An Experimental Study of Structural Diversity in Social Networks

Su, Jessica; Kamath, Krishna; Sharma, Aneesh; Ugander, Johan; Goel, Sharad

doi:10.1609/icwsm.v14i1.7332

Cited by 8 publications

(3 citation statements)

References 27 publications

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“…Typically, this involves recommending triad closing ties, though platforms have at times experimented with making recommendations that result in less clustered (i.e. more structurally diverse networks; Rajkumar et al, 2022;Su et al, 2020). For individuals, these results demonstrate the indirect consequences of forming a tie: it may result in further, potentially advantageous, tie formation with those connected to the new contact.…”

Section: Discussionmentioning

confidence: 99%

Tendencies toward triadic closure: Field-experimental evidence

Mosleh,

Eckles,

Rand

2024

Preprint

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Empirical social networks are characterized by a high degree of triadic closure (i.e. transitivity, clustering), whereby network neighbors of the same individual are also likely to be directly connected. It is unknown to what degree this results from dispositions to form such relationships (i.e. to close open triangles) per se or whether it reflects other processes, such as homophily and more opportunities for exposure. These are difficult to disentangle in many settings, but in social media not only can they be decomposed, but platforms frequently make decisions that can depend on these distinct processes. Here, using a field experiment on social media, we randomize the existing network structure that a user faces when followed by a target account that we control, and we examine whether they reciprocate this tie formation. Being randomly assigned to have an existing tie to an account that follows the target user increases tie formation by 35%. Through the use of multiple control conditions in which the relevant tie is absent (never existent or removed), we are able to attribute this effect specifically to a small variation in the stimulus that indicates the presence (or absence) of a potential mutual follower. Theory suggests that triadic closure should be especially likely in open triads of strong ties, and we find evidence of larger effects when the subject has interacted more with the existing follower. These results indicate a substantial role for dispositions toward triadic closure, which platforms and others can choose to leverage in encouraging tie formation, with implications for network structure and the diffusion of information in online networks.

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Section: Discussionmentioning

confidence: 99%

Tendencies toward triadic closure: Field-experimental evidence

Mosleh,

Eckles,

Rand

2024

Preprint

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“…This approach has less to do with discussion (see below for our approach to conceptualizing discussion diversity), and more to do with information, including news and public affairs content. Thus, informational diversity indicates the “degree of [political] heterogeneity among an individual’s contacts” (Su et al, 2020).…”

Section: Egocentric Publicsmentioning

confidence: 99%

Networks and Selective Avoidance: How Social Media Networks Influence Unfriending and Other Avoidance Behaviors

Barnidge

Peacock

Cooks

et al. 2022

Social Science Computer Review

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From time to time, some social media users avoid content posted by specific people in their networks. Most research on such selective avoidance has focused on individual motivations and other psychological factors rather than on social network characteristics, and there is a need for a systematic analysis of the relationships between individuals’ social media networks and selective avoidance. This study fills that gap in the literature, drawing on theory about egocentric or personal publics. We test our predictions using data from three surveys of adults in the United States, collected just before each of the last three major national elections. Results are discussed in light of theory about the role of media technology in shaping political communication and scholarly discourse about how selective avoidance affects information flows.

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“…For example, Granovetter makes the point that strong ties are individually stronger than weak ties, but the latter are more numerous, and thus more likely to provide job opportunities in aggregate (Granovetter 1977). Similarly, observing two peers who are not socially connected adopt a behavior may be less (or more) influential than observing two peers from the same social circle do a behavior (Ugander et al 2012;Su et al 2020). Many of these heterogeneities can be thought of driven by the position of alters in the network, but independently from that, the social status of the observed peer may also play a role in the strength of the peer effect (Paluck, Shepherd, and Aronow 2016).…”

Section: Introductionmentioning

confidence: 99%

Experience-Driven Peer Effects: Evidence from a Large Natural Experiment

Cai

Ugander

2021

ICWSM

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Social interactions between people are a central mechanism by which behavior spreads. Several field studies have shown how observing peer behavior affects ones own behavior in a wide range of domains including health, information diffusion, advertisement, and education. However, the role of observing peer experience or outcome---the reward for the observed peer behavior---has largely gone uninvestigated. Here we examine evidence from a large-scale online setting, game play records from League of Legends match-ups, where we are able to disentangle the effects of observing peer behavior from observing peer experience. We find that in addition to positive peer effects from observing behavior, the effect is accentuated by observed experience, with a large positive effect when observing a good outcome and a small (but still positive) effect when observing a bad outcome. We further find that this experience driven effect is moderated by skill, becoming more pronounced among highly skilled subjects. Our findings demonstrate the importance of the role of observed peer experience beyond peer behavior. We anticipate this result to be of use to both practitioners and theoreticians in the space of social influence. For example, online platforms may wish to broadcast the positive outcomes of peers, more than mere behaviors, when a user performs a behavior desirable to the platform. Furthermore, efforts aimed at maximizing the social spread of a product may benefit from modeling experience-driven peer effects as part of the spreading process.

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An Experimental Study of Structural Diversity in Social Networks

Cited by 8 publications

References 27 publications

Tendencies toward triadic closure: Field-experimental evidence

Tendencies toward triadic closure: Field-experimental evidence

Networks and Selective Avoidance: How Social Media Networks Influence Unfriending and Other Avoidance Behaviors

Experience-Driven Peer Effects: Evidence from a Large Natural Experiment

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