title: What Big Data tells: Sampling the social network by communication channels.
abstract: Big Data has become the primary source of understanding the structure and dynamics of the society at large scale. The network of social interactions can be considered as a multiplex, where each layer corresponds to one communication channel and the aggregate of all of them constitutes the entire social network. However, usually one has information only about one of the channels or even a part of it, which should be considered as a subset or sample of the whole. Here we introduce a model based on a natural bilateral communication channel selection mechanism, which for one channel leads to consistent changes in the network properties. For example, while it is expected that the degree distribution of the whole social network has a maximum at a value larger than one, we get a monotonically decreasing distribution as observed in empirical studies of single-channel data. We also find that assortativity may occur or get strengthened due to the sampling method. We analyze the far-reaching consequences of our findings.
authors.affiliation: Department of Theoretical Physics, Budapest University of Technology and Economics, Budapest H-1111, Hungary.|Center for Network Science, Central European University, Budapest H-1051, Hungary.
authors.forename: János
authors.initials: J
authors.lastname: Török
authors.affiliation: RIKEN Advanced Institute for Computational Science, Kobe, Hyogo 650-0047, Japan.
authors.forename: Yohsuke
authors.initials: Y
authors.lastname: Murase
authors.affiliation: Department of Physics, Pohang University of Science and Technology, Pohang 37673, Republic of Korea.|Department of Computer Science, Aalto University School of Science, P.O. Box 15500, Espoo, Finland.
authors.forename: Hang-Hyun
authors.initials: HH
authors.lastname: Jo
authors.affiliation: Department of Theoretical Physics, Budapest University of Technology and Economics, Budapest H-1111, Hungary.|Center for Network Science, Central European University, Budapest H-1051, Hungary.|Department of Computer Science, Aalto University School of Science, P.O. Box 15500, Espoo, Finland.
authors.forename: János
authors.initials: J
authors.lastname: Kertész
authors.affiliation: Department of Computer Science, Aalto University School of Science, P.O. Box 15500, Espoo, Finland.
authors.forename: Kimmo
authors.initials: K
authors.lastname: Kaski
mesh_terms: D003142:Communication; D003627:Data Interpretation, Statistical; D006801:Humans; D008962:Models, Theoretical; D012944:Social Support