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Building Language Resources for Emotion Analysis in Bengali

Building Language Resources for Emotion Analysis in Bengali

Dipankar Das, Sivaji Bandyopadhyay
Copyright: © 2013 |Pages: 23
ISBN13: 9781466639706|ISBN10: 1466639709|EISBN13: 9781466639713
DOI: 10.4018/978-1-4666-3970-6.ch016
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MLA

Das, Dipankar, and Sivaji Bandyopadhyay. "Building Language Resources for Emotion Analysis in Bengali." Technical Challenges and Design Issues in Bangla Language Processing, edited by M. A. Karim, et al., IGI Global, 2013, pp. 346-368. https://doi.org/10.4018/978-1-4666-3970-6.ch016

APA

Das, D. & Bandyopadhyay, S. (2013). Building Language Resources for Emotion Analysis in Bengali. In M. Karim, M. Kaykobad, & M. Murshed (Eds.), Technical Challenges and Design Issues in Bangla Language Processing (pp. 346-368). IGI Global. https://doi.org/10.4018/978-1-4666-3970-6.ch016

Chicago

Das, Dipankar, and Sivaji Bandyopadhyay. "Building Language Resources for Emotion Analysis in Bengali." In Technical Challenges and Design Issues in Bangla Language Processing, edited by M. A. Karim, M. Kaykobad, and M. Murshed, 346-368. Hershey, PA: IGI Global, 2013. https://doi.org/10.4018/978-1-4666-3970-6.ch016

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Abstract

Rapidly growing Web users from multilingual communities focus the attention to improve the multilingual search engines on the basis of sentiment or emotion and provide the opportunities to build resources for languages other than English. At present, there is no such corpus or lexicon available for emotion analysis in Indian languages, especially for Bengali, the sixth most popular language in the world, second in India, and the national language of Bangladesh. Thus, in the chapter, the authors describe the preparation of an emotion corpus and lexicon in Bengali. The emotion lexicon, termed Bengali WordNet Affect has been developed from its equivalent version in English by traversing the steps of expansion, translation, and sense disambiguation. In addition to emotion lexicon, a Bengali blog corpus for emotion analysis has also been developed by manual annotators with detailed linguistic expressions such as emotional phrases, intensities, emotion holder, emotion topic and target span, and sentential emotion tags.

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