← Volume 12: Challenges and Perspectives of Hate Speech Research
Linguistic limits to the detection of hate speech
DOI 10.48541/dcr.v12.19 (SSOAR)
Abstract: As long as we have attempted to sanction untoward speech, others have devised strategies for expressing themselves while dodging such sanctions. In this intervention, I review the arms race between technological filters designed to curb hate speech, and evasive language practices designed to avoid detection by these filters. I argue that, following important advances in the detection of relatively overt uses of hate speech, further advances will need to address hate speech that relies on culturally or situationally available context knowledge and linguistic ambiguities to convey its intended offenses. Resolving such forms of hate speech not only poses increasingly unreasonable demands on available data and technologies, but does so for limited, uncertain gains, as many evasive uses of language effectively defy unique valid classification.
Christian Baden is Associate Professor at the Department of Communication and Journalism at the Hebrew University of Jerusalem, Israel.
Baden, C. (2023). Evasive offenses: Linguistic limits to the detection of hate speech. In C. Strippel, S. Paasch-Colberg, M. Emmer, & J. Trebbe (Eds.), Challenges and perspectives of hate speech research (pp. 319–332). Digital Communication Research. https://doi.org/10.48541/dcr.v12.19
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