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  • Writer's pictureDiverting Hate

Dehumanizing Language on Gettr: Exploring an overlooked corner of the manosphere

By: Clara Broekaert


The Diverting Hate Database seeks to define and categorize terminologies, websites, accounts, and hashtags frequently found in the manosphere. One of the key categories of terms found by Diverting Hate’s research team is the semantic idiosyncrasies of the misogynist online world to dehumanize, diminish, or humiliate groups seen as opponents or inferiors to the various submovements of the manosphere, notably and most continually, women. One particular platform that is used by manosphere adherents is Gettr, a social media platform launched by Jason Miller, a former Trump aide in July 2021. The platform defines itself as “a social media platform built on the foundation of freedom of opinion and expression, (1)” but mainly attracts a right-wing user base. An interesting feature of this alt social media platform that boasts 4.5 million users is that users can cross-post to X (formerly known as Twitter), thus directly allowing fringe ideas to make their way to a widely used social media platform.

This preliminary study seeks to understand the thematic foci of manosphere-related content on Gettr by first scraping the platform for selected keywords and then performing narrative analysis through the textual analysis software package Atlas.ti (2). The aim of this study is part of the larger objective of Diverting Hate to inform policymakers, law enforcement, and other key stakeholders about what extreme misogyny looks like in different communities and on various social media platforms without proper content moderation.


Several key terms from the Diverting Hate Database were selected for preliminary insight into the manosphere on Gettr. The terms in Table 1 were scraped through the GoGettr tool (courtesy of the Stanford Internet Observatory) (3). They were selected as a sample representing different violation scales in the Diverting Hate Database. The violation scale metric represents a continuum of a term’s extremism and connection to violence. The scale operates on a numerical value from 1 - 5. Each number on the scale represents how likely a term is to violate social media policies, how widespread the definition is, and how connected the term is to violent groups, individuals, or events.

Table 1. Terms scraped through GoGettr.

After the posts were scraped from Gettr (10/30/23, 11:30 am EST), a sample (10 percent of 905 total) was imported to Atlas.ti for qualitative textual analysis. The posts were inductively coded to understand the different narratives associated with these terms on Gettr. Inductive coding is a form of qualitative data analysis that interprets and tags (or codes) raw data through reading to develop themes and narratives. Through code co-occurrence, analysis of different themes and narratives was established. Additionally, through the GoGettr search command, the term frequency was established.


Figure 1—Quantity of Scraped Posts

Of the 905 scraped posts, posts with keywords “incel/incels” were 297 in total, while those referring to women as “wahmen” were 295. Ranking third in post quantity, a total of 161 posts on Gettr were scraped mentioning “TopG.” Both “Femoid(s)/Foids” and “Feminazi/Feminazis” were significantly less popular, with 71 and 81 posts scraped, respectively. The widespread nature of “wahmen” which garners a 5 on the Diverting Hate violation scale is particularly concerning and risks shifting the term into mainstream discourse.

Figure 2. Code Quantity

Through inductive coding, different themes were established in the Gettr posts sample. The most recurring themes were women being referred to as “stupid”, “dumb”, or “naive” (13), as well as critiques of modern women as “degenerates” and “promiscuous” (12). General transphobic posts were also captured through these key terms (12). General criticisms of wokeness, of which feminism or gender equality is considered part, were frequently coded as well (11). Of note, posts alleging a connection between feminism and/or gender equality and the “deep state” were also frequently recurring (11). There were five instances coded where highly offensive slurs were used to refer to women in politics (“feminazi” or “femoid”). Two very explicit incel-related themes were coded: sexual scarcity, referring to the lack of sexual partners of some men (2), and defense incels referring to posts in direct support of the incel community (1). Of the 136 text segments coded, one segment was coded under the “sexual abuse” theme. The post lamented that women complain about sexual harassment.

Through a Sankey visualization (Figure 3), these themes were further explored and broken down into narratives. Firstly, the against incels category (coded 8 times) overlapped 7 times with the transphobia theme (coded 12 times). The narrative for these two themes goes as follows; incels, unable to get a partner and desperate to find one, gender transition to prey on women. These posts tended to be used to discredit gender transitioning as a legitimate medical treatment for gender dysphoria. The second most recurring narrative (5) is that general ‘wokeness’ and progressive ideations of which feminism and women’s degeneracy are considered a part are leading to societal destruction and the decay of the Western Christian tradition. Closely related is the narrative that the deep state is using feminism to intentionally destroy societies globally. Women as stupid or dumb (13) lies at the core of multiple narratives: women naively destructing society through progressive agendas (3) and feminists being hypocritical in their strive for gender equality (3).

Figure 3. Code Co-Occurrence. Sankey Visualization


This preliminary study sought to understand the thematic foci of manosphere-related content on Gettr. The general frequency of criticism of purported wokeness and degeneracy indicates that Gettr’s ideological foci rely primarily on a far-right vernacular and simultaneously draws on some manosphere concepts. However, most of its discourse relies on deep-state conspiracies interwoven with anti-feminist ideals. A small number of codes for the “sexual scarcity” and “Pick-Up Artist (PUA)” themes indicate there are some sub-movements of the manosphere present on Gettr. Overall, this study suggests Gettr is a useful platform for analysis of evolving discussions of the manosphere and their overlap with other ideological communities.



Figure 4. Code Co-Occurrence Table

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