| 刘欣雨.基于弹幕的突发信息安全类事件舆情分析——以“滴滴平台下架”事件为例[J].情报工程,2022,8(4):085-109 |
| 基于弹幕的突发信息安全类事件舆情分析——以“滴滴平台下架”事件为例 |
| Analysis of Public Opinion Characteristics of Emergency Information Security Events Based on Bullet Screen —— Taking the “Didi Event” as An Example |
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| DOI：10.3772/j.issn.2095-915X.2022.04.008 |
| 中文关键词: 突发信息安全；网络舆情；内容分析；情感规律；羊群效应 |
| 英文关键词: Emergency information security; online public opinion; content analysis; law of emotions; herd effect |
| 基金项目: |
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| 摘要点击次数: 888 |
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| 中文摘要: |
| [ 目的 / 意义 ] 对突发信息安全事件在视频平台中的网络舆情进行分析，有利于把握网络舆情传播的方向路径，为管理者提出控制舆情的应对策略。[ 方法 / 过程 ] 本研究利用 Python 编程爬取 B 站上有关“滴滴平台下架”的视频弹幕信息，对弹幕内容进行热度趋势分析、语义网络及热点话题挖掘、情感分析以及羊群效应识别，以探究突发信息安全事件在视频平台中的舆情传播规律和用户情感特征。[ 结果 / 结论 ] 各视频弹幕高频词都出现了较为明显的分组现象，信息传递较多地依赖某些关键节点；网民在此次滴滴下架事件中没有较大的情感波动，能够理性的表达自己的观点看法。 |
| 英文摘要: |
| [Objective/Significance] The analysis of the network public opinion of the sudden information security incident in the video platform is conducive to grasping the direction and path of the network public opinion communication and putting forward coping strategies for the managers to control the public opinion. [Methods/Processes] In this study, Python programming was used to crawl the video bullet screen information of “Didi platform” on the Bilibili website, and heat trend analysis, semantic network and hot topics mining, sentiment analysis, and herd effect identification were carried out on the bullet screen content, so as to explore the public opinion communication rules and user characteristics of emergency information security events in the video platform. [Result/Conclusion] The high-frequency words in video bullet screen appear relatively obvious grouping phenomenon, and the information transmission mostly depends on some key nodes; there was no big emotional fluctuation in the didi removal event, and netizens were able to rationally express their opinions. |
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