文章摘要
刘玉文,张楚,黄锦泉,刘鹏,谢静.网络热点事件中网络暴力影响因素研究[J].情报工程,2023,9(3):103-113
网络热点事件中网络暴力影响因素研究
Research on the Influencing Factors of Cyber Violence in Hot Network Events
  
DOI:10.3772/j.issn.2095-915X.2023.03.009
中文关键词: 热点事件;网络暴力;影响因素;网络要素;相关性
英文关键词: Hot events; cyber violence; influence factor; network elements; correlation
基金项目:安徽省哲学社会科学规划项目“复杂网络舆情下网络暴力行为定量分析及其对网络生态破坏作用研究”(AHSKQ2019D070)。
作者单位
刘玉文 蚌埠医学院 卫生管理学院 蚌埠 233030 
张楚 蚌埠医学院 卫生管理学院 蚌埠 233030 
黄锦泉 蚌埠医学院 卫生管理学院 蚌埠 233030 
刘鹏 蚌埠医学院 卫生管理学院 蚌埠 233030 
谢静 蚌埠医学院 卫生管理学院 蚌埠 233030 
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中文摘要:
      [ 目的/ 意义] 网络热点事件中网络暴力受到多种因素影响,对其分析能够了解网络暴力传播规律,为舆情引导提供方法指导。当前网络舆情研究主要集中在主题挖掘、情感分析、行为分析以及意见领袖识别等领域,网络暴力传播规律研究相对较少。[ 方法/ 过程] 本文以网络热点事件为研究对象,首先,获取事件下评论用户的组织关系、评论文本、年龄等数据;其次,对事件负面程度进行评分以及对评论文本的暴力属性进行标注;最后,通过计算意见领袖影响力指数、高质量评论指数等网络要素,分析这些要素与网络暴力之间的相关关系。[ 结果/ 结论] 对10 个网络热点事件进行分析,结果表明:事件负面程度(r = 0.99)、负面意见领袖影响力指数(r = 0.79)、负面高质量评论指数(r = 0.77)与网络暴力之间呈正相关关系;网民年龄(r = - 0.61)、正面意见领袖影响力指数(r = -0.86)、正面高质量评论指数(r = -0.81)与网络暴力呈负相关关系。事件负面程度、意见领袖、高质量评论、网民年龄是网络暴力影响因素。
英文摘要:
      [Objective/Significance] The cyber violence in network hot events is affected by many factors, and its analysis can understand the law of network violence transmission and provide method guidance for public opinion guidance. At present, the research of online public opinion mainly focuses on the fields of topic mining, emotion analysis, behavior analysis and opinion leader identification, while the research on the law of the spread of online violence is relatively lacking. [Methods/Processes]This paper takes the network hot events as the research object. First, we obtain the organization relationship, comment text,age and other data of comment users under the event; Then, the severity of the negative events and the violence attribute of the comment text are marked; Finally, by calculating the influence index of opinion leaders, high-quality comment index and other network elements, analyze the correlation between these elements and online violence. [Results /Conclusions] The analysis of 10 hot internet events shows that there is a positive correlation between the negative degree of the event (r=0.99), negative opinion leader influence index (r=0.79), negative high-quality comment index (r=0.77), and online violence. The age of Internet users (r =-0.61), positive opinion leader impact index, positive high-quality comment index are negatively correlated with online violence.The negative degree of the incident, opinion leaders, high-quality comments, and age are the influencing factors of online violence.
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