Abstract
User classification based on sentiment analysis makes it easier for researchers to understand the sentiment behavior characteristic of different groups. Since the current user classification method does not consider the fact of user’s sentiment fluctuation, this paper proposes a user group classification model takes into account the change of user’s sentiment. Firstly, the sentiment analysis of Microblog comments base on the Microblog sentiment dictionary. Calculate the user’s temporal sentiment vector and the user’s sentiment feature vector according to the rules made in this paper. Finally, k-means clustering is used to classify user based on the user’s sentiment feature vector. Experimental results validate the accuracy of the proposed model.
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Acknowledgement
This Research work was supported in part by 2018 Cultivation Project of Top Talent in Anhui Colleges and Universities (Grant No. gxbjZD15), in part by 2019 Anhui Provincial Natural Science Foundation Project (Grant No. 1908085MF189).
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Zhang, M., Zhu, G. (2021). A User Group Classification Model Based on Sentiment Analysis Under Microblog Hot Topic. In: Atiquzzaman, M., Yen, N., Xu, Z. (eds) Big Data Analytics for Cyber-Physical System in Smart City. BDCPS 2020. Advances in Intelligent Systems and Computing, vol 1303. Springer, Singapore. https://doi.org/10.1007/978-981-33-4572-0_269
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DOI: https://doi.org/10.1007/978-981-33-4572-0_269
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