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Computational Analysis of Differences in Indian and American Poetry

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Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 28))

Abstract

Poetry is a verbal art which is motivating the human race from centuries. Indian authors’ English poetry has its own signature in the world poetry. Though it has great significance when compared with Western poetry, very little work has been done in the areas of authorship affinities, classification, style similarity of poets, and comparative studies. In this work, we investigated style and semantic differences between Indian and Western poetry and also compared the poetry in terms of variation in the usage of words and stylistic features such as orthographic, syntactic, and phonetic features. To capture style and variation differences, we considered 84 style features that cover structural, syntactical, sound devices of poetry and computed TF-IDF values using a bag of word method; then, we computed cumulative TF-IDF value of each word across all poems and arranged the values in decreasing order of their cumulative TF-IDF value. Later, we applied ranks and used PCA, LSA, and Spearman correlation to find variance in usage of words by Indian authors’ English poetry and Western poetry and style differences. We observed 40% semantic difference and 30% style difference between Indian authors’ English poetry and Western poetry. Our comparative analysis says that the features that work well with one country poetry may not be necessary to perform well with other country poetry.

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References

  1. Kao J, Jurafsky D (2012) A computational analysis of style, affect, and imagery in contemporary poetry, pp 8–17

    Google Scholar 

  2. Kaplan DM, Blei DM (2007) Seventh IEEE international conference on data mining a computational approach to style in American Poetry, pp 553–558

    Google Scholar 

  3. Lee JSY (2008) Semantic parallelism in classical Chinese poems, pp 527–530

    Google Scholar 

  4. C. Using Markov, Authorship Attribution in Arabic Poetry, 2015

    Google Scholar 

  5. Rana S (2012) A study of Indian english poetry. 2(10):1–5

    Google Scholar 

  6. Kilgarriff A, Rose T, Kilgarriff A, Rose T (1998) Measures for corpus similarity and homogeneity

    Google Scholar 

  7. Lamb C, Brown DG, Clarke CLA (2016) Evaluating digital poetry: insights from the CAT. In: Proceedings of the seventh international conference on computational creativity, pp 65–72, June 2016

    Google Scholar 

  8. Lee J (2016) Word clustering for parallelism in classical Chinese poems P (Wl) P (W2) Suppose N is the total number of tokens in the corpus, pp 49–52

    Google Scholar 

  9. Kikuchi S, Kato K, Saito J, Okura S (2016) Quality estimation for Japanese Haiku poems using neural network

    Google Scholar 

  10. Pavan GK (2014) English poetry and poets of pre-independent India. 2(2):57–62

    Google Scholar 

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Acknowledgements

We profusely express our sincere thanks to Dr. C. Raghavendra Rao, Professor, University of Hyderabad, Central University, for his timely guidance in completing this work.

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Correspondence to K. Praveenkumar .

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Praveenkumar, K., Maruthi Padmaja, T. (2019). Computational Analysis of Differences in Indian and American Poetry. In: Chaki, N., Devarakonda, N., Sarkar, A., Debnath, N. (eds) Proceedings of International Conference on Computational Intelligence and Data Engineering. Lecture Notes on Data Engineering and Communications Technologies, vol 28. Springer, Singapore. https://doi.org/10.1007/978-981-13-6459-4_13

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