers that allow humans to reflect on their own experiences.

Relevance to Status Update

Ultimately, the tools utilized in this lab have demonstrated the potential relationship that can exist between poetry and computer software. Whether the poems are being created by the computer itself, based on human input, as in the first two tools, or the computer is used as a tool to examine and express human-created content, as in the third tool and Barber’s work, a relationship between human user and computer system develops, where each allows the other to express themselves more fully. I am beginning to understand N. Katherine Hayles’ concept of “intermediation” as a framework for understanding the ways in which humans and machines form a symbiotic bond in the pursuit of expressing diverse perspectives. Moreover, Barber’s haiku, and Bender’s illustrations, showcase not only the interpretive dialogue that art inspires, but the ability of computer software to facilitate that dialogue through social media tools. While comments on websites like Facebook, Twitter, and YouTube have an unfortunate reputation for insipid or hurtful, they have the potential to express complex emotional beliefs that thoughtfully respond to the content posted.

Digital Lab #2 – Initial Readings about the Digital Humanities

After having read several articles providing an overview of the Digital Humanities and their histories, philosophical values, and motivations, I have come to at least a preliminary understanding of what they are and how they interact with my traditional notions of the Humanities. Many texts have emphasized the importance of using digital programs as a means of bridging social gaps, allowing individuals to share their work with a wider variety of readers and making diverse perspectives accessible. Most would contend that this is a valiant effort, and I would agree wholeheartedly, but I also believe that more can be said about how such communication can be effectuated.

For example, Lisa Spiro, in the article โ€œโ€˜This is Why We Fightโ€™: Defining the Values of the Digital Humanities,โ€ puts forth a set of guidelines, or values, that she believes should provide a basis for all DH work. The fact that four of these values (Openness, Collaboration, Collegiality/Connectedness, and Diversity) directly relate to building a community, while the fifth (Experimentation) also contributes, indicates Spiro strongly considers the importance of communication between people within DH. She argues that โ€œ[h]ow the digital humanities community operates โ€“ transparently, collaboratively, through online networks โ€“ distinguishes itโ€ (Spiro), implying that this type of community-building is particular to DH, which provides an incentive for the particular values she chooses. Moreover, she claims that โ€œarticulating a set of values for a community should be done by the communityโ€ (Sprio), which seems like an excellent method of incorporating communal discussion into the foundations of the academic field, and preventing DH from becoming limited by institutional bureaucracy, like much of traditional academic work. While such a system risks endless argument, resulting in many headaches and countless hours wasted to minute details, Spiro (optimistically) argues that โ€œif the process of developing values is handled fairly and openly, conflicts can be defused and healthy discussion can move the community forwardโ€ (Spiro). How to ensure fairness and openness remains an open question, however.

When it comes to the actual values Spiro chooses to discuss, they all appear as worthwhile to develop and integral to forming a strong DH community, even if I have some small disagreements with her explanations. For example, regarding Openness, Spiro suggests that โ€œ[r]ather than cheapening knowledge by making it free, embracing openness recognizes the importance of the humanities to societyโ€ (Spiro), and I agree with this notion as an ideal. However, given the infamous potential for the internet to quickly spread misinformation, it is apparent that some level of moderation is required, which would, unfortunately, limit oneโ€™s ability to openly access and produce academic content.

Regarding Collegiality/Connectedness and Collaboration (which all seem quite similar), Spiro mentions the existence of โ€œthe need for people with a range of skills to contribute to digital scholarshipโ€ (Spiro), because the interdisciplinary nature of DH requires people with humanities backgrounds working with people from the computer sciences. One element left out of Spiroโ€™s discussion, however, is that the level of cooperation involved does require collaborators to have a decent understanding of how the work of others operates (humanists should understand the foundations of programming and computer systems, while computer scientists should be familiar with some history and literary theory). Two academic groups not only working together but generally understanding the otherโ€™s work, helps facilitate discussion and progresses research. In effect, interdisciplinarity should not just exist within the academic field as a whole, but within each person.

Finally, Spiroโ€™s discussion of Diversity seems brief, and rather ambiguous, as it does not incorporate any concrete plans for incorporating genuine diversity into the program. Specifically, Spiro discusses how several DH organizations, such as THATCamp SoCal and the Alliance of Digital Humanities Organizations, include diversity statements in their organizational materials, showing that โ€œthe community works toward diversity as a goalโ€ (Spiro). However, the article makes no mention of how such practices are more than mere statements, which just enforces the notion that โ€œthe digital humanities community pays lip service to diversity but has not engaged with it on a deeper levelโ€ (Spiro), rather than contradicts it. As a mathematics major, I am intimately familiar with an academic discipline which sorely lacks diversity (even now, most of my math classes are at least seventy-five percent male), but as a consequence, there exist organizations which strive for improving diversity within the field, such as the Association for Women in Mathematics (AWM), as well as several research programs. While some of these efforts have drawn controversy (look here for an article and discussion), there are at least practices being put in place, which people from DH could look toward for inspiration.

Ultimately, I think Rafael Alvarado sums up this discussion best when he says that the Digital Humanities are a โ€œsocial category, not an ontological oneโ€ (Alvarado), meaning they are defined by the community itself. Attempting to develop a singular definition for the DH would only prove exclusionary, and would counteract the fieldโ€™s devotion to experimentation and novel perspectives, so it requires a multiplicity of definitions that allow for these diverse perspectives. In other words, as Amanda French says, โ€œDigital Humanities is the thing practiced by people who self-identify as Digital Humanistsโ€ (โ€œDay of DHโ€), and it is a field which functions best when it allows for as many forms of research and development as its digital tools can provide.

Works Cited:

Alvarado, Rafael C. โ€œThe Digital Humanities Situation.โ€ Debates in the Digital
โ€ƒHumanities
, Manifold Scholarship, dhdebates.gc.cuny.edu/read/untitled-
โ€ƒ88c11800-9446-469b-a3be-3fdb36bfbd1e/section/c513af64-8f99-4e02-9869-
โ€ƒbabc1cecc451.

โ€œDay of DH: Defining the Digital Humanities.โ€ Debates in the Digital Humanities,
โ€ƒManifold Scholarship, dhdebates.gc.cuny.edu/read/untitled-88c11800-9446-
โ€ƒ469b-a3be-3fdb36bfbd1e/section/550ab4e6-ca58-4840-acba-
โ€ƒea555be32601#p1b5.

Spiro, Lisa. โ€œโ€˜This Is Why We Fightโ€™: Defining the Values of the Digital Humanities.”
โ€ƒDebates in the Digital Humanities, Manifold Scholarship, dhdebates.gc.cuny.edu/
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โ€ƒc688-43ab-8b12-0f6746095335.

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