Sentiment Classification of Social Media Text Considering User Attribute | |
Li, Junjie1,2; Yang, Haitong3; Zong,Chengqing1,2 | |
2016 | |
会议日期 | 2016-12 |
会议地点 | Kunming, China |
英文摘要 | Social media texts pose a great challenge to sentiment classification. Existing classification methods focus on exploiting sophisticated features or incorporating user interactions, such as following and retweeting. Nevertheless, these methods ignore user attributes such as age, gender and location, which is proved to be a very important prior in determining sentiment polarity according to our analysis. In this paper, we propose two algorithms to make full use of user attributes: 1) incorporate them as simple features, 2) design a graph-based method to model relationship between tweets posted by users with similar attributes. The extensive experiments on seven movie datasets in Sina Weibo show the superior performance of our methods in handling these short and informal texts. |
语种 | 英语 |
内容类型 | 会议论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/23103] |
专题 | 自动化研究所_模式识别国家重点实验室_自然语言处理团队 |
通讯作者 | Zong,Chengqing |
作者单位 | 1.National Laboratory of Pattern Recognition, Institute of Automation, CAS, Beijing, China 2.University of Chinese Academy of Sciences, Beijing, China 3.School of Computer, Central China Normal University, Wuhan 430079, China |
推荐引用方式 GB/T 7714 | Li, Junjie,Yang, Haitong,Zong,Chengqing. Sentiment Classification of Social Media Text Considering User Attribute[C]. 见:. Kunming, China. 2016-12. |
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