A Study On The Transmission Mechanism Of Emotional Contagion Of Netizen’s In The Process Of Refuting Rumors

The emotional contagion of netizens is an important factor to accelerate the spread of rumors,and also a critical point to refute the effectiveness of rumors.This article divides netizens’emotions in the process of rumoring into three categories:negative,immune,and positive,and improves the calculation of the subject’s emotional value and transformation rules based on the existing emotional models.Combining Python and Netlogo tools to simulate the process of infection from netizens’individual emotions to group emotions during the process of rumor dissipation,we use this to simulate the process of contagion from netizens’individual emotions to group emotions during the process of rumours.In this paper,the model is simulated and analyzed by setting different parameters through four sets of experiments.Experiment 1 aims to analyze the distribution and dynamic changes of different types of emotional subjects in each time stage by iterating the contagion cycle of emotional subjects.In experiment 2,by controlling the values of w_r,b_r,a_s and v_s variables in R_sr the influence of different degrees of network intimacy on the competitive changes of emotional subjects and the process of transition state of emotional infected subjects were observed.Experiment 3 is to analyze the influence of v_s and a_s on the emotional value of netizens.Experiment 4 is a comparative study of the emotional value of netizens before and after refuting rumors,mainly to analyze the changes of the emotional value of rumors after a series of human intervention,that is,the pros and cons of the final refuting effect.The results show that:（1）the emotional change cycle and trend of Internet users have different manifestations in different periods,but the final distribution structure presents a relatively stable state;（2）the factors affecting the emotional change of Internet users mainly come from the objective and subjective levels.The objective level depends on the speed and credibility of rumor dispelling,and the subjective level depends on the degree of intimacy between Internet users.Both of them can promote the evolution process of emotional contagion.（3）the benign intervention of the authority to refute rumors can positively guide the rumor events on the Internet.The government media with higher credibility can timely release refutation information to minimize the spread of rumors and bring the emotional of netizens back to the normal level at an early date.（4）compared with before refuting rumors,people’s emotions generally change from negative emotions to positive or immune emotions after refuting rumors.Finally,this paper verified four groups of experiments one by one by combining with the actual network rumor refutation cases.Research suggestions:（1）for netizens’emotional contagion in the process of refuting rumors in the era of social media,the method of computational transmission can be used to mine fine-grained representational features and internal correlation logic from the real data,and observe and accurately depict the evolution process,characteristics and rules of netizens’emotional evolution in the process of refuting rumors in the time serialization;（2）focus on soothing the mentality of Internet users in the process of refuting rumors,especially the active users with strong negative emotions and great influence.Because of the frequency and intensity of their interactions with other users,the interpersonal network formed by them is easy to take on a rhythm,and eventually forms a large area of emotional infection and group polarization.（3）the active and positive intervention of the subjects of refuting rumors after resource integration can realize the maximum suppression of online rumors.For example,in the case of limited public resources and small or less serious scope of network rumor damage,reasonable resources should be used to dispel rumors to achieve satisfactory results based on the actual economic cost and budget considerations.