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基于移动短视频特质对用户UGC行为影响之假设

Proposing hypotheses about the impact of mobile short video characteristics on user UGC behavior
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摘要 由于智能手机的普及,越来越多的人通过移动端APP观看短视频,并参与短视频的制作和分享。现从移动短视频平台的角度出发,以SOR理论为基础,把移动短视频特质视为自变量,情感依恋做中介变量,用户的UGC行为作为因变量构建研究模型,研究三者的关系及作用机理。通过问卷星网站设计问题并收集数据,使用SPSS26.0、AMOS26.0对回收的问卷数据进行处理分析,并构建结构方程模型最终得出结果。分析结果显示:移动短视频APP的娱乐性、个性化和社交化均显著影响用户的情感依恋;娱乐性、社交性、个性化通过情感依恋显著影响移动短视频UGC行为。 Due to the popularity of smart phones,more and more people watch short videos through mobile apps,and participate in the production and sharing of short videos.Starting from the perspective of mobile short video platform and based on SOR theory,this study constructed a research model with the characteristics of mobile short video as the independent variable,emotional attachment as the intermediary variable,and user UGC behavior as the dependent variable to study the relationship and mechanism of the three.Through the questionnaire star website design problems and data collection,using SPSS26.0,AMOS26.0 to process and analyze the recovered questionnaire data,and build the structural equation model to obtain the final results.The results show that:entertainment,personalization and socialization of mobile short video apps significantly affect users'emotional attachment;Entertainment,sociability and individuation significantly affect UGC behavior of mobile short video through emotional attachment.
作者 杨春梅 徐西帅 Yang Chunmei;Xu Xishuai(School of Economics and Management,Qiqihar University,Qiqihar Heilongjiang 161000)
出处 《北方经贸》 2023年第8期53-55,117,共4页 Northern Economy and Trade
基金 国家自然科学基金项目(71803095) 黑龙江省哲学社会科学研究规划年度项目(19JYB025)。
关键词 SOR理论 移动短视频 情感依恋 UGC行为 中介变量 SOR theory Mobile short video Emotional attachment UGC behavior Intervening variable
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  • 1Cheng, X. , Dale, C. and Liu, J. Understanding the Characteristics of Internet short video sharing : YouTube as a case study, http://www, webdialogues, net,2009 -04 -23.
  • 2Alexa. http://www, alexa, com,2009 -04 - 15.
  • 3视讯网.http://www.cnvideonews.com/node/1150.2009-04-15.
  • 4Meeyoung Cha, Haewoon Kwak, Pablo Rodriguez, Yong - Yeol Ahn and Sue Moon. I tube, you tube, everybody tubes:analyzing the world's largest user generated content video system. In IMC07 :Proceedings of the 7th ACM SIG- COMM conference on Internet measurement, San Diego, California, USA ,2007. ACM : 1 - 14.
  • 5YouTube. http://www, youtube, com,2009 -03 -15.
  • 6Gijs Kruitbosch, Frank Nack. Broadcast Yourself on You- Tube - Really?. In IMC08 : Proceeding of the 3rd ACM international workshop on Human -centered computing,Vancouver, British Columbia, Canada,2008. ACM :7 - 10.
  • 7Mohit Saxena, Umang Sharan, and Sonia Fahmy. Analyzing Video Services in Web2.0 : A Global Perspective. Proceedings of the 18th International Workshop on Network and Operating Systems Support for Digital Audio and Video, Braunschweig, Germany,2008. ACM :39 - 44.
  • 8Fabricio Benevenuto, Fermando Duarte etc. Understanding Video Interactions in YouTube. In IMC 08 : Proceeding of the 16th ACM international conference on Multimedia, Vancouver, British Columbia, Canada,2008. ACM:761 - 764.
  • 9Peng Xiao-chuan,Mao Xiao-dan.Social Network analysis of BBScommunity characteristics[J].Youth Studies,2004,4:39-44.
  • 10Albert R,Barabasi A L.Statistical Mechanics of Complex Net-works[J].Rev.Mod.Phys.,2002,74:47-97.

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