Exploiting Emoticons in Sentiment Analysis

Alexander Hogenboom, DM Bal, Flavius Frasincar, MA Bal, Franciska de Jong, U Kaymak

Research output: Chapter/Conference proceedingConference proceedingAcademicpeer-review

150 Citations (Scopus)


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 publicationTwenty-Eighth Symposium on Applied Computing (SAC 2013)
EditorsS.Y. Shin, J.C. Maldonado
Number of pages8
Publication statusPublished - 18 Mar 2013


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