mlsanityData to 7 Oct 2026

Persuasive Natural Language Generation -- A Literature Review

arXiv 2101.05786 ↗First posted 14 Jan 2021cs.CL cs.AIcited by 10

Not on the map. Why?

Abstract (arXiv)

This literature review focuses on the use of Natural Language Generation (NLG) to automatically detect and generate persuasive texts. Extending previous research on automatic identification of persuasion in text, we concentrate on generative aspects through conceptualizing determinants of persuasion in five business-focused categories: benevolence, linguistic appropriacy, logical argumentation, trustworthiness, tools and datasets. These allow NLG to increase an existing message's persuasiveness. Previous research illustrates key aspects in each of the above mentioned five categories. A research agenda to further study persuasive NLG is developed. The review includes analysis of seventy-seven articles, outlining the existing body of knowledge and showing the steady progress in this research field.

Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). Builds on 8 of its 90 references that are in the map. First posted on arXiv 14 Jan 2021.

Builds on

8 of 90 references.

References · 8

  1. 2019Persuasion for Good: Towards a Personalized Persuasive Dialogue System for Social Goodcited by 207
  2. 2016Winning Arguments: Interaction Dynamics and Persuasion Strategies in Good-faith Online Discussionscited by 106
  3. 2020DebateSum: A large-scale argument mining and summarization datasetcited by 34
  4. 2020Exploring the Role of Argument Structure in Online Debate Persuasioncited by 26
  5. 2018Cross-lingual Argumentation Mining: Machine Translation (and a bit of Projection) is All You Need!cited by 15
  6. 2019An Unsupervised Domain-Independent Framework for Automated Detection of Persuasion Tactics in Textcited by 9
  7. 2015Echoes of Persuasion: The Effect of Euphony in Persuasive Communicationcited by 5
  8. 2019Experiments in Detecting Persuasion Techniques in the Newscited by 3

Built on by

Cited by year (2026 to 7 Oct)

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

10 papers.

  1. 2023Co-Writing with Opinionated Language Models Affects Users' Viewscited by 145
  2. 2023The Persuasive Power of Large Language Modelscited by 46
  3. 2022Law Informs Code: A Legal Informatics Approach to Aligning Artificial Intelligence with Humanscited by 23
  4. 2022Social Influence Dialogue Systems: A Survey of Datasets and Models For Social Influence Taskscited by 14
  5. 2022Innovations in Neural Data-to-text Generation: A Surveycited by 10
  6. 2023Audience-Centric Natural Language Generation via Style Infusioncited by 5
  7. 2024The Future of Cognitive Strategy-enhanced Persuasive Dialogue Agents: New Perspectives and Trendscited by 4
  8. 2022A Comprehensive Survey of Natural Language Generation Advances from the Perspective of Digital Deceptioncited by 1
  9. 2025A Generalizable Rhetorical Strategy Annotation Model Using LLM-based Debate Simulation and Labellingcited by 1
  10. 2026Can AI-Generated Persuasion Be Detected? Persuaficial Benchmark and AI vs. Human Linguistic Differencescited by 1