Mining Lurkers in Online Social Networks

Principles, Models, and Computational Methods

Roberto Interdonato, Andrea Tagarelli

PDF
ca. 58,84
Amazon iTunes Thalia.de Weltbild.de Hugendubel Bücher.de ebook.de kobo Osiander Google Books Barnes&Noble bol.com Legimi
* Affiliatelinks/Werbelinks
Hinweis: Affiliatelinks/Werbelinks
Links auf reinlesen.de sind sogenannte Affiliate-Links. Wenn du auf so einen Affiliate-Link klickst und über diesen Link einkaufst, bekommt reinlesen.de von dem betreffenden Online-Shop oder Anbieter eine Provision. Für dich verändert sich der Preis nicht.

Springer International Publishing img Link Publisher

Naturwissenschaften, Medizin, Informatik, Technik / Informatik

Beschreibung

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 . 


Weitere Titel von diesem Autor
Weitere Titel zum gleichen Preis
Cover Large Group Decision Making
Iván Palomares Carrascosa
Cover Cybersecurity in Germany
Martin Schallbruch
Cover Big Digital Forensic Data
Kim-Kwang Raymond Choo
Cover Belief Change
Sven Ove Hansson

Kundenbewertungen

Schlagwörter

user engagement, vicarious learning, influence maximization, information diffusion, passive users, trust networks, time-evolving network model, multiplex network model, ranking, lurking behavior analysis, influence propagation, online social networks, silent users, evolutionary game theory, graph mining, lurkers, centrality, network science