间歇性中辍行为特征的探索性研究
2021-01-15李君君王金歌曹园园
李君君 王金歌 曹园园



收稿日期:2020-07-02
基金项目:国家社会科学基金青年项目“老年群体社交网络信息服务质量评价与体验优化研究”(项目编号:17CTQ027)。
作者简介:李君君(1980-),女,副教授,博士,研究方向:网络信息服务、用户行为。王金歌(1996-),女,硕士研究生,研究方向:用户行为研究。曹园园(1984-),女,讲师,博士,研究方向:电子商务。
摘 要:[目的/意义]移动社交网络用户的消极使用行为越来越普遍,间歇性中辍行为是其中非常典型的一类,对间歇性中辍行为特征与影响因素进行分析,有助于加强用户消极行为方面的研究,帮助企业有针对性地采取措施,完善运营机制并实现长久发展。[方法/过程]本文选择有远离微博意向的用户,采用网络爬虫的方式收集用户半年内发微博的时间与内容,基于登录时间间隔、中辍时间间隔与微博内容词云分析对用户的间歇性中辍行为特征与原因进行研究。[结果/结论]研究结果发现,微博的环境、内容与过度使用都会导致用户产生远离意向,其中活跃用户占大多数,然而在实际行为中,活跃用户采取远离行为的可能性更低,中辍时间间隔也更短,消极用户则相反,用户需求不同导致用户的行为意向与实际行为存在差异。
关键词:移动社交用户;间歇性中辍行为;社交网络消极行为;远离意向;时间间隔;词云分析;微博
DOI:10.3969/j.issn.1008-0821.2021.01.007
〔中图分类号〕G252.0 〔文献标识码〕A 〔文章编号〕1008-0821(2021)01-0060-07
Exploratory Study on the Behavioral Characteristics of
Intermittent Dropouts
——A Case Study of Weibo Data
Li Junjun Wang Jinge Cao Yuanyuan
(School of Management,Hangzhou Dianzi University,Hangzhou 310018,China)
Abstract:[Purpose/Significance]The negative use behavior of mobile social network users is becoming more and more common,among which intermittent dropout behavior is a very typical one.The analysis of the characteristics and influencing factors of intermittent dropout behavior is helpful to strengthen the research of users negative behavior,help enterprises to take targeted measures,improve the operation mechanism and realize long-term development.[Method/Process]This article selected users who have intentions to stay away from Weibo,using web crawlers to collect the time and content of users Weibo within six months.Based on the login time interval,dropout interval and word cloud analysis of Weibo content,the characteristics and reasons of users intermittent dropout behavior were studied.[Result/Conclusion]Weibos environment,content and overuse will all lead to users intention to stay away,among which active users account for the majority.However,in actual behavior,active users are less likely to take away behavior,and the dropout time interval is shorter,while negative users are opposite.Different needs of users lead to differences between users behavioral intentions and actual behaviors.
Key words:mobil social network users;intermittent dropout behavior;social network negative behavior;away from intention;time interval;word cloud analysis;Weibo
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