Making the Pick: Understanding Professional Editor Comment Curation in Online News

Online comments within news articles are a key way people share opinions. Discovering insightful comments can, however, be challenging for readers. A solution to this problem is using comment curation, whereby professional editors select the highest quality comments manually — referred to as “editor-picks”. This paper studies the growing use of professional editor-curation for user-generated comments. We focus on the New York Times as a case study, using a dataset covering 80k articles. We study the characteristics of editor-pick comments, highlighting how editor criteria vary across news sections (e.g. sports, entertainment). We find that editor-pick comments tend to be longer, more relevant to the article, positive in sentiment, and contain low toxicity. Our analysis fur- ther reveals that editors within different news sections exhibit differing criteria when they perform comment selection. Thus, we finally propose a set of models that can automatically identify good candidate editor-picks. Our ultimate goal is to reduce editor and journalistic workload, increasing productivity and the quality of curated comments.