基于层次观点树的社交媒体多维度观点挖掘研究

doi:10.3772/j.issn.1000-0135.2023.03.005

情报学报

2023, Vol. 42

Issue (3): 304-315 DOI: 10.3772/j.issn.1000-0135.2023.03.005

情报技术与应用

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基于层次观点树的社交媒体多维度观点挖掘研究

习海旭^1,2, 章成志¹, 赵毅¹, 田亮¹

1.南京理工大学经济管理学院信息管理系，南京 210094
2.江苏理工学院计算机工程学院，常州 213001

Multi-dimension Public Opinion Mining of Social Media Based on the Hierarchical Viewpoint Tree

Xi Haixu^1,2, 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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摘要挖掘社交媒体舆论中隐含的观点有助于人们快速有效地了解社交媒体舆论，避免主观和随意地发表评论，传播错误信息进而引发恶性事件。目前，社交媒体观点挖掘主要从观点主题、倾向性或某方面内容等单个维度分析舆论，人们难以全面认识舆论并掌握这些观点内容之间的逻辑关联等多维度信息，且各子任务的相关性能还有待提高。为了更准确地了解且综合地分析不同维度的舆论信息，促进人们对社交媒体舆论的深入认知，本文提出了一种面向社交媒体短文本，体现各维度观点内容之间逻辑关系的层次观点树构建方法，并选取推特（Twitter）中有关羟基氯喹治疗COVID-19疾病的话题内容，进行层次观点树构建的实证研究。结果表明，本文提出的层次观点树构建方法能够提供多维度、易理解的社交媒体观点信息。

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	习海旭
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关键词 ：社交媒体, 主题聚类, 立场识别, 观点挖掘, 层次观点树

收稿日期: 2022-03-12

基金资助:国家社会科学基金项目“基于情境感知的移动图书馆服务模型的构建与应用研究”（19BTQ045）。

作者简介: 习海旭，男，1981年生，博士研究生，副教授，主要研究领域为信息检索与文本挖掘；章成志，男，1977年生，博士，教授，博士生导师，主要研究领域为信息组织、信息检索、数据挖掘及自然语言处理，E-mail：zhangcz@njust.edu.cn；赵毅，男，1993年生，博士研究生，主要研究领域为文本挖掘与科学计量学；田亮，男，1997年生，硕士研究生，主要研究领域为文本挖掘与科学计量学；

引用本文:

习海旭, 章成志, 赵毅, 田亮. 基于层次观点树的社交媒体多维度观点挖掘研究[J]. 情报学报, 2023, 42(3): 304-315.
Xi Haixu, Zhang Chengzhi, Zhao Yi, Tian Liang. Multi-dimension Public Opinion Mining of Social Media Based on the Hierarchical Viewpoint Tree. 情报学报, 2023, 42(3): 304-315.

链接本文:

https://qbxb.istic.ac.cn/CN/10.3772/j.issn.1000-0135.2023.03.005 或 https://qbxb.istic.ac.cn/CN/Y2023/V42/I3/304

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