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Information Exchange and Multiple Peer Groups: A Natural Experiment in an Online Community

Date
Date
Tuesday 1 March 2022, 14:00-15:00
Speaker:
Dr Zhen Zhu, University of Kent

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Abstract

We utilise a quasi-experimental setup to identify causal effects of having additional peer groups on information exchange in a large online maternity community. The information exchange is a key performance indicator for the community as well as a public good among users. Pregnant users join default peer groups based on estimated due date (EDD). Natural uncertainties of EDD can lead to multiple peer groups. Using EDD as an instrumental variable, we find that additional peer group(s) reduces information exchange in both the default peer group and total peer groups. Having more advanced groups mitigates the reduction, likely due to information spillovers.

The Speaker

Dr Zhen Zhu is a Senior Lecturer in Big Data Analytics at Kent Business School. Previously he worked at the University of Greenwich, Stockholm School of Economics, and IMT School for Advanced Studies Lucca. Zhen’s research fields are data science, network science, and business analytics. He is particularly interested in uncovering community structure and dynamics in social and economic networks.