Detecting Persuasive Arguments based on Author-Reader Personality Traits and their Interaction

ABSTRACT

Persuasion is one of the most frequent, albeit challenging, tasks in human interaction. In a textual argument, one party (author) aims to change the view of the other party (reader). In this paper, we propose to detect persuasive textual arguments while considering the parties personality traits. We find that we can substantially improve accuracy by introducing features that capture author-reader personality traits and their interaction. Our model improves performance of state-of-the-art baselines from 66% to 71% on a new dataset of more than 19K arguments we collected.

References

1. N. H. Anderson. 1971. Integration theory and attitude change. Psychological Review 78, 3 (1971), 171--206.
2. Jilin Chen, Gary Hsieh, Jalal U Mahmud, and Jeffrey Nichols. 2014. Understanding individuals' personal values from social media word use. In Proceedings of the 17th ACM conference on Computer supported cooperative work & social computing. ACM, 405--414.
3. Susan Conroy, Carmine M. Pariante, Maureen N. Marks, Helen A. Davies, Simone Farrelly, Robin Schacht, and Paul Moran. 2012. Maternal Psychopathology and Infant Development at 18 Months: The Impact of Maternal Personality Disorder and Depression. Journal of the American Academy of Child & Adolescent Psychiatry 51 (04 2012), 51--61.
4. John M Digman. 1990. Personality structure: Emergence of the five-factor model. Annual review of psychology 41, 1 (1990), 417--440.
5. Esin Durmus and Claire Cardie. 2018. Exploring the Role of Prior Beliefs for Argument Persuasion. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers). Association for Computational Linguistics, 1035--1045. http://aclweb.org/anthology/N18--1094
6. Raymond L. Falcione. 1974. The factor structure of source credibility scales for immediate superiors in the organizational context. Central States Speech Journal 25, 1 (1974), 63--66.
7. Alan S. Gerber, Gregory A. Huber, David Doherty, Conor M. Dowling, and Costas Panagopoulos. 2013. Big Five Personality Traits and Responses to Persuasive Appeals: Results from Voter Turnout Experiments. Political Behavior 35, 4 (2013), 687--728.
8. Ivan Habernal and Iryna Gurevych. 2016. Which argument is more convincing? Analyzing and predicting convincingness of Web arguments using bidirectional LSTM. In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Association for Computational Linguistics, 1589--1599.
9. Jonathan Herzig, Guy Feigenblat, Michal Shmueli-Scheuer, David Konopnicki, and Anat Rafaeli. 2016. Predicting Customer Satisfaction in Customer Support Conversations in Social Media Using Affective Features. In Proceedings of the 2016 Conference on User Modeling Adaptation and Personalization, UMAP 2016, Halifax, NS, Canada, July 13 - 17, 2016. 115--119.
10. Jacob Hirsh, Sonia K Kang, and Galen Bodenhausen. 2012. Personalized Persuasion: Tailoring Persuasive Appeals to Recipients' Personality Traits. Psychological science 23 (04 2012), 578--81.
11. Anthony Hunter. 2016. Computational Persuasion with Applications in Behaviour Change. In Computational Models of Argument - Proceedings of COMMA 2016, Potsdam, Germany, 12--16 September, 2016. 5--18.
12. Yoon Kim. 2014. Convolutional Neural Networks for Sentence Classification. In Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, EMNLP 2014, October 25--29, 2014, Doha, Qatar, A meeting of SIGDAT, a Special Interest Group of the ACL. 1746--1751.
13. Zhe Liu, Anbang Xu, YiWang, Jerald Schoudt, Jalal Mahmud, and Rama Akkiraju. 2017. Does Personality Matter?: A Study of Personality and Situational Effects on Consumer Behavior. In Proceedings of the 28th ACM Conference on Hypertext and Social Media, HT 2017, Prague, Czech Republic, July 4--7, 2017. 185--193.
14. Stephanie Lukin, Pranav Anand, Marilyn Walker, and Steve Whittaker. 2017. Argument Strength is in the Eye of the Beholder: Audience Effects in Persuasion. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers. Association for Computational Linguistics, 742--753. http://aclweb.org/anthology/E17--1070
15. Shaul Oreg and Noga Sverdlik. 2014. Source Personality and Persuasiveness: Big Five Predispositions to Being Persuasive and the Role of Message Involvement. Journal of Personality 82, 3 (2014), 250--264.
16. Sara Rosenthal and Kathy McKeown. 2016. Social Proof: The Impact of Author Traits on Influence Detection. In Proceedings of the First Workshop on NLP and Computational Social Science. Association for Computational Linguistics, 27--36.
17. Edwin D Simpson and Iryna Gurevych. 2018. Finding Convincing Arguments Using Scalable Bayesian Preference Learning. Transactions of the Association for Computational Linguistics 6 (2018), 357--371. http://aclweb.org/anthology/ Q18--1026
18. Chenhao Tan, Vlad Niculae, Cristian Danescu-Niculescu-Mizil, and Lillian Lee. 2016. Winning Arguments: Interaction Dynamics and Persuasion Strategies in Good-faith Online Discussions. In Proceedings of the 25th International Conference on World Wide Web (WWW '16). 613--624.
19. Zhongyu Wei, Yang Liu, and Yi Li. 2016. Is This Post Persuasive? Ranking Argumentative Comments in Online Forum. In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, ACL 2016, August 7--12, 2016, Berlin, Germany, Volume 2: Short Papers.

Index Terms

• Computing methodologies

  • Modeling and simulation

• Human-centered computing

  • Human computer interaction (HCI)

    • HCI design and evaluation methods

      • User models