Extraction of Key Motifs as a Preview from 2017 Nobel Prize Winning Novel, ‘Never Let Me Go’ An Interactive Word Cloud Study

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Zafar Ullah
Muhammad Uzair
Arshad Mahmood


Word clouds manifest interactive visuals along with their statistical data. Thus knowledge discovery and aesthetic data visualization interlink to produce interactive word cloud which is an interesting, textual, statistical and visual data. This study aims to generate interactive word cloud—Cirrus—on the basis of statistical data to preview text of the novel for readers. So cirrus tool is selected from Voyant open access tools to produce interactive statistical word cloud. Then the generated word cloud and statistical data are analyzed with mixed method and its analysis draws insight from Rakesh Aggrawal’s Knowledge Discovery Theory which seeks innovative and interesting knowledge patterns. This thematic word cloud verifies already known themes and discovers innovative interesting themes. Current study reveals that all mentioned key themes can be easily extracted from a voluminous novel with the help of Cirrus tool. Key motifs have been presented in the word cloud for the readers. On the other hand, unwritten themes can’t be extracted through machine learning tools, rather it is the task of human cognition. Primarily, this novel based study reveals names of chief characters, for instance “Tommy (496),” “Ruth (455)” and “I (Kathy) (355).” Furthermore, motifs of nostalgic memories with word “remember (143),” “thought (126)” about “Hailsham (203),” “carer (74),” “sex (80),” sex “lectures (8)” have been discovered as a preview. Previewing technique prepares reader’s mind and gives an epigrammatic digital view of the text. The visual themes as knowledgeable word cloud leave an indelible mark on the slate of memory.


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Zafar Ullah, Muhammad Uzair, & Arshad Mahmood. (2021). Extraction of Key Motifs as a Preview from 2017 Nobel Prize Winning Novel, ‘Never Let Me Go’: An Interactive Word Cloud Study. Journal of Research in Social Sciences, 7(2), 83–98. https://doi.org/10.52015/jrss.7i2.80