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.

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In many teams, members play distinct roles, from leader to disrupter to social networker. Understanding the roles that contributors enact in micro-lending platforms is both psychologically and socially important for sustaining members' motivation and coordinating their joint efforts. Knowing what roles exist in these communities or which additional ones might be needed can also help teams function more effectively. In this paper, we identify social roles in Kiva.org, a peer-to-peer micro-funding platform, by utilizing members' lending behaviors, social network behaviors and communication behaviors to model their social roles at three levels. At the individual level, this method discovered active lenders who made many loans, earlybird lenders who made loans well before deadlines, and lurkers who rarely lent. At the topical level, our method differentiated those who had broad interests and lent to many causes from those who made loans only to borrowers in certain geographic regions or industry sectors. At the team level, the method revealed eight team-oriented functional roles such as encouragers, reminders, competitors, followers, and welcomers. To demonstrate the utility of the team roles, we used regression analysis to show how the distribution of social roles within teams influences the amount of money teams lent. Implications for identifying roles and understanding their contributions to teams are discussed. CCS Concepts: • Human-centered computing → Computer supported cooperative work; Empirical studies in collaborative and social computing.

Due to challenges around low-quality comments and misinformation, many news outlets have opted to turn off commenting features on their websites. The New York Times (NYT), on the other hand, has continued to scale up its online discussion resources to reach large audiences. Through interviews with the NYT moderation team, we present examples of how moderators manage the first ~24 hours of online discussion after a story breaks, while balancing concerns about journalistic credibility. We discuss how managing comments at the NYT is not merely a matter of content regulation, but can involve reporting from the "community beat" to recognize emerging topics and synthesize the multiple perspectives in a discussion to promote community. We discuss how other news organizations---including those lacking moderation resources---might appropriate the strategies and decisions offered by the NYT. Future research should investigate strategies to share and update the information generated about topics in the news through the course of content moderation.

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