Abstract
Online debates allow people to express their persuasive abilities and provide exciting opportunities for understanding persuasion. Prior studies have focused on studying persuasion in debate content, but without accounting for each debater’s history or exploring the progression of a debater’s persuasive ability. We study debater skill by modeling how participants progress over time in a collection of debates from Debate.org . We build on a widely used model of skill in two-player games and augment it with linguistic features of a debater’s content. We show that online debaters’ skill levels do tend to improve over time. Incorporating linguistic profiles leads to more robust skill estimation than winning records alone. Notably, we find that an interaction feature combining uncertainty cues (hedging) with terms strongly associated with either side of a particular debate (fightin’ words) is more predictive than either feature on its own, indicating the importance of fine- grained linguistic features.
Highlights
Persuasion is an important skill with prevalent use
We first show that the expertise of a debater can be better estimated with the linguistic profile, and analyze the contribution of different components
We introduced a method that uses a linguistic profile derived from a debater’s history of past debates to model their skill level as it changes over time
Summary
Persuasion is an important skill with prevalent use. Online debate communities offer an opportunity to investigate these questions. What linguistic phenomena are associated with higher levels of persuasive skill? These communities feature users who participate in multiple debates over their period of engagement. Such debates involve two parties who willingly and formally present divergent opinions before an audience. Unlike other media of persuasion, such as letters to politicians, there is a clear signal, a win or loss, indicating whether or not a debater was successful against the adversary. This work aims to quantify the skill level of each debater in an online community and investigates what factors contribute to expertise
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