https://scholars.lib.ntu.edu.tw/handle/123456789/632523
標題: | Stance identification by sentiment and target detection | 作者: | Chen C.-C Tsai H.-Y Huang H.-H HSIN-HSI CHEN |
關鍵字: | Capsule network; Sentiment analysis; Stance detection | 公開日期: | 2020 | 起(迄)頁: | 331-338 | 來源出版物: | Proceedings - 2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2020 | 摘要: | Stance detection has attracted attention for several years. Previous work focuses mainly on a supervised topic-specific setting which requires labeled data for each individual topic. In this paper, we discuss the characteristics of different types of topics, and the interaction among sentiment, target, and stance in a sentence. We propose an approach without the need of stancelabeled data to identify stance incorporating the findings of their interaction. The proposed approach is topic independent and can be applied to individual topics flexibly. Furthermore, we evaluate our method on the SemEva1-2016 dataset for detecting stance in tweets, which contains six topics of two different types. Experimental results show that our approach is promising even when stance-labeled data is not available. © 2020 IEEE. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85114437676&doi=10.1109%2fWIIAT50758.2020.00047&partnerID=40&md5=7435219ef1c4f6d45c18e81337da5153 https://scholars.lib.ntu.edu.tw/handle/123456789/632523 |
DOI: | 10.1109/WIIAT50758.2020.00047 | SDG/關鍵字: | Intelligent agents; Labeled data |
顯示於: | 資訊工程學系 |
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