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A Classifier Based Approach to Emotion Lexicon Construction

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Natural Language Processing and Information Systems (NLDB 2012)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7337))

Abstract

The present task of developing an emotion lexicon shows the differences from the existing solutions by considering the definite as well as fuzzy connotation of the emotional words into account. A weighted lexical network has been developed on the freely available ISEAR dataset using the co-occurrence threshold. Two methods were applied on the network, a supervised method that predicts the definite emotion orientations of the words which received close or equal membership values from the first method, Fuzzy c-means clustering. The kernel functions of the two methods were modified based on the similarity based edge weights, Point wise Mutual Information (PMI) and universal Law of Gravitation (LGr) between the word pairs. The system achieves the accuracy of 85.92% in identifying emotion orientations of the words from the WordNet Affect based lexical network.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Jadavpur University, 188, Raja S.C. Mullick Road, Kolkata, 700 032, India

    Dipankar Das, Soujanya Poria & Sivaji Bandyopadhyay

Authors
  1. Dipankar Das
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  2. Soujanya Poria
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  3. Sivaji Bandyopadhyay
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Editor information

Editors and Affiliations

  1. Information Science Department, University of Groningen, Oude Kijk in ’t Jatstraat 26, 9712 EK, Groningen, The Netherlands

    Gosse Bouma

  2. Faculty of Economics and Business, University of Groningen, Nettelbosje 2, 9747 AE, Groningen, The Netherlands

    Ashwin Ittoo  & Hans Wortmann  & 

  3. CNAM-Laboratoire Cédric, 292 rue St. Martin, 75141, Paris Cedex 03, France

    Elisabeth Métais

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© 2012 Springer-Verlag Berlin Heidelberg

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Das, D., Poria, S., Bandyopadhyay, S. (2012). A Classifier Based Approach to Emotion Lexicon Construction. In: Bouma, G., Ittoo, A., Métais, E., Wortmann, H. (eds) Natural Language Processing and Information Systems. NLDB 2012. Lecture Notes in Computer Science, vol 7337. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31178-9_41

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  • DOI: https://doi.org/10.1007/978-3-642-31178-9_41

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31177-2

  • Online ISBN: 978-3-642-31178-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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