mlsanityData to 7 Oct 2026

Conversational Markers of Constructive Discussions

arXiv 1604.07407 ↗First posted 25 Apr 2016cs.CL cs.AI cs.SIcited by 17

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Abstract (arXiv)

Group discussions are essential for organizing every aspect of modern life, from faculty meetings to senate debates, from grant review panels to papal conclaves. While costly in terms of time and organization effort, group discussions are commonly seen as a way of reaching better decisions compared to solutions that do not require coordination between the individuals (e.g. voting)---through discussion, the sum becomes greater than the parts. However, this assumption is not irrefutable: anecdotal evidence of wasteful discussions abounds, and in our own experiments we find that over 30% of discussions are unproductive. We propose a framework for analyzing conversational dynamics in order to determine whether a given task-oriented discussion is worth having or not. We exploit conversational patterns reflecting the flow of ideas and the balance between the participants, as well as their linguistic choices. We apply this framework to conversations naturally occurring in an online collaborative world exploration game developed and deployed to support this research. Using this setting, we show that linguistic cues and conversational patterns extracted from the first 20 seconds of a team discussion are predictive of whether it will be a wasteful or a productive one.

Key facts. Cited by 17 papers in the map (data through 7 Oct 2026). First posted on arXiv 25 Apr 2016.

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Citing papers per year: 2021: 5; 2022: 2; 2023: 1; 2024: 2; 2025: 4; 2026: 3.

17 papers.

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  1. 2021Beyond Fair Pay: Ethical Implications of NLP Crowdsourcingcited by 52
  2. 2021Measuring Conversational Uptake: A Case Study on Student-Teacher Interactionscited by 44
  3. 2021DeliData: A dataset for deliberation in multi-party problem solvingcited by 26
  4. 2021I Beg to Differ: A study of constructive disagreement in online conversationscited by 18
  5. 2023Do Differences in Values Influence Disagreements in Online Discussions?cited by 15
  6. 2024An LLM Feature-based Framework for Dialogue Constructiveness Assessmentcited by 9
  7. 2021Revisiting Contextual Toxicity Detection in Conversationscited by 8
  8. 2025Evaluation and Facilitation of Online Discussions in the LLM Era: A Surveycited by 8
  9. 2022How to disagree well: Investigating the dispute tactics used on Wikipediacited by 6
  10. 2024How Did We Get Here? Summarizing Conversation Dynamicscited by 6
  11. 2025Towards a Perspectivist Turn in Argument Quality Assessmentcited by 5
  12. 2022What makes you change your mind? An empirical investigation in online group decision-making conversationscited by 3
5 more
  1. 2025Conversations Gone Awry, But Then? Evaluating Conversational Forecasting Modelscited by 2
  2. 2025Time is On My Side: Dynamics of Talk-Time Sharing in Video-chat Conversationscited by 0
  3. 2026DeliChess: A Multi-party Dialogue Dataset for Deliberation in Chess Puzzle Solvingcited by 0
  4. 2026Who Plays Which Role When? Communication Role Dynamics for Peer Recognition and Team Performance Predictioncited by 0
  5. 2026Adapting from Downturns: Prediction of Long-Term Conversational-Skill Development in Mental-Health Crisis Counselorscited by 0