基于多粒度粗糙集的微媒体错失焦虑分析研究

Research of FOMO in micro-media based on multigranularity rough set

随着信息技术的快速发展,多种短视频类交互平台赢得用户青睐,针对用户面对海量数据可能产生错失焦虑心理的问题,为了量化用户错失焦虑(Fear Of Missing Out,FOMO)的程度,利用多粒度决策粗糙集模型,借助期望确认理论,将通过李克特量表采集到的数据量化成离散数据,借助条件概率和粗糙代价矩阵计算出具体焦虑情况的评估值。同时将评估值与实际调查结果进行对比,得出该模型可以量化用户当前焦虑程度并挖掘潜在焦虑倾向的结论,为错失焦虑影响因素的研究和错失焦虑心理的发现与治疗提供更多的依据。

With the rapid development of information technology,a variety of short video interactive platforms are winning users’ favor. Faced with massive data,users are very likely to have missed anxiety.In order to quantify the degree of missed anxiety(Fear Of Missing Out,FOMO),this paper quantifies the data collected by Likert scale into the data that can be processed by Rough Set based on the expectation confirmation theory and the multigranularity decision rough set. Conditional probability and cost matrix are used to calculate the evaluation value of a specific state of anxiety. At the same time,the evaluation value is compared with the actual survey results,and the conclusion is drawn that the model can quantify the current anxiety degree of users and explore the potential anxiety tendency. The conclusion of this paper will provide more evidence for the study of the influencing factors of FOMO and the discovery and treatment of FOMO.