Research On The Influence Of Social Media Functions On Users' Response To The Spread Of Fake News

With the rapid development of Internet technology and mobile intelligent devices,social media platforms have become an important medium for the public to obtain information,spread information and share opinions.A large number of fake news have spreaded rapidly as a leading force,seriously affecting social stability and public life.The functions of content editing and interactive sharing provided by social media platform greatly deepen the breadth and depth of information dissemination,and provide a more convenient way for public participation.The news dissemination mechanism based on social media platform has been transformed into a social behavior based on group interaction.Therefore,it is of great significance to clarify the guiding and auxiliary functions of social media platform for users to cope with fake news dissemination,so as to study the systematic mode of using its functions to improve the effective suppression of fake news dissemination.Firstly,sorting out the existing literature to understand the main types and influencing factors of users' information behaviors.Meanwhile,the main methods and strategies for identifying and responding to fake news on social media platforms are summarized.Then,based on the grounded theory,the functional types of social media platforms and users' functional usage habits were theoretically constructed,and relevant hypotheses were verified by PLS path regression.To study the main functions of social media platforms' influence on users' willingness to verify the authenticity of news,according to the research conclusion of the previous chapter,this paper discusses the main functions used by users to judge the authenticity of information: elaborate elaboration,group interaction presentation and broadcast level functions affect users' willingness to verify the authenticity of news,and collects relevant data by designing control variable experiments for analysis.Then,according to the research conclusion of the previous chapter,it is pointed out that the improvement of the quality of group interaction can help users better judge the authenticity of news,thus establishing the evolutionary game model between social media platform and users,and using MATLAB to analysis the effect of audit and incentive mechanism.Then,according to the literature research,empirical research and quantitative analysis on the function of social media platform in users' response to fake news,a systematic conceptual model and incentive strategies were proposed to encourage users to participate in fake news identification and response by using crowdsourcing model.Finally,according to the main conclusion,this paper proposes relevant strategies to deal with fake news from three perspectives of simplifying the process of function use,improving function types and ensuring the safety of function use.The research shows that users who use social media for different motives have significant differences in their usage habits of functions.Some of these features plays an important role in the process of user's participation in response to the spread of fake news.Elaboration function in content evaluation,Group interaction presentation function in content aggregation and sequencing function will have a significant impact on the willingness of users to judge the authenticity of news,but due to some extent affected by the inhibition of group interaction quality is low;This problem can be well solved by improving the functions of social media platform audit and incentive mechanism.Meanwhile,it also proves once again the important role of function design and various mechanisms in dealing with the spread of fake news.Therefore,crowdsourcing mode can be systematically applied into it.