Predicting User-Interactions on Reddit
This work addresses content curation challenges for social media platforms, but it is incremental as it applies existing methods to new data.
The study tackled the problem of predicting user interactions on Reddit by analyzing clicking, browsing, and voting behavior from 186 users over a year, finding that simple models could predict individual interactions with reasonable accuracy.
In order to keep up with the demand of curating the deluge of crowd-sourced content, social media platforms leverage user interaction feedback to make decisions about which content to display, highlight, and hide. User interactions such as likes, votes, clicks, and views are assumed to be a proxy of a content's quality, popularity, or news-worthiness. In this paper we ask: how predictable are the interactions of a user on social media? To answer this question we recorded the clicking, browsing, and voting behavior of 186 Reddit users over a year. We present interesting descriptive statistics about their combined 339,270 interactions, and we find that relatively simple models are able to predict users' individual browse- or vote-interactions with reasonable accuracy.