Abstract

Clustered structure of social networks provides the chances of repeated exposures to carriers with similar information. It is commonly believed that the impact of repeated exposures on the spreading of information is nontrivial. Does this effect increase the probability that an individual forwards a message in social networks? If so, to what extent does this effect influence people’s decisions on whether or not to spread information? Based on a large-scale microblogging data set, which logs the message spreading processes and users’ forwarding activities, we conduct a data-driven analysis to explore the answer to the above questions. The results show that an overwhelming majority of message samples are more probable to be forwarded under repeated exposures, compared to those under only a single exposure. For those message samples that cover various topics, we observe a relatively fixed, topic-independent multiplier of the willingness of spreading when repeated exposures occur, regardless of the differences in network structure. We believe that this finding reflects average people’s intrinsic psychological gain under repeated stimuli. Hence, it makes sense that the gain is associated with personal response behavior, rather than network structure. Moreover, we find that the gain is robust against the change of message popularity. This finding supports that there exists a relatively fixed gain brought by repeated exposures. Based on the above findings, we propose a parsimonious model to predict the saturated numbers of forwarding activities of messages. Our work could contribute to better understandings of behavioral psychology and social media analytics.

Highlights

  • With advances in information and communication technology, more and more people around the world are getting involved in online social networks

  • The patterns are similar across seven online domains. This one-degree network structure allows us to reasonably reduce the scope of the spreading of information considered in our research

  • We show the numbers of networks, the identities of root users, the numbers of nodes in the corresponding direct follower networks and the numbers of message samples we collect for each root user, respectively. doi:10.1371/journal.pone.0140556.t005

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Summary

Introduction

With advances in information and communication technology, more and more people around the world are getting involved in online social networks. In using these services, a simple click will forward a message to another group of people and this simple action significantly facilitates the spreading of information [1, 2]. Information spreading in social networks has long been an active research area. What factors make an individual spread a message by clicking the forward button is still an open question [3,4,5]. Apart from the intrinsic interest orientation [6], the daily routine schedule and the information processing ability of oneself [7, 8], could other.

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