This chapter provides an overview of the work of the junior research group DEDIS (Deliberative Discussions in the Social Web). Drawing on theories of deliberative democracy, we developed and tested innovative measures to improve the quality of citizens’ online discussions about political issues. This chapter focuses on our research on new forms of moderating online discussions and our development of computer-based moderation systems. It outlines our model of moderation effects, which suggests that moderation increases citizens’ willingness to participate in online discussions and to write engaging comments through two pathways: perceived support/sense of community and perceived discussion quality. The chapter also describes empirical evidence that such an expanded understanding of moderation and its effects improves both the quality and deliberative outcomes of online discussions. Finally, the chapter includes a brief overview of an AI-powered moderation system we developed that can help moderators efficiently identify and respond to high-quality and low-quality user comments. Overall, the work of the junior research group advances research on online deliberation and moderation and helps to formulate realistic expectations about what professional moderation can achieve.

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Deliberative Discussions in the Social Web (DEDIS): Using Moderation to Improve the Quality and the Effects of Online Discussions

  • Marc Ziegele

摘要

This chapter provides an overview of the work of the junior research group DEDIS (Deliberative Discussions in the Social Web). Drawing on theories of deliberative democracy, we developed and tested innovative measures to improve the quality of citizens’ online discussions about political issues. This chapter focuses on our research on new forms of moderating online discussions and our development of computer-based moderation systems. It outlines our model of moderation effects, which suggests that moderation increases citizens’ willingness to participate in online discussions and to write engaging comments through two pathways: perceived support/sense of community and perceived discussion quality. The chapter also describes empirical evidence that such an expanded understanding of moderation and its effects improves both the quality and deliberative outcomes of online discussions. Finally, the chapter includes a brief overview of an AI-powered moderation system we developed that can help moderators efficiently identify and respond to high-quality and low-quality user comments. Overall, the work of the junior research group advances research on online deliberation and moderation and helps to formulate realistic expectations about what professional moderation can achieve.