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| Multi-dimension Public Opinion Mining of Social Media Based on the Hierarchical Viewpoint Tree |
| Xi Haixu1,2, Zhang Chengzhi1, Zhao Yi1, Tian Liang1 |
1.Department of Information Management, School of Economics & Management, Nanjing University of Science & Technology, Nanjing 210094
2.School of Computer Engineering, Jiangsu University of Technology, Changzhou 213001 |
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Abstract Mining of public viewpoints on social media can help people quickly and effectively understand them, avoiding subjective and casual comments and spreading wrong information, leading to malignant events. Currently, viewpoint mining on social media mainly analyzes public opinion from a single dimension such as the theme, tendency, or aspect content of viewpoints. It is difficult for people to fully understand public opinion and grasp multi-dimensional information such as the logical relationship between these viewpoints; therefore, the relevant performance of each subtask needs to be improved. To more accurately understand and comprehensively analyze public opinion information of different dimensions and promote people's in-depth understanding of public opinion on social media, this article proposes a construction method of the hierarchical viewpoint tree on social media which reflects the logical relationship between viewpoints in various dimensions, and selects the topic of hydroxychloroquine as the treatment of COVID-19 on Twitter to conduct an empirical study on this topic. The results show that the construction method of the proposed hierarchical viewpoint tree can provide multi-dimensional and understandable viewpoints on social media.
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Received: 12 March 2022
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