A Study On The Influencing Factors Of Wechat Users' Engagement Behavior In Social Recommendation

With the rapid development of Internet technology,a large number of information content is flooding in social platforms.The amount of miscellaneous information not only makes high-quality content difficult to stand out,but also brings troubles to the choice and acceptance of users.Therefore,social platforms have been exploring the content distribution path suitable for their own product model.With the continuous change of social habits of network users,more and more users are used to express opinions,share information and access resources in social platforms.Social recommendation mode has become a hot topic in the industry.This study takes WeChat's new content distribution function "friend watching" as an example to explore the influencing factors of WeChat user participation behavior in social recommendation.Based on relevant research at home and abroad,combined with in-depth interviews with 12 interviewees,the theoretical model of this study is constructed under the guidance of technology acceptance and use integration model(UTAUT)and social exchange theory.506 questionnaires were distributed online,of which 452 were effective and the effective rate was 89.3%.After recovery,spss20.0and amos24.0 were used to test the hypothesis.The research shows that the four independent variables of source platform reliability,relationship strength,timeliness of recommendation content and quantification degree of recommendation content all have a positive impact on wechat users' participation behavior,and privacy concerns have a negative impact on participation behavior.Perceived trust and perceived value play a significant mediating role in the four independent variables of source platform reliability,timeliness of recommended content,quantification degree of recommended content,and privacy concern in the path of dependent user participation.According to the results of the study,this study discusses from five perspectives:product,communication,content,technology and ethics.It is suggested that we should enrich the internal content sources,show the functional entry,and strengthen the recommendation flow of social + content.At the same time,there are some ethical risks in social recommendation,users' implicit preferences are amplified,and complex social psychology dilutes the authenticity of social relations.Users' habits need to be cultivated to make social recommendation and big data recommendation coexist and promote the benign dissemination of high-quality content.