Chengyao Chen
ABSTRACT
Exploring the mechanism that explains how a user's opinion changes under the influence of his/her neighbors is of practical importance (e.g., for predicting the sentiment of his/her future opinion) and has attracted wide attention from both enterprises and academics.Though various opinion influence models have been proposed for opinion prediction, they only consider users' personal identities, but ignore their social identities with which people behave to fit the expectations of the others in the same group. In this work, we explore users' dual identities, including both personal identities and social identities to build a more comprehensive opinion influence model for a better understanding of opinion behaviors. A novel joint learning framework is proposed to simultaneously model opinion dynamics and detect social identity in a unified model. The effectiveness of the proposed approach is demonstrated through the experiments conducted on Twitter datasets
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Cross Ref
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- Chengyao Chen, Dehong Gao, Wenjie Li, and Yuexian Hou. 2014. Inferring topicdependent influence roles of Twiyyer users. In Proceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval. ACM, 1203--1206. Google ScholarDigital Library
- Chengyao Chen, Zhitao Wang, Yu Lei, and Wenjie Li. 2016. Content-based influence modeling for opinion behavior prediction. In Proceedings of the 26th International Conference on Computational Linguistics. 2207--2216.Google Scholar
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Index Terms
- Modeling Opinion Influence with User Dual Identity
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