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| Grouping Microblog Users of Trending Topics Based on Sentiment Analysis |
Zhang Mengyao,Zhu Guangli( ),Zhang Shunxiang,Zhang Biao |
| Computer Science and Engineering, Anhui University of Science & technology, Huainan 232001, China |
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Abstract [Objective] The paper proposes a model to group users of Weibo trending topics. [Methods] First, we computed the sentiment of user’s texts with sentiment dictionary. Then, we combined sentiment and text vector expression to determine the characteristics of user opinion. Finally, we grouped similar users with the K-means method. [Results] The proposed model divided users into three categories, and the value of evaluation index (CA) reached 78.2%. [Limitations] Our model needs to define the number of categories before dividing user groups. [Conclusions] The proposed model could effectively group users with the same sentimental views.
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Received: 28 October 2020
Published: 15 December 2020
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| Fund:National Natural Science Foundation of China(62076006);Anhui Provincial Natural Science Foundation(1908085MF189) |
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Corresponding Authors:
Zhu Guangli ORCID：0000-0003-4364-866X
E-mail: glzhu@aust.edu.cn
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