Measuring Offensive Speech in Online Political Discourse
June 06, 2017 ยท Declared Dead ยท ๐ FOCI @ USENIX Security Symposium
"No code URL or promise found in abstract"
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Authors
Rishab Nithyanand, Brian Schaffner, Phillipa Gill
arXiv ID
1706.01875
Category
cs.CL: Computation & Language
Cross-listed
cs.CY,
cs.SI
Citations
23
Venue
FOCI @ USENIX Security Symposium
Last Checked
3 months ago
Abstract
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.
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