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.
Work funded by the Ministerio de Educación y Ciencia (Gobierno de España) research project TIN2010-20797 (partly financed with FEDER funds), and by the Consellería de Educación e Ordenación Universitaria (Xunta de Galicia) incentives file CN 2011/023 (partly financed with FEDER funds).
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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: Ivanov, I.I., van Sinderen, M., Leymann, F., Shan, T. (eds) Cloud Computing and Services Science. CLOSER 2012. Communications in Computer and Information Science, vol 367. Springer, Cham. https://doi.org/10.1007/978-3-319-04519-1_5
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DOI: https://doi.org/10.1007/978-3-319-04519-1_5
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