mlsanityData to 14 Oct 2026

An Item Response Theory Framework for Persuasion

arXiv 2204.11337 ↗First posted 24 Apr 2022cs.CLcited by 5

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Abstract (arXiv)

In this paper, we apply Item Response Theory, popular in education and political science research, to the analysis of argument persuasiveness in language. We empirically evaluate the model's performance on three datasets, including a novel dataset in the area of political advocacy. We show the advantages of separating these components under several style and content representations, including evaluating the ability of the speaker embeddings generated by the model to parallel real-world observations about persuadability.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 10 of its 44 references that are in the map. First posted on arXiv 24 Apr 2022.

Builds on

10 of 44 references.

References · 10

  1. 2019Persuasion for Good: Towards a Personalized Persuasive Dialogue System for Social Goodcited by 209
  2. 2013Crowdsourcing a Word-Emotion Association Lexiconcited by 196
  3. 2016Winning Arguments: Interaction Dynamics and Persuasion Strategies in Good-faith Online Discussionscited by 110
  4. 2019A Large-scale Dataset for Argument Quality Ranking: Construction and Analysiscited by 67
  5. 2019Automatic Argument Quality Assessment -- New Datasets and Methodscited by 47
  6. 2017Argument Strength is in the Eye of the Beholder: Audience Effects in Persuasioncited by 35
  7. 2019Exploring the Role of Prior Beliefs for Argument Persuasioncited by 31
  8. 2019Are You Convinced? Choosing the More Convincing Evidence with a Siamese Networkcited by 29
  9. 2019A Corpus for Modeling User and Language Effects in Argumentation on Online Debatingcited by 23
  10. 2020Text-Based Ideal Pointscited by 22

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Cited by year

Citing papers per year: 2022: 1; 2023: 1; 2024: 2; 2025: 1.

5 papers.