https://scholars.lib.ntu.edu.tw/handle/123456789/490532
標題: | Context-aware sentiment propagation using LDA topic modeling on Chinese ConceptNet | 作者: | Chou, P.-H. Tsai, R.T.-H. Hsu, J.Y.-J. YUNG-JEN HSU |
關鍵字: | Commonsense knowledge; Context-aware; Sentiment analysis; Sentiment dictionary; Topic model; Value propagation | 公開日期: | 2017 | 卷: | 21 | 期: | 11 | 起(迄)頁: | 2911-2921 | 來源出版物: | Soft Computing | 摘要: | A sentiment dictionary is a valuable resource in sentiment analysis research. Previous work has propagated sentiment values from existing dictionaries via semantic networks to build wide-coverage dictionaries efficiently. Unfortunately, this blind propagation method tends to incorrectly estimate sentiment values the further along the chain it goes from the seed word because it does not consider word senses in context. In this work, we propose a context-aware propagation method on Chinese ConceptNet to help resolve this issue. In our approach, we represent contexts using LDA topic modeling by generating a topic for each context. We can then assign concepts different sentiment values for different topics when propagating sentiments on Chinese ConceptNet. Our experiments on both microblog posts and drama dialogue subtitles show that our context-aware approach improves the accuracy of sentiment polarity prediction. © 2016, Springer-Verlag Berlin Heidelberg. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/490532 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84979986867&doi=10.1007%2fs00500-016-2273-0&partnerID=40&md5=ed7edcc8b1d2ab2381ed5f7af8218e1d |
ISSN: | 14327643 | DOI: | 10.1007/s00500-016-2273-0 | SDG/關鍵字: | Semantics; Commonsense knowledge; Context-Aware; Sentiment analysis; Sentiment dictionaries; Topic Modeling; Data mining |
顯示於: | 資訊工程學系 |
在 IR 系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。