Overview
- First book to discuss the lurking behavior phenomenon in online social networks under both social science and computational perspectives
- It provides detailed descriptions of computational approaches that enable understanding and mining of lurking behaviors, including centrality and ranking, influence propagation and maximization for user engagement, cross-platform analysis methods, and evolutionary games
- It paves the way for next-generation models and techniques that can cope with a large, previously unexplored set of related problems and applications in social science, network science, and other information science related fields
Part of the book series: SpringerBriefs in Computer Science (BRIEFSCOMPUTER)
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Table of contents (9 chapters)
Keywords
- lurking behavior analysis
- centrality
- influence propagation
- lurkers
- silent users
- passive users
- vicarious learning
- user engagement
- centrality
- ranking
- online social networks
- information diffusion
- influence propagation
- influence maximization
- evolutionary game theory
- time-evolving network model
- multiplex network model
- network science
- trust networks
- graph mining
About this book
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 .
Authors and Affiliations
Bibliographic Information
Book Title: Mining Lurkers in Online Social Networks
Book Subtitle: Principles, Models, and Computational Methods
Authors: Andrea Tagarelli, Roberto Interdonato
Series Title: SpringerBriefs in Computer Science
DOI: https://doi.org/10.1007/978-3-030-00229-9
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: The Author(s), under exclusive license to Springer Nature Switzerland AG 2018
Softcover ISBN: 978-3-030-00228-2Published: 19 November 2018
eBook ISBN: 978-3-030-00229-9Published: 09 November 2018
Series ISSN: 2191-5768
Series E-ISSN: 2191-5776
Edition Number: 1
Number of Pages: VI, 93
Number of Illustrations: 1 b/w illustrations, 9 illustrations in colour
Topics: Information Systems and Communication Service, Computer Appl. in Social and Behavioral Sciences, Computer Communication Networks