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Understanding community patterns in large attributed social networks
Univ Bologna, I-40126 Bologna, Italy..
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
Univ Bologna, I-40126 Bologna, Italy..
2015 (English)In: Proceedings Of The 2015 IEEE/ACM International Conference On Advances In Social Networks Analysis And Mining (Asonam 2015), 2015, 1503-1508 p.Conference paper (Refereed)Text
Abstract [en]

There is an inherent presence of communities in online social networks. These communities can be defined based on i) link structure or ii) the attributes of individuals. Attributes can indicate as interests in specific topics, like science-fiction books or romantic movies, or more in general their explicit affiliation to a group inside the network. In this paper, we analyze community structures as defined by how people are associated to third concepts like attributes. To understand the community patterns we analyze three large and one small social network datasets. Our analysis shows that, irrespective of the number of nodes for any particular interest in the network, at least 50% of the nodes are part of the same connected component in the graph induced by each interest. Another interesting result of our analysis is that the majority of sub-communities (50% or above) for any interest are separated by small hops (two to three) from each other.

Place, publisher, year, edition, pages
2015. 1503-1508 p.
Keyword [en]
Community Patterns, Social Network Analysis, Attribute Based Community Analysis
National Category
Computer Science
URN: urn:nbn:se:uu:diva-299016DOI: 10.1145/2808797.2809330ISI: 000371793500224ISBN: 9781450338547OAI: oai:DiVA.org:uu-299016DiVA: diva2:948738
IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), AUG 25-28, 2015, Paris, FRANCE
Available from: 2016-07-13 Created: 2016-07-13 Last updated: 2016-07-13Bibliographically approved

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Magnani, Matteo
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