Influence Of Personalized Recommendation Mechanism On Internet Public Opinion

With the coming of the digital age,the platform of public opinion gradually turns to the online terminal,such as Weibo,We Chat and the news client,etc.In order to meet the information preference of the public,the network platform makes use of personalized recommendation mechanism to select information in the information communication stage.But the personalized recommendation mechanism of the network platform will probably affect the users’ public opinion information acquisition,strengthen the "irrationality" of the public opinion subject,and the social risk brought about by the spread of the irrationality and even "anti-rationality" of the network public opinion is increasing,mainly manifested in the polarization of the network public opinion and the "general emotion" of the public.So whether can personalized recommendation mechanism affect network public opinion and its trend? This research attempts to observe the relationship between the personalized recommendation mechanism of social network and the evolution of online public opinion through the actor model based on Weibo platform.Based on the above network social phenomenon and the question,the paper has launched the following work:(1)Considering the complexity of the research topic on online public opinions,firstly,the relevant literature on personalized recommendation mechanism,online public opinions and trial behaviors on microblog shall be systematically sorted out,from which empirical evidence,theoretical models and research methods available for reference shall be extracted.Referring to the theory of "Emotional infection" in social psychology and the theory of "Agent-based Modeling" in social science,this paper puts forward the simulation experiment of social network public opinion communication based on NetLogo software,and makes in-depth research through the research mode of "data support — simulation ".(2)Secondly,we put forward the theoretical model of this study,and sort out the relevant empirical evidence,based on which we propose the main research hypothesis: personalized recommendation mechanism has an impact on online public opinion.The proposed model is presented in the form of simulation experiments.Firstly,the objects and their attributes are defined.Secondly,the interaction rules of each simulator are designed.Through crawling the trial behavior data of Weibo,provide data support for the simulation experiment,determine the relevant simulation situation and measurement objectives.(3)Based on the given situation,use the NetLogo tool to write relevant code,construct specific visual model and manipulate variables for many times to simulate,and finally derive the simulation results.The influence of personalized recommendation mechanism on network public opinion is determined by simulation experiment,and the simulation results also show the influence of other factors on network public opinion.Through the above analysis and simulation,the results show that:1)personalized recommendation mechanism plays a catalytic role in the generation and development of online public opinion,magnifies individual opinion movement,and accelerates the evolution of group emotions.2)The mainstream media shall be responsible for the dissemination of online public opinions,and the credibility of the mainstream media directly affects the dissemination of group opinions and emotions.3)There is no direct correlation between the intensity of government intervention and the final evolution of online public opinion,and a new path may need to be explored for the governance of online public opinion.4)The distribution of groups and groups of individuals has affected the spread of online public opinions.In today’s increasingly "circle" and "group opposition",individualization may weaken the diversity that new media should present,and make people more polarized,stubborn and vulnerable to the influence of social publicity.This,in turn,would make people more susceptible to polarizing information,causing rumors to proliferate and ultimately eroding interpersonal trust.Personalized algorithms in social platform tend to simplify individuals and society into a subject without contradiction and complexity,and people lose their "exploratory right of information".The homogeneous and emotional information push after filtering by personalized recommendation mechanism has already led to the distortion of network public opinion,so people should be vigilant.