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Discovering missing me edges across social networks

Articolo
Data di Pubblicazione:
2015
Citazione:
Discovering missing me edges across social networks / Buccafurri, F., Lax, G., Nocera, A., Ursino, D.. - In: INFORMATION SCIENCES. - ISSN 0020-0255. - 319:(2015), pp. 18-37. [10.1016/j.ins.2015.05.014]
Abstract:
Distinct social networks are interconnected via membership overlap, which plays a key role when crossing information is investigated in the context of multiple-social-network analysis. Unfortunately, users do not always make their membership to two distinct social networks explicit, by specifying the so-called me edge (practically, corresponding to a link between the two accounts), thus missing a potentially very useful information. As a consequence, discovering missing me edges is an important problem to address in this context with potential powerful applications. In this paper, we propose a common-neighbor approach to detecting missing me edges, which returns good results in real-life settings. Indeed, an experimental campaign shows both that the state-of-the-art common-neighbor approaches cannot be effectively applied to our problem and, conversely, that our approach returns precise and complete results.
Tipologia CRIS:
1.1 Articolo in rivista
Elenco autori:
Buccafurri, F; Lax, G; Nocera, A; Ursino, D
Autori di Ateneo:
BUCCAFURRI Francesco
LAX Gianluca
Link alla scheda completa:
https://iris.unirc.it/handle/20.500.12318/1996
Link al Full Text:
https://iris.unirc.it//retrieve/handle/20.500.12318/1996/254832/Buccafurri_2015_j.ins_Discovering_Post.pdf
Pubblicato in:
INFORMATION SCIENCES
Journal
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URL

https://www.sciencedirect.com/science/article/abs/pii/S0020025515003722
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