Breaking Down the Invisible Wall of Informal Fallacies in Online Discussions

Saumya Yashmohini Sahai, Oana Denisa Balalau, Roxana Horincar

Abstract:

People debate on a variety of topics on online
platforms such as Reddit, or Facebook. De-
bates can be lengthy, with users exchanging
a wealth of information and opinions. How-
ever, conversations do not always go smoothly,
and users sometimes engage in unsound argu-
mentation techniques to prove a claim. These
techniques are called fallacies. Fallacies are
persuasive arguments that provide insufficient
or incorrect evidence to support the claim. In
this paper, we study the most frequent falla-
cies on Reddit, and we present them using
the pragma-dialectical theory of argumenta-
tion. We construct a new annotated dataset of
fallacies, using user comments containing fal-
lacy mentions as noisy labels, and cleaning the
data via crowdsourcing. Finally, we study the
task of classifying fallacies using neural mod-
els. We find that generally the models perform
better in the presence of conversational con-
text.We have released the data and the code
at github.com/sahaisaumya/informal_
fallacies.