Online Incel Speech (Hate Speech/Incivility)

Abstract

Involuntarily celibate men (Incels) form online communities in which they “often bemoan their lack of a loving relationship with a woman while simultaneously dehumanizing women and calling for misogynistic violence” (Glace et al., 2021, p. 288). Several studies investigate this dehumanization and misogyny including (gendered) hate speech in online comments from Incels (e.g., Glace et al., 2021). However, not all online comments from Incels contain misogyny or gendered hate speech. To get a better understanding of the phenomenon of Incels, it would be better to not only focus on these problematic comments. Thus, we propose a new construct called “Online Incel speech”, which is defined as the sum of all online comments from Incels that are related to Inceldom, that is, being or becoming an Incel.

In an approach to provide an extensive system of categorization, Grau Chopite (2022) synthesized codebooks from several studies on Incels (see example studies table note) and put it to an empirical test. She found that most Incel comments found online can be categorized into three subdimensions. The first two subdimensions cover framing by Incels, namely how Incels frame the subjective causes of becoming an Incel and how they frame the subjective emotional consequences of being an Incel. Both subdimensions can also be interpreted as part of a subjective theory (sensu Groeben et al., 1988) of Inceldom. In contrast to this, the third subdimension does not consist of framing, but of observable verbal behaviors, which are often linked to gendered hate speech.

When trying to categorize online comments from Incels, former studies often applied the construct “Hybrid Masculinities” (e.g., Glace et al, 2021). This construct from Bridge and Pascoe (2014) suggests that “some men develop masculinities which appear to subvert, but actually reaffirm, White hegemonic masculinities” (Glace et al., 2021, p. 289). Glace et al. (2021) structure the construct into three subdimensions, namely (1) discursive distancing (claiming distance from hegemonic masculine roles without actually relinquishing masculine power), (2) strategic borrowing (appropriating the cultures of nondominant groups of men), and (3) fortifying boundaries (continually using hegemonic standards to constrain masculinity and demeaning men who fail to meet them). However, the construct only covers a part of Inceldom, which Glace et al. (2021) indirectly acknowledge by adding two inductive categories, that is, hostile sexism (shaming and degrading women) and suicidality (reporting suicidal thoughts, feelings, and intentions).

Field of application/theoretical foundation:

The construct “Online Incel speech” was coined by Grau Chopite (2022), and there are currently no other studies making use of it. However, there are studies (e.g., Vu & Lynn, 2020; also see the entry “Frames (Automated Content Analysis”) based on the framing theory by Entman (1991) where the subdimension “subjective causes” would correspond to Entman’s “causal interpretation frame”, while the “subjective emotional consequences” would correspond to Entman’s “problem definition frame”. The “subjective causes” also correspond to the “discursive distancing” and the “emotional consequences” to “suicidality” in the construct of Hybrid Masculinities.

The third subdimension “verbal behavior” corresponds to gendered online hate speech (e.g., Döring & Mohseni, 2019), but also to “hostile sexism” and “fortifying boundaries” in the construct of Hybrid Masculinities. 

References/combination with other methods:

The study by Grau Chopite (2022) employs a quantitative manual content analysis using a deductive approach. Studies based on the construct of Hybrid Masculinities also employ manual online content analyses or manual thematic analyses, but those are often qualitative in nature (e.g., Glace et al., 2021).

Framing is also often assessed with manual content analyses (e.g., Nitsch & Lichtenstein, 2019), but newer studies try to assess it computationally (e.g., Vu & Lynn, 2020). Hate speech is often assessed with manual content analyses (e.g., Döring & Mohseni, 2019) and surveys (e.g., Oksanen et al., 2014), but some newer studies try to assess it computationally (e.g., Al-Hassan & Al-Dossari, 2019).

As Online Incel Speech is related to framing and gendered hate speech, it seems plausible that manual content analyses of Online Incel Speech could be combined with computational analyses, too, to enable the investigation of large samples. However, computational analyses of subtle forms of verbal behavior can be challenging because the number of wrong categorizations increases (e.g., for sexism detection see Samory et al., 2021; for hate speech detection see Ruiter et al., 2022).

Example studies:

Example study	Construct	Dimensions	Explanation	Reliability
Online Incel speech
Grau Chopite (2022)	Subjective Causes of Inceldom	Race/Ethnicity	having certain racial features and/or belonging to a certain ethnic	κ = .55; AC1 = .80
		Mental Health	suffering from any mental health issue	κ = .58; AC1 = .90
		Employment	difficulties with getting and/or maintaining employment; experiencing dissatisfaction in the workplace	κ = .85; AC1 = .98
		Family	having family issues (e.g., an abusive family member)	κ = .66; AC1 = .98
	Subjective Emotional Consequences of Inceldom	Hopelessness	expressing hopelessness	κ = .37; AC1 = .89
		Sadness	expressing sadness	κ = .26; AC1 = .91
		Suicidality	expressing suicidality	κ = .24; AC1 = .95
		Anger	expressing anger	κ = .44; AC1 = .87
		Hatred	expressing hatred	κ = .40; AC1 = .83
	Verbal Behavior of Incels	Using Gendered Hate Speech Against Women	hostile sexism against women and misogynistic speech	κ = .80; AC1 = .87
		Adopting Social Justice Language	claiming unfairness/ injustice of being discriminated by society or groups (e.g., other men, other races)	κ = .48; AC1 = .82
		Claiming Lack of Masculine Traits	lacking masculine traits (e.g., muscles, a big penis)	κ = .62; AC1 = .86
		Shaming Other Men	shaming of other men directly by calling them terms related to being “effeminate” or “unmanly”	κ = .71; AC1 = .91
		Claiming Lack of Female Interest	being unable to attract women or being rejected by women	κ = .61; AC1 = .87
Hybrid Masculinities
Glace et al. (2021)	Discursive Distancing	Lack of Female Interest	claiming a lack of ability to attract female romantic companionship and sexual interest	n/a
		Lack of Masculine Traits	claiming a lack of traditionally attractive masculine physical traits	n/a
	Strategic Borrowing	Race and Racism	appropriating the culture of racial and ethnic minority men	n/a
		Social Justice Language	using the language of the marginalized to diminish one’s own position of power	n/a
	Fortifying Boundaries	Soyboys	deriding non-Incel men as weak and desperate	n/a
		Cucks	deriding non-Incel men as being cheated or exploited by women	n/a
	Hostile Sexism	Women are Ugly	deriding women for being unattractive	n/a
		Slut-Shaming	deriding women for having sex	n/a
		False Rape Claims	claiming that women make false rape claims (e.g., when approached by an Incel)	n/a
		Women’s Only Value is Sex	claiming that women’s only value is their sexuality	n/a
		Women are Subhuman	dehumanizing women	n/a
	Suicidality	Due to Incel Experience	attributing suicidal thoughts, feelings, and intentions to Incel status	n/a
		The “Clown World”	claiming that the world is meaningless and nonsensical	n/a

Note: The codebook from Grau Chopite (2022) is based on the codebook and findings of Glace et al. (2021) and other studies (Baele et al., 2019; Bou-Franch & Garcés-Conejos Blitvich, 2021; Bridges & Pascoe, 2014; Cottee, 2020; Döring & Mohseni, 2019; D’Souza et al., 2018; Marwick & Caplan, 2018; Mattheis & Waltman, 2021; Maxwell et al., 2020; Rogers et al., 2015; Rouda & Siegel, 2020; Scaptura & Boyle, 2019; Williams & Arntfield, 2020; Williams et al., 2021). Gwet’s AC1 was calculated in addition to Cohen’s Kappa because some categories were rarely coded, which biases Cohen’s Kappa. The codebook is available at http://doi.org/10.23668/psycharchives.5626

References

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Baele, S. J., Brace, L., & Coan, T. G. (2019). From “Incel” to “Saint”: Analyzing the violent worldview behind the 2018 Toronto attack. Terrorism and Political Violence, 1–25. doi:10.1080/09546553.2019.1638256

Bou-Franch, P., & Garcés-Conejos Blitvich, P. (2021). Gender ideology and social identity processes in online language aggression against women. In R. M. DeKeyser (Ed.), Benjamins Current Topics: Vol. 116. Aptitude-Treatment Interaction in Second Language Learning (Vol. 86, pp. 59–81). John Benjamins Publishing Company. doi:10.1075/bct.86.03bou

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Ruiter, D., Reiners, L., Geet D’Sa, A., Kleinbauer, Th., Fohr, D., Illina, I., Klakow. D., Schemer, Ch., & Monnier, A. (2022). Placing m-phasis on the plurality of hate. A feature-based corpus of hate online. Preprint. Retrieved from https://doi.org/10.48550/arXiv.2204.13400

Samory, M., Sen, I., Kohne, J., Flöck, F., & Wagner, C. (2021). “Call me sexist, but...”: Revisiting sexism detection using psychological scales and adversarial samples. Proceedings of the International AAAI Conference on Web and Social Media, 15(1), 573-584. Retrieved from https://ojs.aaai.org/index.php/ICWSM/article/view/18085

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