摘要
[目的/意义]对恐怖事件情境下微博影响力进行预测并揭示其演化模式有助于反恐部门及时预见潜在的问题与危害,并迅速采取有效的应对措施。[研究设计/方法]本文提取了恐怖事件情境下微博的用户特征、时间特征和内容特征,构建了基于逻辑回归模型的恐怖事件微博影响力预测模型,并对预测模型进行训练和评估。[结论/发现]模型的预测准确率达到85.8%,能有效地完成预测任务。此外,对恐怖事件中高影响力微博的特征进行分析和总结,最后,提出基于h指数的微博主题影响力量化方法,并分析了恐怖事件情境下微博主题影响力的演化规律。[创新/价值]研究结果有助于发现可能产生高影响力的恐怖事件相关微博,评估微博信息的传播规模,了解公众对恐怖事件的关注内容、强度及变化规律,协助反恐部门进行舆情管理。
[Purpose/Significance]The prediction of microblog entries’influence in the context of terrorist events and the revelation of their evolution patterns can help the counter-terrorism departments foresee potential problems and hazards in time and take effective measures to respond quickly.[Design/Methodology]In this paper,the features of users,time and contents of microblog entries in terrorist incidents were extracted and a microblog influence prediction model was developed,trained and evaluated based on the logistic regression model.[Findings/Conclusion]The accuracy rate of the proposed model reaches 85.8%,which means it can effectively predict the influence of microblog entries.This paper analyzes the characteristics of high-influence microblogs about terrorist incidents.A quantitative method of microblog topics’influence according to h-index is proposed and the topics’evolutionary patterns are further explored.[Originality/Value]The findings can help identify microblog entries of high influence about terrorist events,assess the scale of microblog information dissemination,understand the contents,intensity and evolution of public attention,and assist counter-terrorism departments in public opinion management.
出处
《图书情报知识》
CSSCI
北大核心
2019年第4期52-61,81,共11页
Documentation,Information & Knowledge
基金
教育部哲学社会科学研究重大课题攻关项目“提高反恐怖主义情报信息工作能力对策研究”(17JZD034)
国家自然科学基金重大课题“国家安全大数据综合信息集成与分析方法”(71790612)的研究成果之一
关键词
恐怖事件
微博
影响力
预测
演化
主题识别
情感分析
H指数
Terrorist events
Microblog
Influence
Prediction
Evolution
Topic identification
Sentiment analysis
H-index
