dorsal/arxiv
View SchemaNew approaches to model and study social networks
| Authors | Pedro G. Lind, Hans J. Herrmann |
|---|---|
| Categories | |
| ArXiv ID | physics/0701107 |
| URL | https://arxiv.org/abs/physics/0701107 |
| DOI | 10.1088/1367-2630/9/7/228 |
| Journal | New J. of Phys. 9, 228 (2007) |
Abstract
We describe and develop three recent novelties in network research which are particularly useful for studying social systems. The first one concerns the discovery of some basic dynamical laws that enable the emergence of the fundamental features observed in social networks, namely the nontrivial clustering properties, the existence of positive degree correlations and the subdivision into communities. To reproduce all these features we describe a simple model of mobile colliding agents, whose collisions define the connections between the agents which are the nodes in the underlying network, and develop some analytical considerations. The second point addresses the particular feature of clustering and its relationship with global network measures, namely with the distribution of the size of cycles in the network. Since in social bipartite networks it is not possible to measure the clustering from standard procedures, we propose an alternative clustering coefficient that can be used to extract an improved normalized cycle distribution in any network. Finally, the third point addresses dynamical processes occurring on networks, namely when studying the propagation of information in them. In particular, we focus on the particular features of gossip propagation which impose some restrictions in the propagation rules. To this end we introduce a quantity, the spread factor, which measures the average maximal fraction of nearest neighbors which get in contact with the gossip, and find the striking result that there is an optimal non-trivial number of friends for which the spread factor is minimized, decreasing the danger of being gossiped.
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"abstract": "We describe and develop three recent novelties in network research which are\nparticularly useful for studying social systems. The first one concerns the\ndiscovery of some basic dynamical laws that enable the emergence of the\nfundamental features observed in social networks, namely the nontrivial\nclustering properties, the existence of positive degree correlations and the\nsubdivision into communities. To reproduce all these features we describe a\nsimple model of mobile colliding agents, whose collisions define the\nconnections between the agents which are the nodes in the underlying network,\nand develop some analytical considerations. The second point addresses the\nparticular feature of clustering and its relationship with global network\nmeasures, namely with the distribution of the size of cycles in the network.\nSince in social bipartite networks it is not possible to measure the clustering\nfrom standard procedures, we propose an alternative clustering coefficient that\ncan be used to extract an improved normalized cycle distribution in any\nnetwork. Finally, the third point addresses dynamical processes occurring on\nnetworks, namely when studying the propagation of information in them. In\nparticular, we focus on the particular features of gossip propagation which\nimpose some restrictions in the propagation rules. To this end we introduce a\nquantity, the spread factor, which measures the average maximal fraction of\nnearest neighbors which get in contact with the gossip, and find the striking\nresult that there is an optimal non-trivial number of friends for which the\nspread factor is minimized, decreasing the danger of being gossiped.",
"arxiv_id": "physics/0701107",
"authors": [
"Pedro G. Lind",
"Hans J. Herrmann"
],
"categories": [
"physics.soc-ph"
],
"doi": "10.1088/1367-2630/9/7/228",
"journal_ref": "New J. of Phys. 9, 228 (2007)",
"title": "New approaches to model and study social networks",
"url": "https://arxiv.org/abs/physics/0701107"
},
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