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Link-Prediction to Tackle the Boundary Specification Problem in Social Network Surveys

Jordan, Tobias, Oto, Costa, De Wilde, Philippe, Buarque de Lima Neto, Fernando (2017) Link-Prediction to Tackle the Boundary Specification Problem in Social Network Surveys. PLoS ONE, 12 (4). Article Number 176094. ISSN 1932-6203. (doi:10.1371/journal.pone.0176094) (KAR id:61392)

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Abstract

Diffusion processes in social networks often cause the emergence of global phenomena from individual behavior within a society. The study of those global phenomena and the simulation of those diffusion processes frequently require a good model of the global network. However, survey data and data from online sources are often restricted to single social groups or features, such as age groups, single schools, companies, or interest groups. Hence, a modeling approach is required that extrapolates the locally restricted data to a global network model. We tackle this Missing Data Problem using Link-Prediction techniques from social network research, network generation techniques from the area of Social Simulation, as well as a combination of both. We found that techniques employing less information may be more adequate to solve this problem, especially when data granularity is an issue. We validated the network models created with our techniques on a number of real-world networks, investigating degree distributions as well as the likelihood of links given the geographical distance between two nodes.

Item Type: Article
DOI/Identification number: 10.1371/journal.pone.0176094
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 75 Electronic computers. Computer science
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Philippe De Wilde
Date Deposited: 19 Apr 2017 15:09 UTC
Last Modified: 16 Feb 2021 13:44 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/61392 (The current URI for this page, for reference purposes)
De Wilde, Philippe: https://orcid.org/0000-0002-4332-1715
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