Exploiting emoticons in sentiment analysis

A.C. Hogenboom, D. Bal, F. Frasincar, M. Bal, F.M.G. Jong, de, U. Kaymak

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

132 Citations (Scopus)
1 Downloads (Pure)

Abstract

As people increasingly use emoticons in text in order to express, stress, or disambiguate their sentiment, it is crucial for automated sentiment analysis tools to correctly account for such graphical cues for sentiment. We analyze how emoticons typically convey sentiment and demonstrate how we can exploit this by using a novel, manually created emoticon sentiment lexicon in order to improve a state-of-the-art lexicon-based sentiment classification method. We evaluate our approach on 2,080 Dutch tweets and forum messages, which all contain emoticons and have been manually annotated for sentiment. On this corpus, paragraph-level accounting for sentiment implied by emoticons significantly improves sentiment classification accuracy. This indicates that whenever emoticons are used, their associated sentiment dominates the sentiment conveyed by textual cues and forms a good proxy for intended sentiment.
Original languageEnglish
Title of host publicationProceedings of the 28th Symposium On Applied Computing (SAC 2013), March 18-22, 2013, Coimbra, Portugal
EditorsS.Y. Shin, J.C. Maldonado
Place of PublicationNew York
PublisherAssociation for Computing Machinery, Inc
Pages703-710
ISBN (Print)978-1-4503-1656-9
DOIs
Publication statusPublished - 2013
Event28th ACM Symposium on Applied Computing (SAC 2013) - Coimbra, Portugal
Duration: 18 Mar 201322 Mar 2013
Conference number: 28

Conference

Conference28th ACM Symposium on Applied Computing (SAC 2013)
Abbreviated titleSAC 2013
Country/TerritoryPortugal
CityCoimbra
Period18/03/1322/03/13

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