Polarity Classification of Tweets Considering the Poster’s Emotional Change by a Combination of Naive Bayes and LSTM

Kiichi Tago, Kosuke Takagi, Qun Jin

研究成果: Conference contribution

抄録

Twitter, as a popular social networking service, is used all over the world, with which users post tweets for various purposes. When users post tweets, an emotion may be behind the messages. As the emotion changes over time, we should better consider their emotional changes and states when analyzing the tweets. In this study, we improve polarity classification by considering the poster’s emotional state. Firstly, we analyze the sentence structure of a tweet and calculate emotion scores for each category by Naive Bayes. Then, the poster’s emotion state is estimated by the emotion scores, and a prediction model of emotional state is created by Long Short Term Memory (LSTM). Based on the predicted emotional state, weights are added to the scores. Finally, polarity classification is performed based on the weighted emotion scores for each category. In our experiments, our approach showed better accuracy than other related studies.

本文言語English
ホスト出版物のタイトルComputational Science and Its Applications – ICCSA 2019 - 19th International Conference, 2019, Proceedings
編集者Sanjay Misra, Elena Stankova, Vladimir Korkhov, Carmelo Torre, Eufemia Tarantino, Ana Maria A.C. Rocha, David Taniar, Osvaldo Gervasi, Bernady O. Apduhan, Beniamino Murgante
出版社Springer-Verlag
ページ579-588
ページ数10
ISBN(印刷版)9783030242886
DOI
出版ステータスPublished - 2019 1 1
イベント19th International Conference on Computational Science and Its Applications, ICCSA 2019 - Saint Petersburg, Russian Federation
継続期間: 2019 7 12019 7 4

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
11619 LNCS
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Conference

Conference19th International Conference on Computational Science and Its Applications, ICCSA 2019
CountryRussian Federation
CitySaint Petersburg
Period19/7/119/7/4

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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