A computational study of homophily and diffusion of common knowledge on social networks based on a model of Facebook
- PDF / 2,044,920 Bytes
- 12 Pages / 595.276 x 790.866 pts Page_size
- 103 Downloads / 249 Views
ORIGINAL ARTICLE
A computational study of homophily and diffusion of common knowledge on social networks based on a model of Facebook Gizem Korkmaz1 · Chris J. Kuhlman1 · Joshua Goldstein1 · Fernando Vega‑Redondo2 Received: 5 February 2019 / Revised: 18 November 2019 / Accepted: 22 November 2019 © Springer-Verlag GmbH Austria, part of Springer Nature 2019
Abstract In this paper, we introduce homophily to a game-theoretic model of collective action (e.g., protests) on Facebook and study the effect of homophily in individuals’ willingness to participate in collective action, i.e., their thresholds, on the emergence and spread of collective action. We use three different networks (a real Facebook network, an Erdős–Rényi random graph, and a scale-free network) and conduct computational experiments to study contagion dynamics (the size and the speed of diffusion) with respect to the level of homophily. We provide a series of parametric results on the time to achieve a specified contagion spread, on the spread of contagion at different times, and the probability of cascades. We demonstrate that these behaviors are highly nonlinear and nonmonotonic in homophily. Networks with randomly assigned thresholds result in both smaller and slower diffusion compared to the networks characterized by homophily and heterophily.
1 Introduction 1.1 Background and motivation Social interactions occur among agents with both similar and different preferences. Informally, homophily is the tendency of people to form edges (links, relationships) with other people that have similar traits (McPherson et al. 2001; Anagnostopoulos et al. 2008; Jackson and Lopez-Pintado 2013). Homophily is important in capturing differences among people with respect to traits such as age, gender, religion, ethnicity, social class, and beliefs (McPherson et al. 2001). A preliminary version of the paper appeared in the Proceedings of 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (Korkmaz et al. 2018). * Gizem Korkmaz [email protected] Chris J. Kuhlman [email protected] Joshua Goldstein [email protected] Fernando Vega‑Redondo [email protected] 1
Biocomplexity Institute, University of Virginia, Arlington, VA, USA
Bocconi University, Milan, Italy
2
For example, modeling studies of homophily have shown that increasing homophily leads to more cultural diversity in populations (Flache and Macy 2011). Not accounting for homophily overestimates the incentives to increase the spread of contagion in an instant messaging network (Aral et al. 2013). Homophily has also been used to explain how large group of individuals can improve or impede the success of collective action (Centola 2013; Chiang 2007; Boyd and Richerson 2002). Collective action occurs when individuals within small or large groups or entire populations make decisions to act for a common cause, such as a protest in which an individual wants to join only if joined by “enough” others. Social networks offer an easy, quick and inexpensive me
Data Loading...
