Abstract

Different social media environments enable different levels of community connectedness, which in turn affects the information that a user is exposed to. In this study, we create an agent-based model to investigate how the different levels of connectedness as well as network structure affects a group's diversity of opinions. In the model, agents are tasked with “liking” or “disliking” a set of objects. At each turn, each agent sees the most popular object amongst the agents that they are connected to. There are two main findings: 1) low network connectivity leads to more diversity amongst agents, 2) a complete network leads information popularity distribution to be more skewed, 3) the more random a network is, the more skewed information popularity distribution is. These findings suggest that online platforms that either create well-connected communities or present aggregated information of users (such as Billboard …

Date

December 9, 2019

Authors

Anne Lin, Andreés Abeliuk, Emilio Ferrara

Conference

2019 IEEE International Conference on Big Data (Big Data)

Pages

3026-3031

Publisher

IEEE