Opinion Formation on Social Media Platform

44 Pages Posted: 27 Oct 2014

See all articles by Yingda Lu

Yingda Lu

Rensselaer Polytechnic Institute (RPI)

Junjie Wu

Beihang University (BUAA)

Yong Tan

University of Washington - Michael G. Foster School of Business

Date Written: October 25, 2014

Abstract

In this paper, we formulate a hierarchical Bayesian learning model to investigate the dynamics of individual opinion formation on a social media platform where individuals are exposed to two sources of social influence, preceding peer posts in a microblog thread and comments from the general public, which are often endogenously generated and thus correlated. The focus of this study is to separate these two distinct sources and measure their respective effects. We take the advantage of a unique natural experiment contained in the data from a leading microblogging website in China to help model identification. Further, we adapt the Consensus Markov Chain Monte Carlo algorithm, a parallel computing approach, to our Bayesian estimation procedure to effectively handle the big data in this study. We find that preceding peer posts in a microblog thread influence an individual to converge to the opinions of her peers. It is observed that more comments from the general public make an individual less certain about the topic discussed in the thread, whereas preceding microblogs from closely connected peers reinforce her opinion. Simulation studies are conducted to show that restricting number of comments in the early stage of a social media campaign helps to build a consumer base that is more certain about their opinions, and identifying more influential users with favorable opinions to participate early positively shifts the average opinion.

Keywords: opinion formation, social media, big data, Bayesian learning

Suggested Citation

Lu, Yingda and Wu, Junjie and Tan, Yong, Opinion Formation on Social Media Platform (October 25, 2014). Available at SSRN: https://ssrn.com/abstract=2514868 or http://dx.doi.org/10.2139/ssrn.2514868

Yingda Lu (Contact Author)

Rensselaer Polytechnic Institute (RPI) ( email )

Troy, NY 12180
United States

Junjie Wu

Beihang University (BUAA) ( email )

37 Xue Yuan Road
Beijing 100083
China

Yong Tan

University of Washington - Michael G. Foster School of Business ( email )

Box 353226
Seattle, WA 98195-3226
United States

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