HBE: Hashtag-based emotion lexicons for twitter sentiment analysis

Fajri Koto, Mirna Adriani

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

10 Citations (Scopus)


In this paper we report the first effort of constructing emo- tion lexicon by utilizing Twitter as source of data. Specifically we used hashtag feature to obtain tweets with certain emotion label in English. There are eight emotion classes used in our work, comprising of angry, disgust, fear, joy, sad, surprise, trust and anticipation that refer to the Plutchik's wheel. To obtain the lexicon, we first ranked the words ac- cording to its term frequency. After that, we reduced some irrelevant words by removing words with low frequency. We also enriched the lexicon with the synonym and conducted filtering by utilizing sentiment lexicon (40,288 words). As result, we successfully constructed 4 Hashtag-Based Emo- tion (HBE) Lexicons through different procedures and called them as HBE-A1 (50,613 words), HBE-B1 (23,400 words), HBE-A2 (26,909 words) and HBE-B2 (14,905 words). In our experiment, we used the lexicons in investigating Twitter Sentiment Analysis and the result reveals that our proposed emotion lexicons can boost the accuracy and even improve over than NRC-Emotion lexicon. It is also worth noting that our construction idea is simple, automatic, inexpensive and suitable for Social Media analysis.

Original languageEnglish
Title of host publicationFIRE 2015 - Proceedings of the 7th Annual Meeting of the Forum for Information Retrieval Evaluation
EditorsPrasenjit Majumder, Mandar Mitra, Madhulika Agrawal, Parth Mehta
PublisherAssociation for Computing Machinery
Number of pages4
ISBN (Electronic)9781450340045
Publication statusPublished - 4 Dec 2015
Event7th Annual Meeting of the Forum for Information Retrieval Evaluation, FIRE 2015 - Gandhinagar, India
Duration: 4 Dec 20156 Dec 2015

Publication series

NameACM International Conference Proceeding Series


Conference7th Annual Meeting of the Forum for Information Retrieval Evaluation, FIRE 2015


  • Emotion lexicon
  • Hashtag
  • Polarity
  • Sentiment analysis
  • Sub-jectivity
  • Twitter


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