A rule-based approach to implicit emotion detection in text

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Abstract

Most research in the area of emotion detection in written text focused on detecting explicit expressions of emotions in text. In this paper, we present a rule-based pipeline approach for detecting implicit emotions in written text without emotion-bearing words based on the OCC Model. We have evaluated our approach on three different datasets with five emotion categories. Our results show that the proposed approach outperforms the lexicon matching method consistently across all the three datasets by a large margin of 17–30% in F-measure and gives competitive performance compared to a supervised classifier. In particular, when dealing with formal text which follows grammatical rules strictly, our approach gives an average F-measure of 82.7% on “Happy”, “Angry-Disgust” and “Sad”, even outperforming the supervised baseline by nearly 17% in F-measure. Our preliminary results show the feasibility of the approach for the task of implicit emotion detection in written text.

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  • Implicit emotion detection in text

    Rights statement: The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-19581-0_17

    Accepted author manuscript, 212 KB, PDF-document

Details

Publication date4 Jun 2015
Publication titleNatural language processing and information systems : 20th international conference on applications of Natural Language to Information Systems, NLDB 2015, Passau, Germany, June 17-19, 2015, proceedings
EditorsChris Biemann, Siegfried Handschuh, André Freitas, et al
Place of PublicationCham (CHE)
PublisherSpringer
Pages197-203
Number of pages7
ISBN (Electronic)978-3-319-19581-0
ISBN (Print)978-3-319-19580-3
Original languageEnglish
Event20th International Conference on Applications of Natural Language to Information Systems - Passau, Germany

Publication series

NameLecture notes in computer science
PublisherSpringer
Volume9103
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference20th International Conference on Applications of Natural Language to Information Systems
Abbreviated titleNLDB 2015
CountryGermany
CityPassau
Period17/06/1519/06/15

Bibliographic note

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-19581-0_17

    Keywords

  • emotion detection, implicit emotions, OCC model, rule-based approach

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