  Public debate forums provide a common platform for exchanging opinions on a
topic of interest. While recent studies in natural language processing (NLP)
have provided empirical evidence that the language of the debaters and their
patterns of interaction play a key role in changing the mind of a reader,
research in psychology has shown that prior beliefs can affect our
interpretation of an argument and could therefore constitute a competing
alternative explanation for resistance to changing one's stance. To study the
actual effect of language use vs. prior beliefs on persuasion, we provide a new
dataset and propose a controlled setting that takes into consideration two
reader level factors: political and religious ideology. We find that prior
beliefs affected by these reader level factors play a more important role than
language use effects and argue that it is important to account for them in NLP
studies of persuasion.

Computation and Language;Artificial Intelligence