GO BACK TO /R/CONSPIRACY: AN EXPLORATION OF METHODS FOR THE AUTOMATIC DETECTION OF AFFECTIVE POLARIZATION ON REDDIT
Abstract
Affective polarization – the tendency to hold negative attitudes towards an out-group and biased, positive
attitudes towards an in-group – is a hot topic in research and public debate. There are concerns that news
media’s tendency to focus on political conflict rather than issues is causing polarization to increase, but
researchers lack methods to automatically asses levels of polarization in online debates and correlate them
with news articles. This study examines the appropriateness of using Reddit Karma, word embeddings and
existing NLP tools for automatic detection of affective polarization in discussions on Reddit. To achieve this,
we collect and manually annotate Reddit discussions for expressions of affective polarization and fit multiple
logistic regression models on the discussion features and metadata. We find a strong correlation between the
probability to encounter expressions of affective polarization in the data and both word embeddings and the
confidence scores of toxicity detection. We also find that patterns in the comment votes are good predictors
of disagreement in the discussions. Moreover, we present a data set of Reddit-discussions about topics
related to the covid-19 pandemic which can be used in further attempts to automatically detect affective
polarization in interactive discourse on social media.
Degree
Student essay
Collections
View/ Open
Date
2022-10-06Author
Båstedt, Klara
Keywords
affective polarization, covid-19, social media, Reddit, NLP
Language
eng