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Structure and Evolution of Online Social Networks.

Ravi Kumar, +2 more
- pp 337-357
TLDR
In this paper, the evolution of structure within large online social networks is studied. Butler et al. present a series of measurements of two such networks, together comprising in excess of five million people and ten million friendship links, annotated with metadata capturing the time of every event.
Abstract
In this paper, we consider the evolution of structure within large online social networks. We present a series of measurements of two such networks, together comprising in excess of five million people and ten million friendship links, annotated with metadata capturing the time of every event in the life of the network. Our measurements expose a surprising segmentation of these networks into three regions: singletons who do not participate in the network; isolated communities which overwhelmingly display star structure; and a giant component anchored by a well-connected core region which persists even in the absence of stars.We present a simple model of network growth which captures these aspects of component structure. The model follows our experimental results, characterizing users as either passive members of the network; inviters who encourage offline friends and acquaintances to migrate online; and linkers who fully participate in the social evolution of the network.

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Citations
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Social Network Sites: Definition, History, and Scholarship

TL;DR: This publication contains reprint articles for which IEEE does not hold copyright and which are likely to be copyrighted.
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Community detection in graphs

TL;DR: A thorough exposition of community structure, or clustering, is attempted, from the definition of the main elements of the problem, to the presentation of most methods developed, with a special focus on techniques designed by statistical physicists.
Proceedings ArticleDOI

Measurement and analysis of online social networks

TL;DR: This paper examines data gathered from four popular online social networks: Flickr, YouTube, LiveJournal, and Orkut, and reports that the indegree of user nodes tends to match the outdegree; the networks contain a densely connected core of high-degree nodes; and that this core links small groups of strongly clustered, low-degree node at the fringes of the network.
Posted Content

Community Structure in Large Networks: Natural Cluster Sizes and the Absence of Large Well-Defined Clusters

TL;DR: In this article, the authors employ approximation algorithms for the graph partitioning problem to characterize as a function of size the statistical and structural properties of partitions of graphs that could plausibly be interpreted as communities.
Proceedings ArticleDOI

On the evolution of user interaction in Facebook

TL;DR: It is found that links in the activity network tend to come and go rapidly over time, and the strength of ties exhibits a general decreasing trend of activity as the social network link ages.
References
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