Twitter Sentiment Analysis: The Good the Bad and the OMG!

Authors

  • Efthymios Kouloumpis i-sieve Technologies
  • Theresa Wilson Johns Hopkins University
  • Johanna Moore University of Edinburgh

DOI:

https://doi.org/10.1609/icwsm.v5i1.14185

Abstract

In this paper, we investigate the utility of linguistic features for detecting the sentiment of Twitter messages. We evaluate the usefulness of existing lexical resources as well as features that capture information about the informal and creative language used in microblogging. We take a supervied approach to the problem, but leverage existing hashtags in the Twitter data for building training data.

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Published

2021-08-03

How to Cite

Kouloumpis, E., Wilson, T., & Moore, J. (2021). Twitter Sentiment Analysis: The Good the Bad and the OMG!. Proceedings of the International AAAI Conference on Web and Social Media, 5(1), 538-541. https://doi.org/10.1609/icwsm.v5i1.14185