Exploring Influence Of Extraversion On Social Network Structure And Relationship

With the rapid development and popularization of online social networks,the research of user psychology based on social network and the analysis of precise marketing model have become the focus of interdisciplinary research.More and more scholars in academia will focus on the study of the impact of user psychology on the characteristics of social network, and further find the accurate recommendation and marketing model for different user groups.Therefore, this paper focuses on the impact of individual personality traits on the characteristics of social networks, and further consummates the related research. The main contents and achievements are as follows: 1 .The research on the social network of online should not ignore the psychological factors that affect the formation of its network characteristics.Firstly,we analysis the influence of personality traits on the structure and relationship of social networks, and constructs a research model of the effect of extraversion on social network characteristicsThis paper combs the relevant literature and research evolution path of the Big Five personality and social network analysis field, and sums up the model and method of the influence of the Big Five Personality on the social network characteristics, thus laying a solid foundation for the research of this paper. In this paper, the extraversion of the big five personality is taken as the independent variable to study the influence of the difference of individual extraversion on the size and frequency of the relationship between the dimensions of the network and the dimension of the relationship between the dimension variables of the self-centered network. Model, exploring the relationship between variables.Secondly,The influence of extraversion on the structure and relationship of social network is explored through empirical research,and the relationship between social network structure dimension and relationship dimension is verifiedAfter reviewing the previous studies on the relationship between the Big Five personality and social network characteristics, this study takes Sina Weibo as an example. In view of the relationship between extraversion to the characteristics of social network and the characteristics of social network,Assumptions, the innovative exploration of online social networks and user psychology, as well as social networks between different dimensions of the relationship between indicators. 232 questionnaires were collected and 211 valid questionnaires were retrieved by questionnaire and platform data capture. Statistical analysis, factor analysis, reliability validity analysis and regression analysis were performed on the collected data with SPSS23.0 and Smart PLS2.0.The results of data analysis show that: (1) Extroversion has a significant positive impact on the scale of social network and the relationship between social center and social network. Extraversion of high individual in the Sina microblogging is more likely to show the high rate of mutual powder,frequent interaction, social circle scale. (2) Social network structure indicators-network center positive influence social network relationship dimension index - interaction frequency. Individuals who are central to social networks are more likely to be trusted by others in the network, and others are more likely to interact with the individual.Thirdly, We analyze the impact of individual personality traits on the characteristics of social network, and further subdivide the user groups, and make accurate recommendation and social network marketing strategy recommendations for different user groupsOn the basis of the above conclusions, from the two purposes of enhancing the service value and commercial value of the enterprise, the paper puts forward the personalized recommendation information flow which is suitable for the user’s habits and focuses on the customer experience; from the angle of commercialization, To enhance the cooperation with other enterprises to provide valuable data to realize the realization of large data, maximize the use of enterprise-owned users, to create a business value chain, The value of data such as management recommendations.