Temporal Analysis of Reddit Networks via Role Embeddings
This work provides insights into temporal dynamics of user behavior in online communities, but it is incremental as it adapts existing methods to a new temporal context without major innovations.
The paper tackled the problem of understanding how user roles evolve over time in social networks by applying the struc2vec role embedding algorithm to Reddit data from loyal and vagrant communities over nine months, enabling analysis of role changes at individual and community levels.
Inspired by diachronic word analysis from the field of natural language processing, we propose an approach for uncovering temporal insights regarding user roles from social networks using graph embedding methods. Specifically, we apply the role embedding algorithm, struc2vec, to a collection of social networks exhibiting either "loyal" or "vagrant" characteristics derived from the popular online social news aggregation website Reddit. For each subreddit, we extract nine months of data and create network role embeddings on consecutive time windows. We are then able to compare and contrast how user roles change over time by aligning the resulting temporal embeddings spaces. In particular, we analyse temporal role embeddings from an individual and a community-level perspective for both loyal and vagrant communities present on Reddit.