Followers are not enough: a multifaceted approach to community detection in online social networks.
PLoS One
; 10(8): e0134860, 2015.
Article
en En
| MEDLINE
| ID: mdl-26267868
ABSTRACT
In online social media networks, individuals often have hundreds or even thousands of connections, which link these users not only to friends, associates, and colleagues, but also to news outlets, celebrities, and organizations. In these complex social networks, a 'community' as studied in the social network literature, can have very different meaning depending on the property of the network under study. Taking into account the multifaceted nature of these networks, we claim that community detection in online social networks should also be multifaceted in order to capture all of the different and valuable viewpoints of 'community.' In this paper we focus on three types of communities beyond follower-based structural communities activity-based, topic-based, and interaction-based. We analyze a Twitter dataset using three different weightings of the structural network meant to highlight these three community types, and then infer the communities associated with these weightings. We show that interesting insights can be obtained about the complex community structure present in social networks by studying when and how these four community types give rise to similar as well as completely distinct community structure.
Texto completo:
1
Banco de datos:
MEDLINE
Asunto principal:
Internet
/
Amigos
/
Red Social
Tipo de estudio:
Diagnostic_studies
Límite:
Humans
Idioma:
En
Revista:
PLoS One
Asunto de la revista:
CIENCIA
/
MEDICINA
Año:
2015
Tipo del documento:
Article
País de afiliación:
Estados Unidos