Title |
Reconstruction of a Real World Social Network using the Potts Model and Loopy Belief Propagation
|
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Published in |
Frontiers in Psychology, November 2015
|
DOI | 10.3389/fpsyg.2015.01698 |
Pubmed ID | |
Authors |
Cristian Bisconti, Angelo Corallo, Laura Fortunato, Antonio A. Gentile, Andrea Massafra, Piergiuseppe Pellè |
Abstract |
The scope of this paper is to test the adoption of a statistical model derived from Condensed Matter Physics, for the reconstruction of the structure of a social network. The inverse Potts model, traditionally applied to recursive observations of quantum states in an ensemble of particles, is here addressed to observations of the members' states in an organization and their (anti)correlations, thus inferring interactions as links among the members. Adopting proper (Bethe) approximations, such an inverse problem is showed to be tractable. Within an operational framework, this network-reconstruction method is tested for a small real-world social network, the Italian parliament. In this study case, it is easy to track statuses of the parliament members, using (co)sponsorships of law proposals as the initial dataset. In previous studies of similar activity-based networks, the graph structure was inferred directly from activity co-occurrences: here we compare our statistical reconstruction with such standard methods, outlining discrepancies and advantages. |
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Geographical breakdown
Country | Count | As % |
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Switzerland | 2 | 33% |
United Kingdom | 1 | 17% |
Brazil | 1 | 17% |
Unknown | 2 | 33% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 4 | 67% |
Scientists | 2 | 33% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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China | 1 | 5% |
Unknown | 19 | 95% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 4 | 20% |
Other | 3 | 15% |
Student > Ph. D. Student | 3 | 15% |
Student > Master | 3 | 15% |
Student > Bachelor | 1 | 5% |
Other | 4 | 20% |
Unknown | 2 | 10% |
Readers by discipline | Count | As % |
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Physics and Astronomy | 3 | 15% |
Neuroscience | 3 | 15% |
Psychology | 2 | 10% |
Agricultural and Biological Sciences | 1 | 5% |
Computer Science | 1 | 5% |
Other | 9 | 45% |
Unknown | 1 | 5% |