Changing views: Persuasion modeling and argument extraction from online discussions

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...

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Bibliographic Details
Published in:Information processing & management 2020-03, Vol.57 (2), p.102085, Article 102085
Main Authors: Dutta, Subhabrata, Das, Dipankar, Chakraborty, Tanmoy
Format: Article
Language:English
Subjects:
Argument mining
Attention mechanism
Cognition & reasoning
Deep LSTM
Dynamic time warping distance
Internet
Logic
Persuasion modeling
Social media
Social networks
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Summary: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.
ISSN:0306-4573
1873-5371
DOI:10.1016/j.ipm.2019.102085