Mining Facebook Activity to Discover Social Ties: Towards a Social-Sensitive Ecosystem

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Abstract

Clearly there is a growing omnipresence of social networking sites in particular and social services in general. Given this translation of social relations into the cloud, services are facing the problem of deciding, for every user, what are the really relevant links to provide a social-sensitive response. To this end, this paper provides a model for calculating the strength of social ties based on interaction information collected from various social APIs in the cloud. We apply this general model over users' data gathered from the Facebook API and preprocess this data to extract representative stereotypes. Apart from evaluating the tie strength according to the observed behaviour of the stereotyped users, we describe the utility of our model to deploy a social-sensitive ecosystem. We envision a ecosystem where services functionality is enhanced by the knowledge about users' social ties; services in the scope of social marketing, attention management and contacts management are included to clarify our vision. © Springer International Publishing Switzerland 2013.

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APA

Servia-Rodríguez, S., Díaz-Redondo, R. P., Fernández-Vilas, A., & Pazos-Arias, J. J. (2013). Mining Facebook Activity to Discover Social Ties: Towards a Social-Sensitive Ecosystem. In Communications in Computer and Information Science (Vol. 367 CCIS, pp. 71–85). Springer Verlag. https://doi.org/10.1007/978-3-319-04519-1_5

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