摘要
【目的】对社交网络进行有效的监管,在一定程度上把控和干预舆情的传播和发展变化。【方法】提出一种综合拓扑势网红度、传播力和关注度的意见领袖挖掘模型OLMT,由此可以从更多的角度、更加客观地进行意见领袖挖掘。此外,对Transformer模型进行改造,构建社交网络传播行为预测模型MF-Transformer,利用其高度并行性和注意力机制,可以更加高效、准确地预测意见领袖的转发行为。【结果】结合意见领袖挖掘结果以及传播行为预测结果,有效预测舆情传播过程中由意见领袖构成的关键传播路径。预测结果的查全率和查准率分别达92.17%和99.07%,明显高于其他方法。【局限】实验主要面向特定舆情事件的新浪微博数据集,没有面向推特等数据集。【结论】本文提出的意见领袖挖掘模型和传播行为预测模型不仅可以更加准确地挖掘出意见领袖,而且可以有效预测舆情传播过程中的关键路径。
[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.
作者
徐雅斌
孙秋天
Xu Yabin;Sun Qiutian(Beijing Key Laboratory of Internet Culture and Digital Dissemination Research,Beijing Information Science and Technology University,Beying 100101,China;School of Computer,Bering Information Science and Technology University,Beijing 100101,China)
出处
《数据分析与知识发现》
CSSCI
CSCD
北大核心
2021年第2期32-42,共11页
Data Analysis and Knowledge Discovery
基金
国家自然科学基金项目(项目编号:61672101)
网络文化与数字传播北京市重点实验室开放课题(项目编号:ICDDXN004)
信息网络安全公安部重点实验室开放课题(项目编号:C18601)的研究成果之一。
关键词
舆情
意见领袖
传播行为预测
关键路径识别
Public Opinion
Opinion Leader
Social Network Behavior Prediction
Dissemination Paths Identification
