An Experimental Study of Structural Diversity in Social Networks

@inproceedings{Su2019AnES,
  title={An Experimental Study of Structural Diversity in Social Networks},
  author={Jessica Su and Krishna Yeswanth Kamath and Aneesh Sharma and Johan Ugander and Sharad Goel},
  booktitle={International Conference on Web and Social Media},
  year={2019}
}
Several recent studies of online social networking platforms have found that adoption rates and engagement levels are positively correlated with structural diversity, the degree of heterogeneity among an individual's contacts as measured by network ties. One common theory for this observation is that structural diversity increases utility, in part because there is value to interacting with people from different network components on the same platform. While compelling, evidence for this causal… 
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References

SHOWING 1-10 OF 38 REFERENCES

Tie Strength, Embeddedness, and Social Influence: A Large-Scale Networked Experiment

This work presents some of the first large-scale in vivo experimental evidence investigating the social and structural moderators of peer influence in networks, and finds that both embeddedness and tie strength increase influence.

Differential Network Effects on Economic Outcomes: A Structural Perspective

In a study of about 33,000 individuals in a south Asian country, we find that structural diversity, measured as the fraction of open triads in an ego-network, shows a relatively strong association…

Structural diversity in social contagion

This analysis of the growth of Facebook shows how data at the size and resolution of the Facebook network make possible the identification of subtle structural signals that go undetected at smaller scales yet hold pivotal predictive roles for the outcomes of social processes.

The Strength of Weak Ties

Analysis of social networks is suggested as a tool for linking micro and macro levels of sociological theory. The procedure is illustrated by elaboration of the macro implications of one aspect of…

The Effect of Recommendations on Network Structure

It is found that users across the popularity spectrum benefitted from the recommendations; however, the most popular users profited substantially more than average, and people are much more likely to respond positively to recommendations for popular users, amplifying the cumulative advantage of well-known individuals.

On the Interplay between Social and Topical Structure

It is found that the hashtags that users adopt can predict their social relationships, and also that the social relationships between the initial adopters of a hashtag can predict the future popularity of that hashtag.

Virality Prediction and Community Structure in Social Networks

It is demonstrated that the future popularity of a meme can be predicted by quantifying its early spreading pattern in terms of community concentration, and the more communities a meme permeates, the more viral it is.

Homophily and Contagion Are Generically Confounded in Observational Social Network Studies

The authors demonstrate, with simple examples, that asymmetries in regression coefficients cannot identify causal effects and that very simple models of imitation can produce substantial correlations between an individual’s enduring traits and his or her choices, even when there is no intrinsic affinity between them.

Exercise contagion in a global social network

It is shown that exercise is socially contagious and that its contagiousness varies with the relative activity of and gender relationships between friends, and interventions that account for social contagion will spread behaviour change more effectively.

Understanding motivations for facebook use: usage metrics, network structure, and privacy

This study identified motives for Facebook use by employing a Uses and Gratifications approach and investigated the extent to which these motives can be predicted through usage and network metrics collected automatically via the Facebook API.