Dynamics of Advice Network and Knowledge Contribution: A Longitudinal Social Network Analysis

Abstract

Online communities have become an increasingly popular channel for social interaction, enabling knowledge and opinion sharing across a board range of topics and contexts. Their viability and sustainability depends largely on contributions from community members in terms of time, resources, and knowledge. However, how individuals' knowledge contribution behavior changes over time and what network structural characteristics influence individuals' contribution behavior is not well understood. This study investigates "co-evolution" of social networks (i.e. advice network) and knowledge contribution behavior thorough a lens of social selection and social influence mechanism. This study are particularly interested in examining the dynamics of the advice network ties and the knowledge contribution behavior in the context of virtual financial communities in which people voluntarily participate to exchanges investing-related information. Unlike popular friendship-based online social networks, virtual financial communities in this study enables members to construct their own advice network by adding, maintaining, or terminating advice ties. Changes in network ties are referred to as social selection, while changes in individuals' behavior in response to the current network position are referred to as social influence. Dynamic network modeling is applied to investigate effects of social selection and influence separately and then examine the interplay between social selection and behavioral influence. Examination of such effects both separately and simultaneously requires a longitudinal data that capture dynamic changes in both the advice ties and the behavior under study.