Lab Activity: Digital Humanities

As part of our Digital Humanities, we were divided into groups by Professor Dilip P. Barad. Our group focused on The Creation of Fictional Characters, and it consisted of three members: Bhumi Mahida, Devangini Vyas, and myself. To explore this theme, we were assigned five different activities that helped us understand how literature, technology, and digital tools intersect in the study of fictional characters. 

These activities were assigned by Professor Dilip P. Barad under the Digital Humanities course to enhance our understanding. To get more information, [click here].

1. Debate on Machines and Poetry 

Understanding how people once debated whether machines could write poems.

"Can a computer write poetry? | Oscar Schwartz," is a philosophical TED Talk that uses poetry-writing algorithms to explore the nature of human creativity and intelligence.

The key takeaway was that computer-generated poems can sometimes trick humans into believing they are authentic. In fact, they fooled 65% of readers, crossing the threshold set by Alan Turing. What I learned here is that the real question isn’t about whether machines can write poetry but about how we define humanity and creativity itself.

2.Human or Computer?

Taking a test to identify whether a poem was written by a human or a computer.

Here, I had to take a test where I guessed whether a poem was written by a computer or a human. At first, it felt simple, but soon I realized it was tricky—sometimes the computer’s poem felt more mechanical, while at other times it was surprisingly human-like.

(here is my test from Given Task )

Was this poem written by a human or a computer? (Click Here To Appear in Test )

3.CLiC - Dickens Project - Exploring the CLiC project on Dickens’ works.

We were divided into groups by Professor Dilip Barad, and in our group we were dealing with The Creation of Fictional Characters. Our group had three members: Bhumi Mahida, Devangini Vyas, and myself. We worked on five activities, and here are the results.

Activity 1  Picking out the character

Patterns in Verbs and Position

1. Lack of agency –

   • Mr. Dick is often placed in positions where he is not the doer but the one being referred to.

   • Example: “give my compliments to Mr. Dick,” or “said Mr. Dick, feebly scratching his head.”

2. Recipient of action or comment –

   • Frequently appears after verbs spoken by others (e.g., “said my aunt, ‘you have heard me mention David Copperfield,’ Mr. Dick…”).

   • His role is often passive, being spoken to, sent for, or looked at.

3. Weak agentive verbs –

   • When he does act, the verbs are minor or hesitant: “leaning,” “linger,” “scratching his head.”

   • These suggest uncertainty, weakness, or lack of decisive action.

4. Cognitive or perceptual verbs –

   • His strongest verbs show thinking or observing: “he thought,” “anxiously watched,” “considering, and looking vacantly.”

   • This emphasizes his role as someone who perceives and reflects rather than materially influences events.

Oddities

• Often defined through others’ perception – his aunt or David frequently “frame” him by commenting on him.

• Repetitive phrasing – His name is often repeated in full (Mr. Dick) rather than using pronouns, which might add to his comic or peculiar portrayal.

• Contradiction between presence and action – He appears frequently in conversations, yet contributes little that moves the plot forward.

Activity 2 Picking out the characterisation

What stands out is that many of these lines reduce his presence to formulaic reporting clauses such as “said Mr. Dick” or “Mr. Dick looked”. These repeated reporting structures limit the variety of his portrayal and make him seem less dynamic than other characters. When description does expand, it still tends to highlight his passivity or eccentricity: he is shown “scratching his head,” “looking vacantly,” or “laying down his pen.” These are minor, hesitant actions rather than decisive or plot-driving ones.

Taken together, these examples reinforce the impression that Mr. Dick’s role in the novel is more about being observed, spoken about, or gently ridiculed than about performing significant actions. His presence is marked by repetition, simple reporting clauses, and weak verbs, all of which underline his reflective, passive, and somewhat comic characterisation.

Activity 8.3 isolated reporting clauses like said Mr. Dick, showing how much of his presence is tied to his spoken words. 

Activity 8.4 examined “long suspensions,” where the narrator interrupts his speech with descriptions of body language and emotion, which emphasized his mental states and expressions. 

Finally, Activity 8.5 filtered for words connected to body parts like head, face, or eyes, confirming how central his facial expressions are to his portrayal. Altogether, these activities demonstrated how digital tools can uncover patterns in characterization that might otherwise go unnoticed.

4. Voyant Tools

Voyant Tools is a widely used digital humanities tool designed to make text analysis more accessible. It is open-source, web-based, and does not require technical expertise, making it useful for scholars, students, and even the general public who want to explore texts in new ways.

Voyant allows users to upload or link to a text (or a corpus of multiple texts) and then performs lightweight text analytics such as:

• Word frequency lists (showing how often words occur)

• Frequency distribution plots (visualizing word trends across the text)

• KWIC (Key Word in Context) displays (showing how words are used in their textual surroundings)

• Word clouds (visual depictions of the most frequent words)

• For instance I have taken Shakespeare's Hamlet

Word Tree

The Voyant WordTree tool is an interactive form of the keyword-in-context (KWIC) technique. It's designed to show how a specific word is used in different phrases (its context) throughout the text.  

TermsBerry 

The TermsBerry visualization in Voyant Tools is designed to be a blend of a word cloud (Cirrus) and a collocates graph 

The Trends

The Trends visualization in Voyant Tools is a line graph that shows the distribution of word frequencies across a text or collection of texts.

My Experience and Learning Outcomes

Working on these activities was a unique experience. Of course, it took time to understand each tool and apply it properly, but the effort was worthwhile. I learned some great and important things:

• How digital tools like CLiC and Voyant can make us rethink literature.
• How machines and humans both contribute to creativity in surprising ways.
• How characterisation and word patterns reveal much more than what we notice at first glance.

This lab activity not only improved my digital skills but also deepened my appreciation for literature in the digital age. It was challenging at times, but overall a good experience that allowed me to learn many things—and I believe I can learn much more as I continue exploring Digital Humanities.