Measuring Offensive Speech in Online Political Discourse
This addresses the issue of online harassment and polarization in political forums, which is incremental as it applies existing methods to new data.
The paper tackles the problem of offensive speech in online political discourse by developing a classifier to measure offensiveness, finding that political discussions are more offensive than general ones, based on analysis of over 168M Reddit comments.
The Internet and online forums such as Reddit have become an increasingly popular medium for citizens to engage in political conversations. However, the online disinhibition effect resulting from the ability to use pseudonymous identities may manifest in the form of offensive speech, consequently making political discussions more aggressive and polarizing than they already are. Such environments may result in harassment and self-censorship from its targets. In this paper, we present preliminary results from a large-scale temporal measurement aimed at quantifying offensiveness in online political discussions. To enable our measurements, we develop and evaluate an offensive speech classifier. We then use this classifier to quantify and compare offensiveness in the political and general contexts. We perform our study using a database of over 168M Reddit comments made by over 7M pseudonyms between January 2015 and January 2017 -- a period covering several divisive political events including the 2016 US presidential elections.