# ConvoKit: A Toolkit for the Analysis of Conversations

arXiv: https://arxiv.org/abs/2005.04246 · HTML: https://mlsanity.com/paper/2005.04246/

## Key facts

- Cited by 72 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 May 2020.

## Built on by (most cited first, 30 of 72)

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- [Accounting for Agreement Phenomena in Sentence Comprehension with Transformer Language Models: Effects of Similarity-based Interference on Surprisal and Attention](https://mlsanity.com/paper/2104.12874/) (2021)
- ["They are uncultured": Unveiling Covert Harms and Social Threats in LLM Generated Conversations](https://mlsanity.com/paper/2405.05378/) (2024)
- [WildVis: Open Source Visualizer for Million-Scale Chat Logs in the Wild](https://mlsanity.com/paper/2409.03753/) (2024)
- [I Beg to Differ: A study of constructive disagreement in online conversations](https://mlsanity.com/paper/2101.10917/) (2021)
- [Idiosyncratic but not Arbitrary: Learning Idiolects in Online Registers Reveals Distinctive yet Consistent Individual Styles](https://mlsanity.com/paper/2109.03158/) (2021)
- [The R-U-A-Robot Dataset: Helping Avoid Chatbot Deception by Detecting User Questions About Human or Non-Human Identity](https://mlsanity.com/paper/2106.02692/) (2021)
- [Computationally Identifying Funneling and Focusing Questions in Classroom Discourse](https://mlsanity.com/paper/2208.04715/) (2022)
- [Proactive Moderation of Online Discussions: Existing Practices and the Potential for Algorithmic Support](https://mlsanity.com/paper/2211.16525/) (2022)
- [''Fifty Shades of Bias'': Normative Ratings of Gender Bias in GPT Generated English Text](https://mlsanity.com/paper/2310.17428/) (2023)
- [How Deep Is Representational Bias in LLMs? The Cases of Caste and Religion](https://mlsanity.com/paper/2508.03712/) (2025)
- [OdysSim: Building Foundation Models for Human Behavior Simulation](https://mlsanity.com/paper/2606.14199/) (2026)
- [Edu-ConvoKit: An Open-Source Library for Education Conversation Data](https://mlsanity.com/paper/2402.05111/) (2024)
- [Evaluating Decision Models for Text Annotation in Computational Social Science](https://mlsanity.com/paper/2609.24574/) (2026)
- [HANSEN: Human and AI Spoken Text Benchmark for Authorship Analysis](https://mlsanity.com/paper/2310.16746/) (2023)
- [An LLM Feature-based Framework for Dialogue Constructiveness Assessment](https://mlsanity.com/paper/2406.14760/) (2024)
- [What do Large Language Models Say About Animals? Investigating Risks of Animal Harm in Generated Text](https://mlsanity.com/paper/2503.04804/) (2025)
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- [The structure of online social networks modulates the rate of lexical change](https://mlsanity.com/paper/2104.05010/) (2021)
- [Opening up Minds with Argumentative Dialogues](https://mlsanity.com/paper/2301.06400/) (2023)
- [Learning User Simulators with Turing Rewards](https://mlsanity.com/paper/2606.19336/) (2026)
- [Co-Located Human-Human Interaction Analysis using Nonverbal Cues: A Survey](https://mlsanity.com/paper/2207.10574/) (2022)
- [Assessing the efficacy of large language models in generating accurate teacher responses](https://mlsanity.com/paper/2307.04274/) (2023)
- [Deal, or no deal (or who knows)? Forecasting Uncertainty in Conversations using Large Language Models](https://mlsanity.com/paper/2402.03284/) (2024)
- [How Did We Get Here? Summarizing Conversation Dynamics](https://mlsanity.com/paper/2404.19007/) (2024)
- [Sycophantic AI Decreases Prosocial Intentions and Promotes Dependence](https://mlsanity.com/paper/2510.01395/) (2025)
- [Can Unsupervised Knowledge Transfer from Social Discussions Help Argument Mining?](https://mlsanity.com/paper/2203.12881/) (2022)

## Abstract (arXiv)

This paper describes the design and functionality of ConvoKit, an open-source toolkit for analyzing conversations and the social interactions embedded within. ConvoKit provides an unified framework for representing and manipulating conversational data, as well as a large and diverse collection of conversational datasets. By providing an intuitive interface for exploring and interacting with conversational data, this toolkit lowers the technical barriers for the broad adoption of computational methods for conversational analysis.