Reddit CrosspostNet—Studying Reddit Communities with Large-Scale Crosspost Graph Networks

Abstract

As the largest open social medium on the Internet, Reddit is widely studied in the scientific literature. Due to its structured form and division into topical subfora (subreddits), conducted research often concerns connections and interactions between users and/or whole, subreddit-structure-based communities. Overall, the relations between communities are most often studied by applying graph networks, with various creation algorithms. In this work, a novel approach is proposed to build and understand the structure of Reddit. It is based on crossposts—posts that appeared on one subreddit and then were crossposted to another. After capturing one year of crossposts, a directed weighted graph network, using seven million posts from over 10,000 of the most popular subreddits, has been created. Using graph network algorithms, its characteristics are captured and compared to similar studies. We identify the information “sinks” and “sources”—the most active crossposting subreddits. Moreover, we obtained graph network metrics: the degree (modeled with the Power Law), clustering, community detection algorithms, and connected components structure network are compared to previous studies on Reddit network(s), yielding consistent, but also novel results. Finally, the relations between extensively studied subreddits (e.g., r/AITA, r/Parenting, r/politics) and new ones, which were not accounted for in previous research, opening new paths for data-driven studies, are summarized.