Lab Session: Digital Humanities

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This lab session has been assigned by Dr. Dilip Barad sir as a part of our learning process, with the objective of familiarizing us with various digital tools that can enhance our understanding and academic skills Teacher blog

                            

                     Digital Humanities


Take a test - Was this poem written by a human or a computer? Click here

In this activity, we were required to choose whether a given poem was written by a computer or a human. After making our selections, we received a score based on the accuracy of our answers, which helped us reflect on our ability to distinguish between human creativity and machine-generated writing.

Was this poem written by a human or a computer?
 
                        


Learning outcomes 

Analyzing a poem's authorship sharpens our critical literary skills (recognizing emotional depth, metaphor, and voice) and provides practical insight into the capabilities and limits of generative AI by forcing you to define what constitutes genuine human creativity.

Sometimes it's difficult to identify that the poem was written by computer or human 


                        CLic Activity 


13. The fireplace pose – texts and cultural context Click here

This activity aims to make connections between textual patterns in the novels andsocial or cultural behavious and conventions in the realworld. As most texts in CLiCwere written in the 19th century, we focus on the cultural context of that period.


Activity 13.1 The social importance of the fire-place

1. Search for fire in DNov (Dickens’s Novels) in “All text”. This should give you over1700 hits – too many to analyse in detail so that it’s best to use theKWICGrouper for narrowing down the search.





Learning Outcome 

By searching for the word fire in Dickens’s novels using CLiC, learners understand how frequently and in what contexts it appears. Using the KWICGrouper helps narrow down patterns, showing how the fireplace functioned socially and culturally in the 19th century. This develops skills in digital literary analysis and links textual patterns to real-world social meanings.


2. Use the KWICGrouper and left-right sorting to search through theconcordance. First set the “Search in span” from L5 to L1 by dragging theslider. Next “Search for types” by typing in back. Hit Return.






Learning Outcome 

By using the KWICGrouper with left-right sorting and focusing on the span L5–L1, learners identify how the word back frequently appears with fire, highlighting the recurring “fireplace pose.” This activity teaches how digital tools uncover textual patterns, showing links between language and cultural behavior. Students gain skills in refining searches, interpreting collocations, and understanding how Dickens’s novels reflect 19th-century social norms and gender roles.



3. You should see a highlighted set of concordance lines showing phrases suchas back to the fire, like the one below.









Learning Outcome 

By observing highlighted concordance lines such as back to the fire, learners recognize a recurring textual pattern in Dickens’s novels. This reveals how certain phrases reflect social customs like the “fireplace pose.” The activity helps students connect literary language with cultural practices, strengthening their ability to analyze recurring expressions and understand how fiction mirrors 19th-century social roles and behaviors.



Activity 13.2 The fire-place pose in 19th century literature


4. Open another browser tab and run the concordance search for fire on theother 19th century novels.



Learning Outcome 

By running a concordance search for fire in other 19th-century novels, learners can compare Dickens’s usage with that of different authors. This develops comparative analytical skills and highlights whether the “fireplace pose” is unique to Dickens or a wider literary convention. Students learn how digital tools reveal similarities and differences across texts, deepening their understanding of how literature reflects cultural and social practices of the 19th century.


5. Use the KWICGrouper again: are your observations on the fireplace posepatterns in the other 19th century novels similar to those in Dickens?




Learning Outcome:

By using the KWICGrouper to analyze the fireplace pose patterns in Dickens and comparing them with other 19th-century novels, students develop skills in digital text analysis and comparative literary study. They learn how to identify recurring motifs across texts, recognize differences in thematic or symbolic use, and critically evaluate how authors employ common cultural images like the fireplace pose. This enhances their ability to connect computational tools with close reading for deeper literary interpretation

                      Voyant - activity

Voyant Tools is an open-source, web-based application for performing text analysis. It supports scholarly reading and interpretation of texts or corpus, particularly by scholars in the digital humanities, but also by students and the general public. It can be used to analyze online texts or ones uploaded by users.[1] Voyant has a large, international user base: in October 2016 alone, Voyant's main server had 81,686 page views originating from 156 countries, invoking the tool 1,173,252 times Click here


My Experience of Voyant Tool





  1. Identify key themes and recurring vocabulary in a text or corpus through visual prominence of frequently used words.

  2. Interpret word frequency distribution — understanding how word size represents frequency and how it reflects the focus or tone of the text.

  3. Develop initial hypotheses about the text’s central ideas, motifs, and stylistic features based on dominant words.

  4. Compare and contrast multiple texts to observe differences in vocabulary emphasis or thematic focus.

  5. Use visual textual analysis as a starting point for deeper critical or quantitative literary interpretation.






📘 Learning Outcome 

  1. Identify and analyze word frequency patterns across the text or corpus.

  2. Understand the relative importance of specific terms by examining their frequency and distribution.

  3. Interpret how certain words contribute to the overall meaning, theme, or tone of the text.

  4. Use quantitative data (word counts and trends) to support qualitative literary analysis.

  5. Compare occurrences of selected terms across different parts of a text or between multiple texts.

  6. Develop digital literacy skills by integrating textual statistics with critical reading and interpretation.






Learning Outcome 

  1. Visualize the distribution of words throughout a text using bubble sizes to represent word frequency in different segments.

  2. Identify patterns of repetition and emphasis — noticing where certain words appear more frequently or are absent.

  3. Understand how themes or motifs develop and shift across the structure of the text.

  4. Compare multiple terms simultaneously to explore relationships or contrasts between recurring ideas.

  5. Interpret visual data to support textual analysis, blending quantitative and qualitative approaches.

  6. Develop skills in digital text visualization, recognizing how data representation can reveal underlying narrative or rhetorical structures.





 Learning Outcome 

By using the Correlations tool in Voyant, learners will be able to identify and analyze relationships between words that frequently occur together within a text or corpus. This visualization helps students understand how certain terms are statistically connected, revealing deeper thematic or conceptual links in the text. Through examining these co-occurrence patterns, learners can interpret how ideas, emotions, or motifs interact and reinforce each other throughout the narrative. The tool also encourages the use of quantitative evidence to support qualitative literary interpretations, fostering a balanced analytical approach. Overall, learners develop digital research skills and gain insights into how linguistic relationships contribute to the structure and meaning of literary works.



 Learning Outcome 

By using the Loom tool in Voyant, learners will be able to explore how multiple texts or segments of a corpus relate to each other through shared or unique vocabulary patterns. The tool visually “weaves” together occurrences of words across texts, helping users recognize thematic connections, lexical similarities, and stylistic variations. Through this visual mapping, learners can compare and contrast texts, trace the distribution of key terms, and observe how specific words contribute to the overall unity or diversity within a collection. The Loom tool encourages students to think critically about intertextual relationships and language usage, integrating digital visualization with traditional literary analysis. Ultimately, it enhances both data interpretation and critical reading skills, allowing for a deeper understanding of textual relationships within a corpus.




 Learning Outcome 

By using the StreamGraph tool in Voyant, learners will be able to visualize how the frequency of selected words or themes changes across different sections of a text or a collection of texts. The flowing, layered design of the StreamGraph helps students trace the rise and fall of specific terms over time, revealing patterns of emphasis, thematic shifts, and narrative progression. This tool enables users to identify when and where particular ideas or motifs become dominant, thereby connecting quantitative trends with qualitative literary insights. Through analyzing these visual representations, learners gain the ability to interpret temporal dynamics in language use and understand how authors construct meaning through repetition and variation. Ultimately, the StreamGraph enhances skills in digital textual analysis, critical thinking, and interpretation, linking data visualization to deeper literary understanding.



 Learning Outcome 

By using the Trends tool in Voyant, learners will be able to analyze how the frequency of specific words or terms fluctuates across different parts of a text or corpus. This visualization presents a line graph showing the rise and fall of word usage, helping users detect thematic developments, stylistic variations, or changes in focus throughout the text. Learners will understand how quantitative patterns can highlight key moments of emphasis or transition within a narrative. The tool also supports comparative analysis, allowing users to examine how multiple terms relate to each other across the same textual timeline. Through interpreting these visual trends, students develop skills in digital reading, pattern recognition, and data-supported literary interpretation, deepening their ability to connect textual form with meaning and thematic progression




 Learning Outcome 

By using the Topics tool in Voyant, learners will be able to identify and analyze the major themes or topics present within a text or corpus. The tool groups words that frequently appear together, helping students uncover conceptual clusters and understand how different ideas are interconnected. Learners can explore how topics are distributed across the text, observe patterns of emphasis, and interpret shifts in thematic focus over time. This facilitates a deeper understanding of the text’s semantic structure, enabling students to connect recurring words and phrases to broader literary or conceptual themes. Through this analysis, learners enhance their critical reading skills, develop data-driven insights, and integrate digital textual analysis into traditional literary interpretation.



 Learning Outcome 

By using the Phrases tool in Voyant, learners will be able to identify recurring multi-word expressions, collocations, and significant sequences of words within a text or corpus. This tool highlights patterns in word combinations, helping students understand how ideas, motifs, or concepts are expressed through language structures rather than single words alone. Learners can analyze the context and frequency of phrases, observe stylistic or rhetorical patterns, and trace thematic development across the text. Using Phrases, students enhance their ability to conduct detailed textual analysis, connecting lexical patterns to meaning, tone, and authorial style. The tool also fosters digital literacy and critical thinking, allowing learners to integrate quantitative data on phrase usage with qualitative literary interpretation.


Thak You































































































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