ConsensUs: Supporting MultiCriteria Group Decisions by Visualizing Points of Disagreement 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 betweensubjects 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.

VISTX: Experimenting with Interactive Stance and Sentiment Visualisation Usergenerated content online continues to grow rapidly, and with this it becomes more challenging to evaluate the general consensus on a trending topic. Even greater challenges are faced if one wishes to compare opinions across multiple topics, as it can be difficult to make comparisons and reach conclusions with large amounts of data in an intuitive manner. VISTX explores innovative methods of visualising opinion in terms of stance and sentiment using Twitter data from the SemEval2016 Stance Dataset and presents three types of interactive visualisations. We discuss the method of testing the visualisations for effectiveness with a small group of users, where time taken and the number of incorrect interpretations were measured for each user. We discuss the results, which indicate that the xe2x80x98circlepackingxe2x80x99 visualisation type may lead to quicker interpretations for five or more topics. Finally, we discuss the work needed to further solidify these initial findings.