This study intended to explore the mediating effect of peer recommendation and algorithm recommendations to illustrate the impact of social media user's repeated exposure on news buzz.An analysis was conducted on total 584 people collected through a convenience sampling nationwide.Data were analyzed using PROCESS macro, a bootstrapping method that is known to be a more accurate mediation method than the Baron and Kenny and Sobel test.As the result of analysis, first, social media users' repeated exposure to news had a significant positive effect on news buzz.Second, social media users' peer recommendations for news were found to mediate the relationship between repeated exposure and news buzz.Third, social media users' algorithmic recommendations were found to mediate the relationship between repeated exposure and news buzz.Fourth, the double mediating effect of peer recommendation and algorithm recommendation was confirmed in the impact of social media users' repeated exposure and news buzz.Based on the results of this study, peer recommendation may become a standard for news evaluation in a network environment between social media users.It was found that algorithmic recommendation based on data from media consumption records can serve as a standard for identifying general social support trends.In the process of processing news information on social media, repeated exposure and social influence became major factors in news acceptance, making it possible to predict the negativity of the echo chamber phenomenon of public opinion.
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Mikyung Kim (2024) studied this question.
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