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Holder and Topic Based Analysis of Emotions on Blog Texts: A Case Study for Bengali

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Mining Social Networks and Security Informatics

Part of the book series: Lecture Notes in Social Networks ((LNSN))

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Abstract

The paper presents an extended approach of analyzing emotions of the blog users on different topics. The rule based techniques to identify emotion holders and topics with respect to their corresponding emotional expressions helps to develop the baseline system. On the other hand, the Support Vector Machine (SVM) based supervised framework identifies the holders, topics and emotional expressions from the blog sentences by outperforming the baseline system. The existence of many to many relations between the holders and the topics with respect to Ekman’s six different emotion classes has been examined using two way evaluation techniques, one is with respect to holder and other is from the perspective of topic. The results of the system were found satisfactory in comparison with the agreement of the subjective annotation. The error analysis shows that the topic of a blog at document level is not always conveyed at the sentence level. Moreover, the difficulty in identifying topic from a blog document is due to the problem of identifying some features like bigrams, Named Entities and sentiment. Thus, we employed a semantic clustering approach along with these features to identify the similarity between document level topic and sentential topic as well as to improve the results of identifying the document level topic.

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Notes

  1. 1.

    http://www.internetworldstats.com/stats.htm.

  2. 2.

    http://www.ethnologue.com/ethno_docs/distribution.asp?by=size.

  3. 3.

    http://ltrc.iiit.ac.in/showfile.php?filename=downloads/shallow_parser.php.

  4. 4.

    www.amarblog.com/.

  5. 5.

    http://home.uchicago.edu/~cbs2/banglainstruction.html.

  6. 6.

    English to Indian Languages Machine Translation (EILMT) is a TDIL project undertaken by the consortium of different premier institutes and sponsored by MCIT, Govt. of India.

  7. 7.

    http://dsal.uchicago.edu/dictionaries/biswas-bangala/.

  8. 8.

    http://www.d.umn.edu/tpederse/similarity.html.

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Acknowledgements

The work reported in this paper was supported by a grant from the India-Japan Cooperative Programme (DSTJST) 2009 Research project entitled “Sentiment Analysis where AI meets Psychology” funded by Department of Science and Technology (DST), Government of India.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Jadavpur University, Kolkata, India

    Dipankar Das & Sivaji Bandyopadhyay

Authors
  1. Dipankar Das
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  2. Sivaji Bandyopadhyay
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Correspondence to Dipankar Das .

Editor information

Editors and Affiliations

  1. Department of Computer Engineering, TOBB University, Sogutozu Cad No. 43, Sogutozu Ankara, Turkey

    Tansel Özyer

  2. Information Technologies Institute, TUBITAK BILGEM, Gebze, Kocaeli, 41470, Turkey

    Zeki Erdem

  3. Computer Science, University of Calgary, University Dr. NW 2500, Calgary, T2N 1N4, Canada

    Jon Rokne

  4. American University of Sharjah, Universities City, Sharjah, Saudi Arabia

    Suheil Khoury

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Das, D., Bandyopadhyay, S. (2013). Holder and Topic Based Analysis of Emotions on Blog Texts: A Case Study for Bengali. In: Özyer, T., Erdem, Z., Rokne, J., Khoury, S. (eds) Mining Social Networks and Security Informatics. Lecture Notes in Social Networks. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-6359-3_7

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  • DOI: https://doi.org/10.1007/978-94-007-6359-3_7

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-007-6358-6

  • Online ISBN: 978-94-007-6359-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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