Mining Lurkers in Online Social Networks

Andrea Tagarelli, Roberto Interdonato

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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.

Subjek

APPLICATION SOFTWARE
 

Katalog

Mining Lurkers in Online Social Networks
978-3-030-00228-2
95p.: pdf file.; 3 MB
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Pengarang

Andrea Tagarelli, Roberto Interdonato
Perorangan
 
 

Penerbit

Springer
New York
2018

Koleksi

Kompetensi

 

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