Paper Info
Title
Understanding lurking behaviors in social networks across time
Abstract
Mining the silent members, also called lurkers, of an online community has been recognized as an important problem that accompanies the extensive use of social networks. Existing solutions to the ranking of lurkers can aid understanding the lurking behaviors in social networks, however they ignore any information concerning the time dimension. In this work we push forward research in lurker mining by providing an analysis of temporal aspects that aims to unveil the behavior of lurkers and their interrelations with other users. Our analysis builds upon four research questions, which encompass relations between lurkers and inactive users, relations between lurkers and active users, the responsiveness behavior of lurkers, and the evolution of lurking trends across time. Evaluation has been conducted on Flickr, FriendFeed and Instagram networks.
Year
DOI
Venue
2014
10.1109/ASONAM.2014.6921559
ASONAM '14: Advances in Social Networks Analysis and Mining 2014 Beijing China August, 2014
Keywords
Field
DocType
data mining,social networking (online),Flickr,FriendFeed,Instagram networks,lurker mining,lurking behaviors,online community,social networks,Flickr,Friend-Feed,Instagram,LurkerRank,lurking analysis
World Wide Web,Online community,Social network,Ranking,Computer science,Encyclopedia,Multiple time dimensions,Market research,The Internet,Lurker
Conference
ISBN
Citations 
PageRank 
978-1-4799-5876-4
3
0.38
References 
Authors
12
2
Name
Order
Citations
PageRank
Andrea Tagarelli147552.29
Roberto Interdonato27012.42