EAN: 9783030002282

SPRINGERBRIEFS IN COMPUTER SCIENCE MINING LUR...

This SpringerBrief brings order to the wealth of research studies that contribute to shape our
understanding of on-line social networks (OSNs) lurking phenomena. This brief also drives the
development of computational approaches that can be effectively applied to answer questions
related to lurking behaviors  as well as to the engagement of lurkers in OSNs. All large-scale
online social networks (OSNs) are characterized by a participation inequality principle  i.e. 
the crowd of an OSN does not actively contribute  rather it takes on a silent role. Silent
users are also referred to as lurkers  since they gain benefit from others' information without
significantly giving back to the community. Nevertheless  lurkers acquire knowledge from the
OSN  therefore a major goal is to encourage them to more actively participate. Lurking behavior
analysis has been long studied in social science and human-computer interaction fields  but it
has also matured over the last few years in social network analysis and mining. While the main
target audience corresponds to computer  network  and web data scientists  this brief might
also help increase the visibility of the topic by bridging different closely related research
fields. Practitioners  researchers and students interested in social networks  web search  data
mining  computational social science and human-computer interaction will also find this brief
useful research material .

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