Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
131 tokens/sec
GPT-4o
10 tokens/sec
Gemini 2.5 Pro Pro
47 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Social Orientation: A New Feature for Dialogue Analysis (2403.04770v1)

Published 26 Feb 2024 in cs.CL and cs.LG

Abstract: There are many settings where it is useful to predict and explain the success or failure of a dialogue. Circumplex theory from psychology models the social orientations (e.g., Warm-Agreeable, Arrogant-Calculating) of conversation participants and can be used to predict and explain the outcome of social interactions. Our work is novel in its systematic application of social orientation tags to modeling conversation outcomes. In this paper, we introduce a new data set of dialogue utterances machine-labeled with social orientation tags. We show that social orientation tags improve task performance, especially in low-resource settings, on both English and Chinese language benchmarks. We also demonstrate how social orientation tags help explain the outcomes of social interactions when used in neural models. Based on these results showing the utility of social orientation tags for dialogue outcome prediction tasks, we release our data sets, code, and models that are fine-tuned to predict social orientation tags on dialogue utterances.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (32)
  1. On the dangers of stochastic parrots: Can language models be too big? In Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, FAccT ’21, page 610–623, New York, NY, USA. Association for Computing Machinery.
  2. TweetNLP: Cutting-edge natural language processing for social media. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, pages 38–49, Abu Dhabi, UAE. Association for Computational Linguistics.
  3. Jonathan P. Chang and Cristian Danescu-Niculescu-Mizil. 2019. Trouble on the horizon: Forecasting the derailment of online conversations as they develop. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pages 4743–4754, Hong Kong, China. Association for Computational Linguistics.
  4. Thread with caution: Proactively helping users assess and deescalate tension in their online discussions. Proc. ACM Hum.-Comput. Interact., 6(CSCW2).
  5. CaSiNo: A corpus of campsite negotiation dialogues for automatic negotiation systems. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 3167–3185, Online. Association for Computational Linguistics.
  6. Frugalgpt: How to use large language models while reducing cost and improving performance.
  7. Unsupervised cross-lingual representation learning at scale. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 8440–8451, Online. Association for Computational Linguistics.
  8. COLD: A benchmark for Chinese offensive language detection. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, pages 11580–11599, Abu Dhabi, United Arab Emirates. Association for Computational Linguistics.
  9. In-context learning for few-shot dialogue state tracking.
  10. WikiConv: A corpus of the complete conversational history of a large online collaborative community. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pages 2818–2823, Brussels, Belgium. Association for Computational Linguistics.
  11. Measuring faithfulness in chain-of-thought reasoning.
  12. Groups and morality. In M. Mikulincer, P.R. Shaver, J.F. Dovidio, and J. Simpson, editors, APA Handbook of Personality and Social Psychology, Vol. 2: Group Processes, pages 123–149. American Psychological Association, Washington, DC.
  13. Deal or no deal? end-to-end learning of negotiation dialogues. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pages 2443–2453, Copenhagen, Denmark. Association for Computational Linguistics.
  14. Complementarity of interpersonal behaviors in dyadic interactions. Personality & social psychology bulletin, 29(9):1082–1090.
  15. OpenAI. 2023. Gpt-4 technical report.
  16. It takes two to lie: One to lie, and one to listen. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 3811–3854, Online. Association for Computational Linguistics.
  17. Emotion recognition in conversation: Research challenges, datasets, and recent advances.
  18. "why should i trust you?": Explaining the predictions of any classifier. In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD ’16, page 1135–1144, New York, NY, USA. Association for Computing Machinery.
  19. Are we on the same wavelength? interpersonal complementarity as shared cyclical patterns during interactions. Journal of Personality and Social Psychology, 97(6):1005–1020.
  20. Distilbert, a distilled version of bert: smaller, faster, cheaper and lighter.
  21. The structure of toxic conversations on twitter. In Proceedings of the Web Conference 2021, WWW ’21, pages 1086–1097, New York, NY, USA. Association for Computing Machinery.
  22. Proactive moderation of online discussions: Existing practices and the potential for algorithmic support. Proc. ACM Hum.-Comput. Interact., 6(CSCW2).
  23. Casa: Conversational aspect sentiment analysis for dialogue understanding. J. Artif. Int. Res., 73.
  24. Karen Spärck Jones. 1972. A statistical interpretation of term specificity and its application in retrieval. Journal of Documentation, 28(1):11–21.
  25. Włodzimierz Strus and Jan Cieciuch. 2017. Towards a synthesis of personality, temperament, motivation, emotion and mental health models within the circumplex of personality metatraits. Journal of Research in Personality, 66:70–95.
  26. Tracking satisfaction states for customer satisfaction prediction in E-commerce service chatbots. In Proceedings of the 29th International Conference on Computational Linguistics, pages 616–625, Gyeongju, Republic of Korea. International Committee on Computational Linguistics.
  27. delearyous: Training interpersonal communication skills using unconstrained text input. In Proceedings of ECGBL 2012, The 6th European Conference on Games Based Learning, volume 6, pages 505–513. ACAD CONFERENCES LTD.
  28. Frederik Vaassen and Walter Daelemans. 2011. Automatic emotion classification for interpersonal communication. In Proceedings of the 2nd Workshop on Computational Approaches to Subjectivity and Sentiment Analysis (WASSA 2.011), pages 104–110, Portland, Oregon. Association for Computational Linguistics.
  29. Attention is all you need. In Advances in Neural Information Processing Systems, volume 30. Curran Associates, Inc.
  30. Persuasion for good: Towards a personalized persuasive dialogue system for social good. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 5635–5649, Florence, Italy. Association for Computational Linguistics.
  31. Conversations gone awry: Detecting early signs of conversational failure. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 1350–1361, Melbourne, Australia. Association for Computational Linguistics.
  32. Conversational flow in Oxford-style debates. In Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 136–141, San Diego, California. Association for Computational Linguistics.

Summary

We haven't generated a summary for this paper yet.

Ai Sparkles Streamline Icon: https://streamlinehq.com Summarize Now
Youtube Logo Streamline Icon: https://streamlinehq.com

YouTube