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Generating artificial social networks
Högskolan Kristianstad, Sektionen för lärande och miljö, Avdelningen för Psykologi.ORCID-id: 0000-0002-8057-3831
2019 (engelsk)Inngår i: The Quantitative Methods for Psychology, ISSN 1017-3455, E-ISSN 1543-8740, Vol. 15, nr 2, s. 56-74Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

The study of complex social networks is an inherently interdisciplinary research area with applications across many fields, including psychology. Social network models describe, illustrate and explain how people are connected to each other and can, for example, be used to study information spread and interconnectedness of people with different kinds of traits. One approach to social network modelling, originating mainly in the physics literature, is to generate targeted kinds of social networks using models with specialized mechanisms while analyzing and deriving features of the models. Surprisingly though, and despite the popularity of this approach, there is no available functionality for generating a wide variety of social networks from these models. Thus, researchers are left to implement and specify these models themselves, restricting the applicability of these models. In this article, I provide a set of Matlab functions enabling the generation of artificial social networks from 22 different network models, most of them explicitly designed to capture features of social networks. Many of these models originate in the physics literature and may therefore not be familiar to psychological researchers. I also provide an illustration of how these models can be evaluated in terms of a simulated model comparison approach and how they can be applied to psychological research. With the already existing network functionality available in Matlab and other languages, this should provide a useful extension to researchers.

sted, utgiver, år, opplag, sider
2019. Vol. 15, nr 2, s. 56-74
Emneord [en]
Social Network; Model; Psychology; Matlab; Function; Clustering; Community.
HSV kategori
Identifikatorer
URN: urn:nbn:se:hkr:diva-16432DOI: 10.20982/tqmp.15.2.p056OAI: oai:DiVA.org:hkr-16432DiVA, id: diva2:1065198
Tilgjengelig fra: 2017-01-13 Laget: 2017-01-13 Sist oppdatert: 2019-10-07bibliografisk kontrollert

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