Lexical blending and dehumanisation in misogynistic hate speech: A cognitive, corpus‑assisted study of foid

• The blend foid shows ‑oid as the parameter shaping mechanistic dehumanisation. • Verb patterns reveal sexualised harm when foid is an object and low‑agency framing when it is a subject. • Modifiers reinforce dual dehumanisation, combining animalistic vilification with mechanistic objectification. • Fine‑grained analysis of foid + be highlights definitional environments tied to dehumanising attributes. • Granular corpus evidence supports a usage‑based definition distinguishing mechanistic and animalistic senses. NIncel discourse constitutes a form of online hate speech against women, mainly located in the digital manosphere and specific forums. It is characterised by extremist misogyny and recurrent self-victimisation, whereby incels frame themselves as powerless and dominated by women. This study examines the relationship between incel language and emotion by analysing dehumanization strategies through a cognitive corpus-assisted approach. The Incelcor corpus, consisting of 229 posts retrieved from incel forums, was compiled for this purpose. The analysis focuses on the blend foid ( female + android ). Corpus-assisted discourse analysis was combined with cognitive linguistics to examine the behaviour of the blend when it acts as subject/object and the interaction with its modifiers. Besides, cognitive modelling has been addressed in order to explore the granular dimension of the term under study. With the linguistic evidence and instances, a usage-based dictionary entry has been proposed distinguishing the two folded dehumanization strategies identified in the blend. Linguistic evidence reflects that incels made use of victimization in their speech, and their perpetration of linguistic and symbolic violence lies on these mechanisms of dehumanization and victimization. Granularity played a key role in the study of this salient term as it allowed to zoom on the lexical and discursive levels, also capturing elaboration through the study of collocational patterns. There are limitations that should be acknowledged like the corpus size, the specialized dataset and the absence of experimental measurements that empirically linked language and emotions.

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Publication Details

Journal
Applied Corpus Linguistics
Published
2026-04-15
DOI
https://doi.org/10.1016/j.acorp.2026.100211
Primary Topic
Hate Speech and Cyberbullying Detection
Type
article
Field-Weighted Citation Impact
0.00

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article

Lexical blending and dehumanisation in misogynistic hate speech: A cognitive, corpus‑assisted study of foid

Antonio Jesús Tinedo Rodríguez
Applied Corpus Linguistics
Hate Speech and Cyberbullying Detection
article

Lexical blending and dehumanisation in misogynistic hate speech: A cognitive, corpus‑assisted study of foid

Antonio Jesús Tinedo Rodríguez
article en

Abstract

• The blend foid shows ‑oid as the parameter shaping mechanistic dehumanisation. • Verb patterns reveal sexualised harm when foid is an object and low‑agency framing when it is a subject. • Modifiers reinforce dual dehumanisation, combining animalistic vilification with mechanistic objectification. • Fine‑grained analysis of foid + be highlights definitional environments tied to dehumanising attributes. • Granular corpus evidence supports a usage‑based definition distinguishing mechanistic and animalistic senses. NIncel discourse constitutes a form of online hate speech against women, mainly located in the digital manosphere and specific forums. It is characterised by extremist misogyny and recurrent self-victimisation, whereby incels frame themselves as powerless and dominated by women. This study examines the relationship between incel language and emotion by analysing dehumanization strategies through a cognitive corpus-assisted approach. The Incelcor corpus, consisting of 229 posts retrieved from incel forums, was compiled for this purpose. The analysis focuses on the blend foid ( female + android ). Corpus-assisted discourse analysis was combined with cognitive linguistics to examine the behaviour of the blend when it acts as subject/object and the interaction with its modifiers. Besides, cognitive modelling has been addressed in order to explore the granular dimension of the term under study. With the linguistic evidence and instances, a usage-based dictionary entry has been proposed distinguishing the two folded dehumanization strategies identified in the blend. Linguistic evidence reflects that incels made use of victimization in their speech, and their perpetration of linguistic and symbolic violence lies on these mechanisms of dehumanization and victimization. Granularity played a key role in the study of this salient term as it allowed to zoom on the lexical and discursive levels, also capturing elaboration through the study of collocational patterns. There are limitations that should be acknowledged like the corpus size, the specialized dataset and the absence of experimental measurements that empirically linked language and emotions.

Applied Corpus LinguisticsVol. 6(2)
University of Córdoba (ES)
Agencia Estatal de Investigación, Universidad de Córdoba
Gender equality
Openalex Percentile: Top 13%
Hate Speech and Cyberbullying Detection
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