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Year 2022, Volume: 6 Issue: 1, 58 - 60, 20.07.2022

Abstract

References

  • Reference1: Gao, Wei, and Fabrizio Sebastiani. "Tweet sentiment: From classification to quantification." Advances in Social Networks Analysis and Mining (ASONAM), 2015 IEEE/ACM International Conference on. IEEE, 2015
  • Reference2: Boia, Marina, et al. "A:) is worth a thousand words: How people attachsentiment to emoticons and words in tweets." Social computing (socialcom),2013

Sentiment Analysis Of Tweets Using Natural Language Processing

Year 2022, Volume: 6 Issue: 1, 58 - 60, 20.07.2022

Abstract

Millions of people use Twitter and other social media sites to share their everyday thoughts in the form of tweets. It is a
short and straightforward way of expressing oneself, which is a hallmark of tweeting. As a result, we concentrated on sentiment
analysis of Twitter data in our research. Sentiment Analysis is a subset of natural language processing and text data mining. It is
feasible to investigate sentiment analysis using Twitter data. performed in a number of different circumstances The technique of
finding valuable patterns from textual data is referred to as sentiment analysis.

References

  • Reference1: Gao, Wei, and Fabrizio Sebastiani. "Tweet sentiment: From classification to quantification." Advances in Social Networks Analysis and Mining (ASONAM), 2015 IEEE/ACM International Conference on. IEEE, 2015
  • Reference2: Boia, Marina, et al. "A:) is worth a thousand words: How people attachsentiment to emoticons and words in tweets." Social computing (socialcom),2013
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Details

Primary Language English
Subjects Engineering
Journal Section Articles
Authors

Dursun Ekmekci 0000-0002-9830-7793

Fıras Shıhab 0000-0001-5956-4183

Publication Date July 20, 2022
Submission Date June 13, 2022
Published in Issue Year 2022 Volume: 6 Issue: 1

Cite

IEEE D. Ekmekci and F. Shıhab, “Sentiment Analysis Of Tweets Using Natural Language Processing”, IJMSIT, vol. 6, no. 1, pp. 58–60, 2022.