Discriminative features fusion with bert for social sentiment analysis

Duy Duc Le Nguyen, Yen Chun Huang, Yung Chun Chang

研究成果: 書貢獻/報告類型會議貢獻

1 引文 斯高帕斯(Scopus)

摘要

The need for sentiment analysis in social networks is increasing. In recent years, many studies have shifted from author sentiment research to reader sentiment research. However, the use of words that hinders sentiment analysis is very diverse. In this paper, we provide a model that combines the latest and most recent contextual text embedding technology and feature selection to more accurately detect the emotional intent of an article. We named it DF2BERT (Discriminative Features Fusion with Bert), and extensively applied datasets in different languages and different text classification tasks to validate our method, and compared it with several well-known approaches. Experimental results show that our model can effectively predict sentiment behind the text which outperform comparisons.

原文英語
主出版物標題Trends in Artificial Intelligence Theory and Applications. Artificial Intelligence Practices - 33rd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2020, Proceedings
編輯Hamido Fujita, Jun Sasaki, Philippe Fournier-Viger, Moonis Ali
發行者Springer Science and Business Media Deutschland GmbH
頁面30-35
頁數6
ISBN(列印)9783030557881
DOIs
出版狀態已發佈 - 2020
事件33rd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2020 - Kitakyushu, 日本
持續時間: 9月 22 20209月 25 2020

出版系列

名字Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
12144 LNAI
ISSN(列印)0302-9743
ISSN(電子)1611-3349

會議

會議33rd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2020
國家/地區日本
城市Kitakyushu
期間9/22/209/25/20

ASJC Scopus subject areas

  • 理論電腦科學
  • 一般電腦科學

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