ConsensUs: Supporting Multi-Criteria Group Decisions by Visualizing Points of Disagreement.
ACM Trans. Social Computing(2018)
摘要
Groups often face difficulty reaching consensus. For complex decisions with multiple criteria, verbal and written discourse alone may impede groups from pinpointing and moving past fundamental disagreements. To help support consensus building, we introduce ConsensUs, a novel visualization tool that highlights disagreement by asking group members to quantify their subjective opinions across multiple criteria. To evaluate this approach, we conducted a between-subjects experiment with 87 participants on a comparative hiring task. The study compared three modes of sensemaking on a group decision: written discourse only, visualization only, and written discourse plus visualization. We confirmed that the visualization helped participants identify disagreements within the group and then measured subsequent changes to their individual opinions. The results show that disagreement highlighting led participants to align their ratings more with the opinions of other group members. While disagreement highlighting led to better score alignment, participants reported a number of reasons for shifting their score, from genuine consensus to appeasement. We discuss further research angles to understand how disagreement highlighting affects social processes and whether it produces objectively better decisions.
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关键词
Multi-criteria decisions, consensus building, group decision making, information visualization
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