Master Thesis Defense on "Exploring consensus-mediating arguments in online debates" (Thu, Oct 12, 9:00am)

Student:  Andreas Kaas Johansen

Date and Time:  09:00am, Thursday, 12th October 2017

Place: Knuth room, SICS, Electrum building 6th floor

Examiner:  Šarūnas Girdzijauskas

Academic Supervisor: Vladimir Vlassov

Industrial Supervisor: Magnus Sahlgren

Title: Exploring consensus-mediating arguments in online debates

Abstract
This work presents a first venture into the search for features that define the rhetorical strategy known as Rogerian rhetoric. Rogerian Rhetoric is a conflict-solving rhetorical strategy intended to find common ground instead of polarizing debates further by presenting strong arguments and counter arguments, as is often done in debates.
That goal of the thesis is to lay the ground work, a feature exploration and evaluation of machine learning in this domain, for others tempted to model consensus-mediating arguments.
In order to evaluate different sets of features statistical testing is applied to test if the distribution of certain features differ over consensus-mediating comments compared to non-consensus mediating comments. Machine Learning in this domain is evaluated using support vector machines and different featuresets. 
The results show that on this data the consensus-mediating comments do have some characteristics that differ from other comments, some of which may generalize across debates. Next, as consensus-mediating arguments proved to be rar, these comments are a minority class, and in order to classify them using machine learning techniques overfitting needs to be addressed, the results suggest that the strategy applied to deal with overfitting is highly important. Finally the feature “polarity” is suggested and the evaluation shows that the hand-annotated comments as well as false-positives found by machine learning models in other debates have significantly lower “polarity” than non-consensus-mediating comments.
Due to the bias inherent in the hand annotated dataset the results should be considered provisional, more studies using debates from more domains with either expert or crowdsourced annotations are necessary to take the research further and produce results that generalize well.