Paper Info
Title
Community-based delurking in social networks.
Abstract
The participation inequality phenomenon in online social networks between the niche of super contributors and the crowd of silent users, a.k.a. lurkers, has been witnessed in many domains. Within this view, understanding the role that lurkers take in the network is essential to develop innovative strategies to delurk them, i.e., to engage such users into a more active participation in the social network life. In this work, we leverage the boundary spanning theory to enhance our understanding of lurking behaviors, with the goal of improving the task of delurking in social networks. Assuming the availability of a global community structure, we first analyze how lurkers are related to users that take the role of bridges between different communities, unveiling insights into the bridging nature of lurkers and their tendency to acquire information from outside their own community. Moreover, based on a targeted influence maximization method designed for delurking, we also analyze how the learning of users that can best engage lurkers is related to the community structure. We found that the best users to engage lurkers belonging to any particular community, are more often found outside that community, and more specifically they are located in the adjacent communities.
Year
DOI
Venue
2016
10.5555/3192424.3192472
ASONAM '16: Advances in Social Networks Analysis and Mining 2016 Davis California August, 2016
Keywords
Field
DocType
silent users, lurking, targeted influence maximization, community detection, LurkerRank, boundary spanning theory, participation and engagement in social networks
Boundary spanning,Community structure,Social network,Computer science,Bridging (networking),Knowledge management,Inequality,Phenomenon
Conference
ISBN
Citations 
PageRank 
978-1-5090-2846-7
1
0.36
References 
Authors
21
3
Name
Order
Citations
PageRank
Roberto Interdonato17012.42
Chiara Pulice2329.45
Andrea Tagarelli347552.29