Changing Views: Persuasion Modeling and Argument Extraction from Online Discussions
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Abstract (arXiv)
Persuasion and argumentation are possibly among the most complex examples of the interplay between multiple human subjects. With the advent of the Internet, online forums provide wide platforms for people to share their opinions and reasonings around various diverse topics. In this work, we attempt to model persuasive interaction between users on Reddit, a popular online discussion forum. We propose a deep LSTM model to classify whether a conversation leads to a successful persuasion or not, and use this model to predict whether a certain chain of arguments can lead to persuasion. While learning persuasion dynamics, our model tends to identify argument facets implicitly, using an attention mechanism. We also propose a semi-supervised approach to extract argumentative components from discussion threads. Both these models provide useful insight into how people engage in argumentation on online discussion forums.
Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). First posted on arXiv 13 Jul 2019.
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Citing papers per year: 2021: 1; 2022: 3; 2023: 1; 2024: 1; 2025: 2; 2026: 3.
11 papers.
- 2022Hate Speech and Counter Speech Detection: Conversational Context Does Mattercited by 32
- 2025Must Read: A Comprehensive Survey of Computational Persuasioncited by 12
- 2021Reddit Entity Linking Datasetcited by 7
- 2022Can Unsupervised Knowledge Transfer from Social Discussions Help Argument Mining?cited by 5
- 2022Multilingual Persuasion Detection: Video Games as an Invaluable Data Source for NLPcited by 4
- 2024Hatred Stems from Ignorance! Distillation of the Persuasion Modes in Countering Conversational Hate Speechcited by 2
- 2025A Hybrid Theory and Data-driven Approach to Persuasion Detection with Large Language Modelscited by 2
- 2026Can AI-Generated Persuasion Be Detected? Persuaficial Benchmark and AI vs. Human Linguistic Differencescited by 1
- 2023Enhancing AI Research Paper Analysis: Methodology Component Extraction using Factored Transformer-based Sequence Modeling Approachcited by 0
- 2026The GDN-CC Dataset: Automatic Corpus Clarification for AI-enhanced Democratic Citizen Consultationscited by 0
- 2026A Model of Multi-turn Human Persuadability Using Probabilistic Belief Tracingcited by 0
- 2026A Model of Multi-turn Human Persuadability Using Probabilistic Belief Tracing3 Jun 2026
- 2026The GDN-CC Dataset: Automatic Corpus Clarification for AI-enhanced Democratic Citizen Consultations21 Jan 2026
- 2026Can AI-Generated Persuasion Be Detected? Persuaficial Benchmark and AI vs. Human Linguistic Differences8 Jan 2026
- 2025A Hybrid Theory and Data-driven Approach to Persuasion Detection with Large Language Models27 Nov 2025
- 2025Must Read: A Comprehensive Survey of Computational Persuasion12 May 2025
- 2024Hatred Stems from Ignorance! Distillation of the Persuasion Modes in Countering Conversational Hate Speech18 Mar 2024
- 2023Enhancing AI Research Paper Analysis: Methodology Component Extraction using Factored Transformer-based Sequence Modeling Approach5 Nov 2023
- 2022Multilingual Persuasion Detection: Video Games as an Invaluable Data Source for NLP10 Jul 2022
- 2022Hate Speech and Counter Speech Detection: Conversational Context Does Matter13 Jun 2022
- 2022Can Unsupervised Knowledge Transfer from Social Discussions Help Argument Mining?24 Mar 2022
- 2021Reddit Entity Linking Dataset4 Jan 2021