Identifying Leaders and Dissemination Paths of Public Opinion
Xu Yabin1,2(),Sun Qiutian2
1Beijing Key Laboratory of Internet Culture and Digital Dissemination Research, Beijing Information Science and Technology University, Beijing 100101, China 2School of Computer, Beijing Information Science and Technology University, Beijing 100101, China
[Objective] This study proposes new method to monitor social media, aiming to limit or guide the spread of public opinion. [Methods] First, we constructed an OLMT model to identify opinion leaders based on the dissemination force and topological potential. Then, we modified the Transformer model to build a social media behavior prediction model (MF-Transformer) with high parallelism and attention mechanism. [Results] The proposed models identified opinion leaders and their retweeting behaviors, as well as the main dissemination paths of online public opinion. The recall and accuracy of the predicted results were 92.17% and 99.07%, respectively, which were higher than those of the existing methods. [Limitations] We only examined our new models with data from Sina Weibo. [Conclusions] The proposed models could effectively identify online opinion leaders, as well as predict the dissemination paths of their comments and retweets.
徐雅斌, 孙秋天. 特定舆情的意见领袖挖掘和关键传播路径预测[J]. 数据分析与知识发现, 2021, 5(2): 32-42.
Xu Yabin, Sun Qiutian. Identifying Leaders and Dissemination Paths of Public Opinion. Data Analysis and Knowledge Discovery, 2021, 5(2): 32-42.
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