Rare, but Valuable: Understanding Data-centered Talk in News Website Comment Sections

Abstract

News websites can facilitate global discussions about civic issues, but the financial cost and burden of moderating these forums has forced many to disable their commenting systems. In this paper, we consider the role that data visualizations play in online discussion around a civic issue, through an analysis of how people talk about climate change data in the comment threads at three news websites (i.e., Breitbart news, the Guardian, the New York Times). We find that out of 6,525 comments, only 2.4% reference data visualizations in the articles. While rare, the paper presents illustrative examples of how people refer to data-their collection, analysis, and visual representation-to engage with an article's narrative. Using text classification techniques we identify several features related to the content of comments that contain data-centered talk, such as article cosine similarity, hyperlinks, and comparison terms. Finally, we discuss potential ways that newsrooms might apply this analysis to promote data literacy, data science, and to foster community around shared experiences.