Towards a Characterization of Egocentric Networks in Online Social Networks

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• 作者：Valerio Arnaboldi (19)
  Andrea Passarella (19)
  Maurizio Tesconi (19)
  Davide Gazzè (19)
  
• 关键词：Online Social Networks ; Measurements ; Ego networks
• 刊名：Lecture Notes in Computer Science
• 出版年：2011
• 出版时间：2011
• 年：2011
• 卷：7046
• 期：1
• 页码：534-543
• 全文大小：191KB
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• 作者单位：Valerio Arnaboldi (19)
  Andrea Passarella (19)
  Maurizio Tesconi (19)
  Davide Gazzè (19)
  
  19. IIT-CNR, Via G. Moruzzi 1, 56124, Pisa, Italy
  

文摘

Online Social Networks (OSNs) are more and more establishing as one of the key means to create and enforce social relationships between individuals. While substantial results have been obtained in the anthropology literature describing the properties of human social networks (built “outside-the OSN world), a clear understanding of the properties of social networks built using OSNs is still to be achieved. In this paper we provide a contribution towards this goal, by starting characterizing ego networks formed inside Facebook through the analysis of data obtained from a measurement campaign. Ego networks capture all the social relationships (links) between an ego and all the other people with whom the ego has a social tie. Ego networks are one of the key social structure that have been studied in the anthropology literature, and is thus a reference objective for our work. In this paper we analyze a number of quantitative variables that can be collected on Facebook, which can be used to describe the properties of the social links in ego networks. We also analyze the correlation between these variables and the strength of the social ties, as explicitly ranked by the monitored Facebook users. Our results show that there is an interesting similarity between the properties observed by anthropologists in human social networks, and those of Facebook social networks. Moreover, we found a noticeable correlation between most of the measured variables and the tie strengths, suggesting the possibility of automatically inferring the latter from measurable Facebook variables.