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作 者:李长荣 纪雪梅[1] 郭凤仪 Li Changrong;Ji Xuemei;Guo Fengyi(Institute of Information Management,Shandong University of Technology,Zibo 255049,China)
机构地区:[1]山东理工大学信息管理研究院,山东淄博255049
出 处:《现代情报》2021年第7期85-93,102,共10页Journal of Modern Information
基 金:国家社会科学基金青年项目“突发事件情境下社交媒体用户情感表达行为的特征与驱动因素研究”(项目编号:16CTQ027)。
摘 要:[目的/意义]探索突发公共卫生事件情境下在线健康社区用户的情感表达特征,对在线健康社区平台创新服务水平,舆情监管部门提升舆情管理水平具有重要作用。[方法/过程]本文以新冠肺炎疫情事件为情境,首先,采用基于情感词典的方法对在线健康社区用户的发帖和回帖文本进行情感分析和计算;然后,采用社会网络分析法识别事件传播过程中的高影响力用户、高活跃度用户和关键中间用户;最后,采用方差分析法研究关键用户的情感表达类别特征,采用相关分析法研究关键用户的情感表达强度特征。[结果/结论]研究发现,在线健康社区用户对新冠肺炎疫情事件主要呈现“好”和“恶”两种情感;“怒”情感的影响力均值、中间中心度均值最高;用户的影响力与中间中心度之间存在高度相关关系;用户的活跃度与情感表达强度之间存在正相关关系。相关部门需要及时疏导用户负面情感,安抚情感表达激烈的用户,有效控制舆情蔓延。[Purpose/Significance]Exploring the emotional expression characteristics of online health community users plays an important part in innovating the service level of online health community platforms,and improving the public opinion management level of public opinion supervision departments.[Method/Process]The article took the COVID-19 as the situation.First of all,the sentiment dictionary was used to analyze the emotion of online health community users'posts and replies.Then,the social network analysis was used to analyze the high-impact users,highly active users and key intermediary users.Finally,analysis of variance was used to analyze the emotional type characteristics of key users in online health community,correlation analysis was used to analyze the emotional intensity of key users in online health community.[Result/Conclusion]In the face of the COVID-19,online health community users mainly expressed two emotions:good and evil.“Anger”had the highest average influence and average betweeness centrality.There was a high correlation between influence and centrality.There was a positive correlation between activity and emotional intensity.Therefore,relevant departments need to promptly disseminate users'negative emotions,appease users with intense emotional expressions,and effectively control the spread of public opinion.
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