EMFSA: Emoji-based multifeature fusion sentiment analysis
文献类型：期刊论文
| 作者 | Tang, Hongmei3,4; Tang, Wenzhong3; Zhu, Dixiongxiao3; Wang, Shuai3; Wang, Yanyang1,5; Wang, Lihong2 |
| 刊名 | PLOS ONE
 |
| 出版日期 | 2024-09-19 |
| 卷号 | 19期号:9页码:e0310715 |
| ISSN号 | 1932-6203 |
| DOI | 10.1371/journal.pone.0310715 |
| 产权排序 | 2 |
| 英文摘要 | Short texts on social platforms often suffer from insufficient emotional semantic expressions, sparse features, and polysemy. To enhance the accuracy achieved by sentiment analysis for short texts, this paper proposes an emoji-based multifeature fusion sentiment analysis model (EMFSA). The model mines the sentiments of emojis, topics, and text features. Initially, a pretraining method for feature extraction is employed to enhance the semantic expressions of emotions in text by extracting contextual semantic information from emojis. Following this, a sentiment- and emoji-masked language model is designed to prioritize the masking of emojis and words with implicit sentiments, focusing on learning the emotional semantics contained in text. Additionally, we proposed a multifeature fusion method based on a cross-attention mechanism by determining the importance of each word in a text from a topic perspective. Next, this method is integrated with the original semantic information of emojis and the enhanced text features, attaining improved sentiment representation accuracy for short texts. Comparative experiments conducted with the state-of-the-art baseline methods on three public datasets demonstrate that the proposed model achieves accuracy improvements of 2.3%, 10.9%, and 2.7%, respectively, validating its effectiveness. |
| 资助项目 | National Natural Science Foundation of China[62272022] ; National Key Research and Development Program of China[210YBXM2024106007] ; National Key Research and Development Program of China[2022YFB3207700] |
| WOS研究方向 | Science & Technology - Other Topics |
| 语种 | 英语 |
| WOS记录号 | WOS:001316557200076 |
| 出版者 | PUBLIC LIBRARY SCIENCE |
| 资助机构 | National Natural Science Foundation of China ; National Key Research and Development Program of China |
| 源URL | [http://ir.xao.ac.cn/handle/45760611-7/7021]  |
| 专题 | 新疆天文台_计算机技术室 |
| 通讯作者 | Tang, Wenzhong; Wang, Shuai |
| 作者单位 | 1.Jiangxi Res Inst Beihang Univ, Nanchan, Peoples R China 2.Coordinat Ctr China, Natl Comp Network Emergency Response Tech Team, Beijing, Peoples R China 3.Beihang Univ, Sch Comp Sci & Engn, Beijing, Peoples R China 4.Chinese Acad Sci, Xinjiang Astron Observ, Urumqi, Peoples R China 5.Beihang Univ, Sch Aeronaut Sci & Engn, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Tang, Hongmei,Tang, Wenzhong,Zhu, Dixiongxiao,et al. EMFSA: Emoji-based multifeature fusion sentiment analysis[J]. PLOS ONE,2024,19(9):e0310715. |
| APA | Tang, Hongmei,Tang, Wenzhong,Zhu, Dixiongxiao,Wang, Shuai,Wang, Yanyang,&Wang, Lihong.(2024).EMFSA: Emoji-based multifeature fusion sentiment analysis.PLOS ONE,19(9),e0310715. |
| MLA | Tang, Hongmei,et al."EMFSA: Emoji-based multifeature fusion sentiment analysis".PLOS ONE 19.9(2024):e0310715. |
入库方式： OAI收割
来源：新疆天文台
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