Conceptualizing a Framework for Social Media Data Sharing

Abstract

Information sharing is one of the most important trends on social media nowadays, but detailed research on what can encourage it is still in the early stages. This exploratory work examines three categories of antecedents to data sharing which have come up in the literature: sharing benefits, social influences, and trust / risk issues, particularly associated with reliable vs. false information. A very simple model of direct impacts shows that information value, voluntary sharing, and false data risk significantly impact data sharing, but the other antecedents do not. The dependent variable was explicitly about sharing factual data, and these results suggest some feeling of social obligation to voluntarily share, particularly when respondents are well aware of the prevalence of misinformation. Social media providers together with organizations can contribute to efforts at preventing disinformation to enhance their credibility with social media users or customers.

Keywords: Social media data sharing, Information value, Social influences, Trust, Perceived risk