dorsal/arxiv
View SchemaA Stochastic Evolutionary Growth Model for Social Networks
| Authors | Trevor Fenner, Mark Levene, George Loizou, George Roussos |
|---|---|
| Categories | |
| ArXiv ID | physics/0607188 |
| URL | https://arxiv.org/abs/physics/0607188 |
Abstract
We present a stochastic model for a social network, where new actors may join the network, existing actors may become inactive and, at a later stage, reactivate themselves. Our model captures the evolution of the network, assuming that actors attain new relations or become active according to the preferential attachment rule. We derive the mean-field equations for this stochastic model and show that, asymptotically, the distribution of actors obeys a power-law distribution. In particular, the model applies to social networks such as wireless local area networks, where users connect to access-points, and peer-to-peer networks where users connect to each other. As a proof of concept, we demonstrate the validity of our model empirically by analysing a public log containing traces from a wireless network at Dartmouth College over a period of three years. Analysing the data processed according to our model, we demonstrate that the distribution of user accesses is asymptotically a power-law distribution.
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"abstract": "We present a stochastic model for a social network, where new actors may join\nthe network, existing actors may become inactive and, at a later stage,\nreactivate themselves. Our model captures the evolution of the network,\nassuming that actors attain new relations or become active according to the\npreferential attachment rule. We derive the mean-field equations for this\nstochastic model and show that, asymptotically, the distribution of actors\nobeys a power-law distribution. In particular, the model applies to social\nnetworks such as wireless local area networks, where users connect to\naccess-points, and peer-to-peer networks where users connect to each other. As\na proof of concept, we demonstrate the validity of our model empirically by\nanalysing a public log containing traces from a wireless network at Dartmouth\nCollege over a period of three years. Analysing the data processed according to\nour model, we demonstrate that the distribution of user accesses is\nasymptotically a power-law distribution.",
"arxiv_id": "physics/0607188",
"authors": [
"Trevor Fenner",
"Mark Levene",
"George Loizou",
"George Roussos"
],
"categories": [
"physics.soc-ph"
],
"title": "A Stochastic Evolutionary Growth Model for Social Networks",
"url": "https://arxiv.org/abs/physics/0607188"
},
"schema_id": "dorsal/arxiv",
"source": {
"execution_id": "b6a76ad9-c27d-406f-ac8f-500b8b9a609d",
"id": "arXiv Dataset IDs",
"type": "Model",
"variant": "snapshot-2026-03-01",
"version": "0.1.0"
},
"user_id": 1000002
}