摘要
以python爬取的数据为基础,通过LDA主题模型和机器学习得到用户倦怠的隐藏主题,使用“S-O-R”理论对其分析,得到用户产生社交媒体倦怠的8个重要性主题,发现影响微博用户倦怠的因素可分为媒体因素和个体因素。其中媒体因素是产生倦怠的主要原因,包括平台服务、媒体环境、信息质量及社交压力;个体因素分为上进意愿和个人敏感度,通过词云分析进一步验证主题分析结果的合理性。
Based on the data crawled by python,this paper uses the LDA topic model and the machine learning to obtain the hidden topics of user s ennui.The“S-O-R”theory is used to analyze the 8 important topics of user s ennui to the social media.It is found that the factors affecting user s ennui can be divided into the media and the individual factors.The media factors are the main causes of their ennui,including the platform services,the media environment,the information quality and the social pressure;while the individual factors can be divided into the motivation and the personal sensitivity.Then the rationality of the topic analysis results is further verified by the word cloud analysis.
作者
李庆真
唐焘
LI Qing-zhen;TANG Tao(School of Law,Hangzhou Dianzi University,Hangzhou Zhejiang 310018,China)
基金
浙江省“之江青年社科学者”专项项目(16ZJQN008YB)。
