City Research Online

Abstract

This study explores the role of online engagement, homophily and social influence in explaining traffic and news consumption by social network users at an external news website. The authors jointly model visits and page views for a panel of users who registered with the news site using their Facebook accounts. In their model, the authors account for homophily using a latent space approach, and account for endogeneity, heterogeneity, and unobservable correlates. The results show that measures of an individual’s activity on Facebook are positively associated with that individual’s actions at the news site. In addition, knowing what a user’s Facebook friends do at the content website provides insights into a focal user’s behavior at that website, as visitors with friends who visit external news sites are more likely to visit the news website studied. In addition, news consumption (not just visits) also depends on friend’s actions but such an impact varies with the individual’s underlying browsing mode. We highlight the importance of social influence in news consumption and further show that homophily bias in news consumption is similar to prior research in other categories. Our study also highlights that visitors’ past browsing patterns are important predictors of future content consumption, although social network information significantly improves prediction beyond the effect of such more traditional behavioral metrics. Finally, we find that Managers can use readily available data for both prediction and targeting.

Publication Type:	Article
Additional Information:	© 2017, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
Publisher Keywords:	Online Social Networks, News, Social Influence, Homophily, Latent Space Approach
Subjects:	H Social Sciences > HM Sociology Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments:	Bayes Business School > Management
SWORD Depositor:	Symplectic Administrator

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