AFFECTIVE BLOG ANALYZER - What People Feel to

Masato Tokuhisa, Jin'ichi Murakami, Satrou Ikehara

Abstract

This paper proposes an affective blog analyzer which can capture people's emotional targets. The existing affective analysis has some problems. For instance, polarity analysis or positive/negative classification for documents are developed, but emotional targets can not be extracted. Some investigations can capture customer's wanted/needed objects, but the knowledge is domain dependent. Therefore, it can not analyze people's everyday life. Against these problems, this paper uses a sentence pattern dictionary to analyze emotions. The dictionary covers Japanese fundamental 6,000 verbs and contains 14,800 patterns with emotional information for everyday life. This dictionary is available for analyzing the downloaded blog articles. After analyzing blogs, many keywords can be extracted as emotional targets. In order to filter and sort them for supporting blog analysts, two parameters are applied. One is Z-score in terms of the frequency of the target appearance, and another is probability of emotions. In the experiments, trendy and emotional targets were successfully extracted from 6-month-blogs. Thus, the effects of the patterns and parameters are confirmed.

References

  1. Elliott, C. (1992). The Affective Reasoner: A process model of emotions in a multi-agent system. PhD thesis, Northwestern University.
  2. Hatzivassiloglou, V. and McKeown, K. R. (1997). Predicting the semantic orientation of adjectives. In Proceedings of the Annual Meeting of the Association for Computational Linguistics, pages 174-181.
  3. Ikehara, S., Miyazaki, M., Shirai, S., Yokoo, A., Nakaiwa, H., Ogura, K., Ooyama, Y., and Hayashi, Y. (1997). Goi-Taikei: A Japanese Lexicon. Iwanami Shoten.
  4. Kanayama, H. and Nasukawa, T. (2008). Textual demand analysis: Detection of users' wants and needs from opinions. In Proceedings of the International Conference on Computational Linguistics, pages 409-416.
  5. Liu, H., Liberman, H., and Selker, T. (2003). A model of textual affect sensing using real-world knowledge. In Proceeding of the International Conference on Intelligent User Interfaces, pages 125-132.
  6. Ortony, A., Clore, G. L., and Collins, A. (1988). The Cognitive Structure of Emotions. Cambridge Univ. Press.
  7. Tokuhisa, M. and Okada, N. (1997). A conceptual analysis of emotional words for an intellectual, emotional agent. In Proc. of the Int. Conf. on Pacific Association for Computational Linguistics, pages 307-315.
  8. Tokuhisa, R., Inui, K., and Matsumoto, Y. (2008). Emotion classification using massive examples extracted from the web. In Proceedings of the International Conference on Computational Linguistics, pages 881-888.
  9. Turney, P. (2002). Thumbs up or thumbs down? semantic orientation applied to unsupervised classification of reviews. In Proc. of the Ann. Meeting of the Association for Computational Linguistics, pages 417-424.
Download


Paper Citation


in Harvard Style

Tokuhisa M., Murakami J. and Ikehara S. (2010). AFFECTIVE BLOG ANALYZER - What People Feel to . In Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-674-021-4, pages 247-252. DOI: 10.5220/0002719602470252


in Bibtex Style

@conference{icaart10,
author={Masato Tokuhisa and Jin'ichi Murakami and Satrou Ikehara},
title={AFFECTIVE BLOG ANALYZER - What People Feel to},
booktitle={Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2010},
pages={247-252},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002719602470252},
isbn={978-989-674-021-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - AFFECTIVE BLOG ANALYZER - What People Feel to
SN - 978-989-674-021-4
AU - Tokuhisa M.
AU - Murakami J.
AU - Ikehara S.
PY - 2010
SP - 247
EP - 252
DO - 10.5220/0002719602470252