Monday, 3 August 2026

Lab Session1: Digital Humanities: CLiC - etc

From Poetry to Pixels: A Digital Humanities Approach to Literary Expression and Analysis

This blog is written as part of the Lab Activity on Digital Humanities assigned by Prof. Dr. Dilip Barad, Head of the Department of English, Maharaja Krishnakumarsinhji Bhavnagar University. The purpose of this activity was to explore how digital tools can enrich literary studies by combining computational methods with traditional close reading. 

Introduction : 


This blog is divided into three parts:

Part I – What If Machines Write Poems?
  • An exploration of AI-generated poetry inspired by Prof. Dr. Dilip Barad's blog, reflecting on computational creativity, authorship, and the relationship between artificial intelligence and literature.
Part II – Exploring CLiC: A Corpus Stylistic Approach to Literary Analysis
  • A study of the CLiC (Corpus Linguistics in Context) tool through the "Fireplace Pose – Texts and Cultural Context" activity, highlighting how corpus linguistics and Digital Humanities support literary interpretation.
Part III – Exploring The Importance of Being Earnest Through Voyant Tools
  • A hands-on experience using Voyant Tools to analyse Oscar Wilde's The Importance of Being Earnest, focusing on word frequency, character prominence, and textual visualization to understand the play from a Digital Humanities perspective.

Part I: What If Machines Write Poems? Rethinking Creativity in the Age of Artificial Intelligence


- Inspired by Prof. Dr. Dilip Barad's blog, What if Machines Write Poems? (2017)

Introduction:


Every year, World Poetry Day celebrates the beauty of human imagination, emotions, and creativity. Traditionally, poetry has been regarded as one of the purest expressions of the human soul a form of art that cannot exist without lived experience, emotions, memories, and imagination. Yet, in the twenty-first century, this long-held belief is being challenged by a surprising question:

Can machines write poetry?


Even more unsettling is another question:

What if machines begin writing poems that readers appreciate as much as, or even more than, poems written by humans?

While these questions may have sounded absurd a few decades ago, they have become central to discussions in Digital Humanities, Artificial Intelligence, computational creativity, and literary studies. Inspired by Prof. Dr. Dilip Barad's thought-provoking blog What if Machines Write Poems?, I explored various AI poetry generators and reflected on the changing relationship between technology and literature. This activity not only challenged my assumptions about creativity but also encouraged me to rethink the future of authorship itself.

Poetry Beyond the Human Mind

For centuries, literature has been considered uniquely human. Poets such as William Wordsworth believed that poetry arises from "emotion recollected in tranquillity," while Romantic writers viewed imagination as a divine human faculty. Consequently, the idea of a computer composing poetry once seemed impossible.

Today, however, artificial intelligence has blurred these distinctions. Computers can analyse millions of poems, identify recurring linguistic patterns, imitate poetic styles, generate metaphors, and even create verses that appear emotionally meaningful.

This development raises philosophical questions rather than merely technological ones.
  • If readers are emotionally moved by a poem, does it matter whether it was written by a human or a machine?
  • Can creativity exist without consciousness?
  • Can algorithms imitate imagination?

The Inspiration Behind This Activity

While reading Prof. Dr. Dilip Barad's blog, I was struck by one simple but profound observation:

  • "What if human poems sound mechanical and machine's, humane?"

This sentence completely reverses our expectations.  Instead of asking whether computers can become creative, it asks whether humans may gradually become repetitive while machines become increasingly expressive.

The blog encourages readers not simply to admire technological advancement but to question traditional definitions of creativity, originality, and authorship.

Exploring AI Poetry Generators

As suggested in the blog, I experimented with different poetry generation websites. One of the simplest was the Pangloss Poem Generator, where I entered the opening line of a poem and watched the computer generate an entirely new composition within seconds. Although the poem lacked deep personal experience, it surprisingly maintained rhythm, imagery, and poetic structure.

Later, I explored several other automatic poetry generators, each producing different styles depending on the prompts I entered. This experience made me realise that writing poetry is no longer limited to human imagination alone; it has become a collaborative space where algorithms also participate.


Exploring AI poetry generators during the Digital Humanities activity.

Human Creativity versus Artificial Creativity

One of the most interesting aspects of this activity was comparing machine-generated poems with human-written poetry.

Human poets write from memory, emotion, pain, joy, relationships, and lived experiences. Their poetry often reflects personal history and cultural identity. Machines, however, do not experience love, grief, loneliness, or hope.

Instead, they analyse enormous datasets of existing literature and statistically predict which words are most likely to appear together.

Yet the final result can still appear remarkably poetic. This creates an intellectual dilemma. If readers cannot distinguish between human and machine poetry, what exactly makes literature "human"? Perhaps creativity is not merely about expressing emotion but also about recognising patterns and producing meaningful language.

The Human or Machine Challenge

Another fascinating activity recommended in the blog was taking online quizzes where readers attempt to identify whether a poem was written by a human or a computer.

Initially, I felt confident that distinguishing them would be easy.

However, after reading several poems, I realised how difficult the task actually was. Some machine-generated poems contained beautiful imagery and coherent metaphors.

Meanwhile, some human poems intentionally used fragmented language and experimental structures. The boundary between human and artificial creativity seemed increasingly blurred. This experience reminded me that literary value often depends on interpretation rather than authorship alone.


Attempting the "Human or Machine?" poetry identification activity.

Generative Literature: A New Literary Movement

The poems produced through algorithms belong to a broader field known as Generative Literature.

Generative literature refers to texts created wholly or partially through computational procedures rather than conventional human writing. Instead of writing every line manually, authors design rules, algorithms, datasets, or prompts that enable computers to generate literary works.

In this sense, the author becomes both writer and programmer. The computer functions as a creative collaborator rather than merely a tool. This completely transforms traditional concepts of authorship.

Instead of asking, "Who wrote the poem?" we begin asking:
  • Who designed the algorithm?
  • Who selected the training data?
  • Who decided the prompts?
  • Who edited the generated text?
These questions demonstrate that creativity is gradually becoming collaborative rather than individual.

Digital Humanities and Computational Creativity

This activity also introduced me to an important area within Digital Humanities. Digital Humanities does not simply digitise literary texts.

Rather, it explores how digital technologies reshape reading, writing, interpretation, preservation, and literary production. AI poetry generators illustrate how computation intersects with literary creativity. Instead of replacing literature, digital tools expand the possibilities of literary expression.

Today researchers use artificial intelligence to:
  • generate poetry,
  • imitate literary styles,
  • analyse poetic patterns,
  • translate literature,
  • identify authorship,
  • and even compose novels.
Consequently, literature is no longer confined to pen and paper.

It increasingly exists within algorithms, databases, and machine learning models.

My Personal Reflection

Before beginning this activity, I strongly believed that poetry belonged exclusively to human imagination. After experimenting with AI poetry generators, my perspective changed significantly.

I realised that computers are capable of producing surprisingly meaningful poetic language. Although I still believe that machines cannot genuinely experience emotions, they can successfully imitate emotional expression through linguistic patterns.
  • This distinction is extremely important.
  • Machines do not feel.
  • They simulate feeling.
  • Yet readers may still respond emotionally to the generated text.
Therefore, literature is becoming less about the identity of the author and more about the experience of the reader. This activity also taught me that artificial intelligence should not necessarily be viewed as the enemy of creativity.

Instead, it can function as a collaborative partner that stimulates new ideas, new poetic forms, and new creative possibilities.

As a student of English Literature, this experience encouraged me to appreciate both traditional literary creativity and computational innovation.


My own experiment with AI-generated poetry and reflections.

Ethical Questions Raised by AI Poetry

Despite its fascinating possibilities, AI-generated poetry also raises several ethical concerns.

If a machine writes a poem using thousands of existing human poems as training data, who owns the final work?
  • Can AI-generated poetry receive literary awards?
  • Should readers always know whether a poem has been written by a human or generated by artificial intelligence?
  • Could AI eventually replace professional poets?
These questions remain open for debate.

Rather than providing definite answers, Digital Humanities encourages critical thinking about technology and culture.


Conclusion

The question, "What if machines write poems?", is no longer speculative. Machines already write poetry.

The more significant question today is:

  • How should humans respond to this new form of creativity?

Rather than fearing artificial intelligence, we should understand its capabilities and limitations. Human creativity remains rooted in lived experience, cultural memory, empathy, and consciousness. Artificial intelligence contributes computational power, linguistic modelling, and infinite experimentation. Together, they open exciting new possibilities for literature.

This activity transformed my understanding of poetry from being solely an emotional art form into a dynamic collaboration between humans and machines. It reminded me that the future of literature is not about replacing poets with algorithms but about exploring how technology can inspire new ways of reading, writing, and imagining the world.

Part II: Exploring CLiC: A Corpus Stylistic Approach to Literary Analysis



CLiC (Corpus Linguistics in Context) is a free web-based Digital Humanities and corpus stylistics tool developed by researchers at the University of Birmingham. It enables scholars, students, and researchers to analyze literary texts computationally while preserving their literary context. It was initially developed for the CLiC Dickens Project and has since expanded to include a wide range of English literary texts.


What is CLiC?

CLiC combines corpus linguistics and literary studies. Instead of reading a novel page by page, users can search across one or many literary texts to identify patterns in vocabulary, dialogue, narration, characterization, and style. It is especially valuable for researchers in Digital Humanities, English Literature, Stylistics, Corpus Linguistics, and Cultural Studies.

Main Features of CLiC
Concordance Search (KWIC – Key Word in Context):
  • Displays every occurrence of a word or phrase with its surrounding context.
  • Helps identify how words are used throughout a text.
Keyword Analysis:
  • Compares one text with another corpus to identify unusually frequent or distinctive words.
  • Useful for determining an author's stylistic signature.
Clusters and N-grams:
  • Finds recurring phrases such as "I don't know" or "at the same time".
  • Reveals habitual expressions and stylistic patterns.
Character and Dialogue Analysis:
  • Searches specifically within quotation marks (direct speech) or outside quotations (narration).
  • Particularly useful for studying characterization and narrative voice.
Distribution Plots:
  • Shows where words or phrases appear throughout a novel.
  • Helps identify thematic development across chapters.
Corpus Comparison:
  • Compare Dickens with Austen, Hardy, Conan Doyle, or your own uploaded texts.
  • Useful for comparative literary research.
Custom Corpora:
  • Users can upload and analyze their own texts alongside the built-in collections.
Literary Corpora Available

CLiC includes collections such as:
  • Charles Dickens' novels
  • Nineteenth-century fiction
  • Children's literature
  • Gothic fiction
  • Other classic English literary works

These corpora allow researchers to compare authors, genres, and literary periods.

Why is CLiC Important in Digital Humanities?

CLiC demonstrates how computational methods can support close reading rather than replace it. It allows researchers to:
  • Detect linguistic patterns across thousands of pages.
  • Study characterization through speech and narration.
  • Analyze themes, emotions, and narrative techniques quantitatively.
  • Combine statistical evidence with traditional literary interpretation.

This integration of computational analysis with literary criticism is a key example of Digital Humanities research.

How CLiC Can Help an M.A. English Student

Since you are working in Indian English Literature and Digital Humanities, you can use CLiC to investigate questions such as:
  • How do Indian English authors use dialogue differently from British novelists?
  • Which words dominate a particular novel or play?
  • How is gender represented through speech?
  • What lexical patterns characterize postcolonial writing?
  • How does narrative style differ between authors?
Example Research Topics Using CLiC
  • Corpus Stylistic Analysis of Salman Rushdie's Midnight's Children
  • Speech Representation in Mahesh Dattani's Plays
  • Gendered Language in Anita Desai's Fiction
  • Keywords and Identity in Indian English Novels
  • Corpus-Based Study of Postcolonial Narrative Style
Digital Humanities Approach to Characterization in Indian English Literature

In short, CLiC is a corpus analysis platform designed specifically for literary research. It bridges traditional literary criticism with computational methods, making it one of the most valuable Digital Humanities tools for scholars of English literature.

Experience and Learning Outcomes 


Working on the "Fireplace Pose – Texts and Cultural Context" activity in CLiC was an insightful experience because it demonstrated how Digital Humanities tools can reveal literary patterns that are difficult to notice through conventional close reading alone. By using the Concordance and KWICGrouper features, I explored the occurrences of the word fire in Dickens's novels and examined the recurring pattern "back to the fire." Initially, the large number of concordance lines appeared overwhelming, but the KWICGrouper enabled me to organize and filter the data efficiently, making the analysis more systematic and meaningful.

As I examined the concordance lines, I realized that the fireplace in nineteenth-century fiction functions as more than a physical object; it is also a cultural and social symbol. I observed that male characters frequently occupied the space in front of the fireplace, often standing with their backs to the fire, which suggested confidence, authority, and social prominence. This pattern became even more meaningful when I connected it with the historical explanation of Victorian gender roles discussed by Mahlberg and Korte. I understood how seemingly ordinary descriptions of posture and space can reflect broader social conventions and ideologies embedded within literary texts.

Comparing Dickens's novels with other nineteenth-century fiction further strengthened my understanding of corpus-based literary analysis. I noticed that while similar patterns appeared in other novels, Dickens employed the fireplace pose with greater consistency and narrative significance. This comparison helped me appreciate how corpus tools support both quantitative analysis and qualitative interpretation, allowing researchers to identify stylistic tendencies while still engaging in close textual reading.

This activity also enhanced my technical skills in using CLiC. I became familiar with conducting concordance searches, narrowing results through the KWICGrouper, adjusting search spans, sorting contexts, and identifying lexical patterns. More importantly, I learned that Digital Humanities methods do not replace traditional literary criticism; instead, they complement it by providing empirical evidence for critical interpretations.

Overall, this exercise changed the way I approach literary texts. I learned that repeated linguistic patterns can reveal cultural assumptions, social hierarchies, and character relationships that might otherwise remain unnoticed. The activity strengthened my appreciation of corpus stylistics and demonstrated how computational tools can deepen literary interpretation by connecting textual evidence with historical and cultural contexts. It has encouraged me to incorporate Digital Humanities methodologies into my future research in English literature.


Part III: Exploring The Importance of Being Earnest Through Voyant Tools


Introduction to Voyant Tools

Voyant Tools is a free, web-based Digital Humanities application developed by Stéfan Sinclair and Geoffrey Rockwell for text analysis and visualization. It allows users to upload literary texts and examine them through tools such as Cirrus (word cloud), Trends, Reader, Bubblelines, Summary, Loom, Contexts, and Collocates. These visualizations help identify word frequency, thematic patterns, character prominence, and vocabulary distribution. By combining computational analysis with close reading, Voyant Tools enables researchers to discover textual patterns that enrich literary interpretation.

My Understanding and Experience Using Voyant Tools

As part of my Digital Humanities learning, I explored Oscar Wilde's The Importance of Being Earnest using Voyant Tools. This activity introduced me to a new way of reading literature through computational analysis. While traditional literary criticism focuses on close reading, Voyant Tools helped me identify recurring patterns and visualise textual data, making my understanding of the play more systematic and evidence-based.


Uploading The Importance of Being Earnest into Voyant Tools.

The first feature I explored was the Cirrus Word Cloud. It immediately highlighted the most frequently occurring words in the play. Character names such as Jack, Algernon, Cecily, Gwendolen, Lady Bracknell, and Miss Prism appeared prominently, showing their importance in the narrative. Other commonly used words like importance, earnest, think, know, and dear reflected Wilde's witty and dialogue-driven style. This visualization helped me quickly understand the central focus of the play without manually counting word frequencies.



 Cirrus Word Cloud showing the most frequent words in the play.

Next, I examined the Trends graph, which displays how often a selected word appears throughout different sections of the text. I searched for Gwendolen and observed that her name appeared more frequently in the middle and later parts of the play. This helped me understand how the importance of characters changes as the story develops. Instead of relying only on memory, I could visually connect character frequency with the structure of the narrative.

The Bubblelines feature further enhanced this understanding by showing where specific words occur across the text. It allowed me to see the concentration of character appearances and how Wilde shifts attention between different characters during the play.



 Trends and Bubblelines illustrating the distribution of characters across the play.

The Summary panel provided useful statistics about the corpus, including the total number of words, vocabulary density, readability index, and average sentence length. These statistics gave me an overview of Wilde's writing style and demonstrated how computational tools can provide objective linguistic information alongside literary interpretation.

Although the Loom visualization initially appeared complex, I gradually understood that it represents the distribution of multiple terms throughout the text. It helped me recognise that different characters dominate different sections of the play, revealing narrative patterns that are difficult to observe through conventional reading alone.
 Loom visualization and Summary statistics generated by Voyant Tools.

This activity changed my understanding of literary analysis. I realised that Digital Humanities does not replace traditional close reading but complements it by providing visual and statistical evidence. Voyant Tools enabled me to identify recurring vocabulary, character prominence, and textual patterns more efficiently than manual reading alone.

Overall, this experience strengthened both my technical and analytical skills. I learned how to create a corpus, interpret word clouds, analyse frequency graphs, and connect quantitative data with qualitative literary interpretation. As an M.A. English student, I found Voyant Tools to be an effective platform for exploring literature from a Digital Humanities perspective. It has encouraged me to incorporate computational methods into my future literary research while continuing to value close reading as the foundation of literary criticism.

Works Cited

  • Mahlberg, Michaela, et al. CLiC: Corpus Linguistics in Context. University of Birmingham, clic.bham.ac.uk. Accessed 3 Aug. 2026.
  • Mahlberg, Michaela, and Barbara Korte. "The Fireplace in Dickens and Nineteenth-Century Fiction: A Corpus Stylistic Approach." Language and Literature, vol. 26, no. 2, 2017, pp. 135-155.
  • Sinclair, Stéfan, and Geoffrey Rockwell. Voyant Tools. voyant-tools.org. Accessed 3 Aug. 2026.

Thank you!!

at

No comments:

Post a Comment

Subscribe to: Post Comments (Atom)

CS - Hamlet

  The Little People of Power Marginalization, Expendability, and Existential Crisis in Shakespeare's Hamlet and Tom Stoppard's Rosen...