http://www.cnr.it/ontology/cnr/individuo/prodotto/ID294025
Information Diffusion in OSNs: The impact of Nodes' sociality (Contributo in atti di convegno)
- Type
- Label
- Information Diffusion in OSNs: The impact of Nodes' sociality (Contributo in atti di convegno) (literal)
- Anno
- 2014-01-01T00:00:00+01:00 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
- 10.1145/2554850.2555000 (literal)
- Alternative label
Arnaboldi V.; Conti M.; La Gala M.; Passarella A.; Pezzoni F. (2014)
Information Diffusion in OSNs: The impact of Nodes' sociality
in 29th Annual ACM Symposium on Applied Computing (SAC 2014), New York, USA
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- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Arnaboldi V.; Conti M.; La Gala M.; Passarella A.; Pezzoni F. (literal)
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- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
- http://www.scopus.com/inward/record.url?eid=2-s2.0-84905670757&partnerID=q2rCbXpz (literal)
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- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- IIT-CNR, via G. Moruzzi, 1-56124 Pisa, Italy (literal)
- Titolo
- Information Diffusion in OSNs: The impact of Nodes' sociality (literal)
- Abstract
- The advent of Online Social Networks allowed scientists to remarkably improve the knowledge of the mechanisms controlling the formation of information diffusion chains in social networks (typically referred to as information cascades). Nevertheless, we are still not fully able to explain the role of social tie strength in the process, since most of the analyses in literature are based on unweighted networks only, i.e., they do not consider the social strength of the links between nodes. In this paper we contribute to fill this gap by analysing the properties of synthetically generated information cascades in a social network derived from a Face-book communication dataset. The properties of the cascades are studied in detail in relation to the characteristics of the nodes from which the diffusion starts (seed nodes). We compute, for both weighted and unweighted networks, the correlation between different measures of connectivity and centrality of the seed nodes, and the coverage of the resulting cascades. The results indicate that the knowledge of the strength of the social links is fundamental to infer which nodes will give rise to large information cascades. Copyright 2014 ACM. (literal)
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