Search Results (2)

Reddit is the largest topically structured social network. Existing literature, reporting results of Reddit-related research, considers different phenomena, from social and political studies to recommender systems. The most common techniques used in these works, include natural language processing, e.g., named entity recognition, as well as graph networks representing online social networks. However, large-scale studies that take into account Reddit’s unique structure are scarce. In this contribution, similarity between subreddits is explored. Specifically, subreddit posts (from 3189 subreddits, spanning the year 2022) are processed using NER to build graph networks which are further mined for relations between subreddits. The evaluation of obtained results follows the state-of-the-art approaches used for a similar problem, i.e., recommender system metrics, and applies recall and AUC. Overall, the use of Reddit crossposts discloses previously unknown relations between subreddits. Interestingly, the proposed approach may allow for researchers to better connect their study topics with particular subreddits and shows promise for subreddit similarity mining. Full article

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. Full article