TY  - BOOK
AU  - Tagarelli,Andrea
AU  - Interdonato,Roberto
ED  - SpringerLink (Online service)
TI  - Mining Lurkers in Online Social Networks: Principles, Models, and Computational Methods 
T2  - SpringerBriefs in Computer Science,
SN  - 9783030002299
AV  - QA75.5-76.95 
U1  - 005.7 23
PY  - 2018///
CY  - Cham
PB  - Springer International Publishing, Imprint: Springer
KW  - Computers
KW  - Application software
KW  - Computer communication systems
KW  - Information Systems and Communication Service
KW  - Computer Appl. in Social and Behavioral Sciences
KW  - Computer Communication Networks
N1  - Acceso multiusuario
N2  - 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 .
UR  - http://148.231.10.114:2048/login?url=https://doi.org/10.1007/978-3-030-00229-9
ER  -