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Knowledge discovery from the texts of Nobel Prize winners in literature: sentiment analysis and Latent Dirichlet Allocation

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Abstract

Today, The Nobel Prize for Literature is one of the most recognized and prestigious awards. Examining the texts of the authors who have received this award and revealing the factors that play an important role in the awarding of this award is very important for the author, the reader and interested parties. In this direction, within the framework of the study, firstly identified the most popular works of the authors who received the Nobel Prize in Literature between 1980 and 2021 and created a data set—corpus. Dictionary-based sentiment analysis, a method for classifying sentiments, and Latent Dirichlet Allocation (LDA), a very popular approach in topic modeling, were applied to this dataset. As a result, the findings obtained from both sentiment and LDA analyzes were evaluated together and it was found that the themes with the highest distribution in the popular texts of Nobel Prize winners are also those with the positive emotional pole and “trust” weighted sentiment. This study is an exemplary resource in that it contributes to the understanding of the structure and emotional character of the related works of Nobel Prize-winning authors and enables readers and authors to quickly and functionally examine large groups of texts in terms of theme and content.

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Data Availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Authors and Affiliations

  1. Educational Sciences, Educational Measurement and Evaluation, Akdeniz University, Antalya, Turkey

    Bilal Barış Alkan & Leyla Karakuş

  2. Department of Turkish Education, Akdeniz University, Antalya, Turkey

    Bekir Direkci

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  1. Bilal Barış Alkan
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BBA and BD presented the idea for the corresponding study. BBA designed the general framework of the study and supervised each phase of the study. LK performed the data collection and analysis phases. All authors contributed to the final version of the study.

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Correspondence to Bilal Barış Alkan.

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Alkan, B.B., Karakuş, L. & Direkci, B. Knowledge discovery from the texts of Nobel Prize winners in literature: sentiment analysis and Latent Dirichlet Allocation. Scientometrics 128, 5311–5334 (2023). https://doi.org/10.1007/s11192-023-04783-6

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