Effects of Network Structure on Subjective Preference Diversity

Published in 2019 IEEE International Conference on Big Data (Big Data), 2019

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 rankings) may lead to homogeneity in the subjective preference of the users over time.’

Use Google Scholar for full citation