New words enlightened sentiment analysis in social media

Chiyu Cai, Linjing Li, Dajun Zeng

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations


Public sentiment permeated through social media is usually regarded as an important measure for hot event detecting, policy making and so forth, hence many governments and intelligence agencies have been launching various initiatives to facilitate theories, technologies and systems toward monitoring its fluctuation. Recently, massive new words are created and widely spread in social media, and they pose a great influence on sentiment analysis. Facing this situation, most previous work still just add those new words into sentiment lexicon, none of the existed researches focuses on the role and influence of new words in emotional expression. In this paper, we pay more attention to the influence of new words and propose two novel new words based sentiment analysis methods, named NWLb and NWSA, the former only with the help of lexicon and the latter further incorporates machine learning, which utilize the distinctive role of new words to improve the effectiveness of sentiment analysis in social media. Experiments on real social media dataset demonstrate the effectiveness and performance of our methods.

Original languageEnglish (US)
Title of host publicationIEEE International Conference on Intelligence and Security Informatics
Subtitle of host publicationCybersecurity and Big Data, ISI 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages3
ISBN (Electronic)9781509038657
StatePublished - Nov 15 2016
Event14th IEEE International Conference on Intelligence and Security Informatics, ISI 2015 - Tucson, United States
Duration: Sep 28 2016Sep 30 2016


Other14th IEEE International Conference on Intelligence and Security Informatics, ISI 2015
Country/TerritoryUnited States


  • lexicon based method
  • machine learning
  • sentiment analysis
  • social media

ASJC Scopus subject areas

  • Information Systems
  • Artificial Intelligence
  • Computer Networks and Communications
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality


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