Detecting persuasive arguments based on author-reader personality traits and their interaction

Michal Shmueli-Scheuer; Jonathan Herzig; David Konopnicki; Tommy Sandbank

doi:10.1145/3320435.3320467

Detecting persuasive arguments based on author-reader personality traits and their interaction

Michal Shmueli-Scheuer, Jonathan Herzig, David Konopnicki, Tommy Sandbank

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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.

Original language	English
Title of host publication	ACM UMAP 2019 - Proceedings of the 27th ACM Conference on User Modeling, Adaptation and Personalization
Publisher	Association for Computing Machinery, Inc
Pages	211-215
Number of pages	5
ISBN (Electronic)	9781450360210
DOIs	https://doi.org/10.1145/3320435.3320467
State	Published - 7 Jun 2019
Externally published	Yes
Event	27th ACM Conference on User Modeling, Adaptation and Personalization, UMAP 2019 - Larnaca, Cyprus Duration: 9 Jun 2019 → 12 Jun 2019

Publication series

Name	ACM UMAP 2019 - Proceedings of the 27th ACM Conference on User Modeling, Adaptation and Personalization

Conference

Conference	27th ACM Conference on User Modeling, Adaptation and Personalization, UMAP 2019
Country/Territory	Cyprus
City	Larnaca
Period	9/06/19 → 12/06/19

Keywords

Personality traits
Persuasion
Social media

Access to Document

10.1145/3320435.3320467

Cite this

Shmueli-Scheuer, M., Herzig, J., Konopnicki, D., & Sandbank, T. (2019). Detecting persuasive arguments based on author-reader personality traits and their interaction. In ACM UMAP 2019 - Proceedings of the 27th ACM Conference on User Modeling, Adaptation and Personalization (pp. 211-215). (ACM UMAP 2019 - Proceedings of the 27th ACM Conference on User Modeling, Adaptation and Personalization). Association for Computing Machinery, Inc. https://doi.org/10.1145/3320435.3320467

Shmueli-Scheuer, Michal ; Herzig, Jonathan ; Konopnicki, David ; Sandbank, Tommy. / Detecting persuasive arguments based on author-reader personality traits and their interaction. ACM UMAP 2019 - Proceedings of the 27th ACM Conference on User Modeling, Adaptation and Personalization. Association for Computing Machinery, Inc, 2019. pp. 211-215 (ACM UMAP 2019 - Proceedings of the 27th ACM Conference on User Modeling, Adaptation and Personalization).

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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.",

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Shmueli-Scheuer, M, Herzig, J, Konopnicki, D & Sandbank, T 2019, Detecting persuasive arguments based on author-reader personality traits and their interaction. in ACM UMAP 2019 - Proceedings of the 27th ACM Conference on User Modeling, Adaptation and Personalization. ACM UMAP 2019 - Proceedings of the 27th ACM Conference on User Modeling, Adaptation and Personalization, Association for Computing Machinery, Inc, pp. 211-215, 27th ACM Conference on User Modeling, Adaptation and Personalization, UMAP 2019, Larnaca, Cyprus, 9/06/19. https://doi.org/10.1145/3320435.3320467

Detecting persuasive arguments based on author-reader personality traits and their interaction. / Shmueli-Scheuer, Michal; Herzig, Jonathan; Konopnicki, David; Sandbank, Tommy.

ACM UMAP 2019 - Proceedings of the 27th ACM Conference on User Modeling, Adaptation and Personalization. Association for Computing Machinery, Inc, 2019. p. 211-215 (ACM UMAP 2019 - Proceedings of the 27th ACM Conference on User Modeling, Adaptation and Personalization).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Shmueli-Scheuer M, Herzig J, Konopnicki D, Sandbank T. Detecting persuasive arguments based on author-reader personality traits and their interaction. In ACM UMAP 2019 - Proceedings of the 27th ACM Conference on User Modeling, Adaptation and Personalization. Association for Computing Machinery, Inc. 2019. p. 211-215. (ACM UMAP 2019 - Proceedings of the 27th ACM Conference on User Modeling, Adaptation and Personalization). https://doi.org/10.1145/3320435.3320467

Detecting persuasive arguments based on author-reader personality traits and their interaction

Abstract

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Conference

Keywords

Access to Document

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