
doi: 10.1145/3492837
The problems associated with open-ended group discussion are well-documented in sociology research. We seek to alleviate these issues using technology that autonomously serves as a discussion moderator. Building on top of an extensible framework called Diplomat, we develop a "conversational agent", ArbiterBot to promote efficiency, fairness, and professionalism in otherwise unstructured discussions. To evaluate the effectiveness of this agent, we recruited university students to participate in a study involving a series of prompted discussions over the Slack messenger app. The results of this study suggest that the conversational agent is effective at balancing contributions across participants, encouraging a timely consensus and promoting a higher coverage of topics. We believe that the results motivate further investigation into how conversational agents can be used to improve group discussion and cooperation.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 16 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
