Network Overlap and Network Blurring in Online Social Networks

Nan (Andy) Zhang, Chong (Alex) Wang


Online communities and the online social networks embedded become a prominent medium for social interactions. The success of social media depends on users’ willingness to continue investing their time and efforts in the absence of economic rewards, making psychological attachment critical to online communities. While prior studies identify that members do develop psychological commitment to online communities, why and how the commitment arises remain underexplored. This study focuses on the relationship between network overlap, a common feature of online social networks, and affective commitment to an online community. Drawing on the commitment theory and social network boundary theory, we argue that the effect of online/offline network overlap is partially mediated by network boundary blurring. Meanwhile, contrary to industrial wisdom, the direct impact of network overlap on commitment is negative. Our empirical study supports our proposal. It indicates that it is critical to help users integrate online and offline social networks. Without success social network boundary blurring, high level of network overlap may backfire.


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Paper Citation

in Harvard Style

Zhang N. and Wang C. (2016). Network Overlap and Network Blurring in Online Social Networks . In Proceedings of the 18th International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-758-187-8, pages 327-332. DOI: 10.5220/0005911203270332

in Bibtex Style

author={Nan (Andy) Zhang and Chong (Alex) Wang},
title={Network Overlap and Network Blurring in Online Social Networks},
booktitle={Proceedings of the 18th International Conference on Enterprise Information Systems - Volume 2: ICEIS,},

in EndNote Style

JO - Proceedings of the 18th International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - Network Overlap and Network Blurring in Online Social Networks
SN - 978-989-758-187-8
AU - Zhang N.
AU - Wang C.
PY - 2016
SP - 327
EP - 332
DO - 10.5220/0005911203270332