Networks of strong ties

Shi, Xiaolin; Adamic, Lada A.; Strauss, Martin J.

doi:10.1016/j.physa.2006.11.072

Cited by 90 publications

(75 citation statements)

References 25 publications

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“…In practice, relatively simple proxies have substituted for it: communication reciprocity [11], possessing at least one mutual friend [37], recency of communication [28] and interaction frequency [13,17]. In a 1984 study, Peter Marsden used survey data from three metropolitan areas to precisely unpack the predictors of tie strength [33].…”

Section: The Dimensions Of Tie Strengthmentioning

confidence: 99%

Predicting tie strength with social media

Gilbert

Karahalios

2009

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

1,059

802

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Social media treats all users the same: trusted friend or total stranger, with little or nothing in between. In reality, relationships fall everywhere along this spectrum, a topic social science has investigated for decades under the theme of tie strength. Our work bridges this gap between theory and practice. In this paper, we present a predictive model that maps social media data to tie strength. The model builds on a dataset of over 2,000 social media ties and performs quite well, distinguishing between strong and weak ties with over 85% accuracy. We complement these quantitative findings with interviews that unpack the relationships we could not predict. The paper concludes by illustrating how modeling tie strength can improve social media design elements, including privacy controls, message routing, friend introductions and information prioritization.

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Section: The Dimensions Of Tie Strengthmentioning

confidence: 99%

Predicting tie strength with social media

Gilbert

Karahalios

2009

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

1,059

802

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“…Simmel theorized that people with common friends are more likely to create friendships and Krackhardt and Handcock [12] applied this theory to explain the evolution of triangle closures. A network model based on closed triangles was proposed by Shi et al [20].…”

Section: Related Workmentioning

confidence: 99%

Microscopic evolution of social networks

Leskovec

Bäckström

Kumar

et al. 2008

Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

607

506

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We present a detailed study of network evolution by analyzing four large online social networks with full temporal information about node and edge arrivals. For the first time at such a large scale, we study individual node arrival and edge creation processes that collectively lead to macroscopic properties of networks. Using a methodology based on the maximum-likelihood principle, we investigate a wide variety of network formation strategies, and show that edge locality plays a critical role in evolution of networks. Our findings supplement earlier network models based on the inherently non-local preferential attachment.Based on our observations, we develop a complete model of network evolution, where nodes arrive at a prespecified rate and select their lifetimes. Each node then independently initiates edges according to a "gap" process, selecting a destination for each edge according to a simple triangle-closing model free of any parameters. We show analytically that the combination of the gap distribution with the node lifetime leads to a power law out-degree distribution that accurately reflects the true network in all four cases. Finally, we give model parameter settings that allow automatic evolution and generation of realistic synthetic networks of arbitrary scale.

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“…In light of developments in the field of social networks, the affective bonds with the members of religious groups that these two studies theorize can be translated into what is known as strong social ties, which can be considered as close friends who have at least one person in common (Shi, Adamic and Strauss 2007). It is more expectable that adopting a new religion, which is a risky behavior, will require a presence of a strong tie to a member of that religion to develop enough trust to adopt it.…”

Section: Introductionmentioning

confidence: 99%