1School of Information and Cyber Security, People’s Public Security University of China, Beijing 102600, China 2TRS Information Technology Co., Ltd., Beijing 100101, China
【目的】综述网络舆情预警的发展态势,总结网络舆情预警的研究内容与进展。【文献范围】 在Web of Science核心数据库和CNKI分别以舆情预警、网络舆情、舆情风险等相关词汇作为关键词进行检索,经阅读筛选,共选取52篇能够代表学科基础与前沿发展态势的文献进行综合述评。【方法】从网络舆情特性与风险评价指标的角度归纳网络舆情预警的基础,总结当前网络舆情预警的研究进展与不足之处。【结果】目前主要相关研究分别基于专家赋权、机器学习、传播过程、情感分析4个方法类别,均能在适用场景下准确预警网络舆情的风险等级,这对网络环境以及社会安定具有重要意义。【局限】 网络舆情风险应对研究中,针对政府管控对策的文献较多,出于对预警的侧重,只选择部分有关预警技术的文献进行分析。【结论】目前相关工作对网络舆情的概念过于细分,不具有普适性;风险评价指标尚需完善;验证过程相对片面,缺乏权威统一的标准来比较不同监测系统的优劣。
[Objective] This paper summarizes the developments of early warning research for online public opinion. [Coverage] We searched the Web of Science and CNKI with related terms such as public opinion warning, online public opinion, and public opinion risks. A total of 52 articles representing the foundations of the disciplines and the development trends were selected for a comprehensive review. [Methods] We summarized the foundations of early warning studies from the perspective of online public opinion characteristics and risk evaluations. Then, we examined the status quo of current research on early warning for online public opinion. [Results] Currently, most research focuses on expert empowerment, machine learning, communication process, and sentiment analysis. All of them can accurately predict the risk level of online public opinion, which is significant to the online environment and social stability. [Limitations] More research is needed to review early warning technology. [Conclusions] The existing research does not provide universal concepts for online public opinion. The risk evaluation method needs to be improved. We should also establish authoritative and unified standards to compare the performance of different monitoring systems.
迪路阳, 钟寒, 施水才. 网络舆情预警研究综述*[J]. 数据分析与知识发现, 2023, 7(8): 17-29.
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