Crazy, mad and wacko: misogyny is prevalent among offenses to women candidates in the current elections

In the first week of the campaign, 97 women candidates received almost 4,5 thousand attacks and/or insults on Twitter.

News Inequalities and Identities 09.06.2022 by Lu Belin

Allusions to madness, hysteria or mental illnesses are the main way found by Twitter users to address Brazilian candidates to Legislative and Executive offices in these elections. In the first week of campaign, MonitorA registered 518 occurrences of terms such as crazy, mad, wacko, unstable, hysterical and uncontrolled relating to women candidates. Posts suggesting that candidates “seek treatment”, “get medication” or “commit to a mental institution”, among similar references, were also found. 

The prejudiced association to mental illnesses and disorders prevailed on the tweets assessed by the project, a partnership of AzMina, InternetLab and Núcleo Jornalismo that, in this edition, is monitoring the profiles of 175 candidates to elective positions. For this report, more than 10 thousand tweets, collected in the period from August 17 to 22, were manually analyzed, containing 4,468 attacks and/or insults targeting 97 women candidates.

The results of the first week of assessments show that the historical attribution of stereotypes of madness and hysteria to women who raise their voices is still one of the main tools for sexist control. Adjectives as “mad” and “uncontrolled” and questions as “have you forgotten to take your pills today?” appear to candidates belonging to a wide range of political spectrums.

“Say this amount of bullshit on Mars. This woman should live on an island, totally isolated. To her, nobody is good enough. She flipping out, someone commits her, please… she’s  nuts!!”

 “We can notice that political criticism is not present on the messages; there is only a downgradidng of women”, highlights Giovana Durat, a psychologist who recently studied the impacts of gender issues on women’s subjectivities. “The person is so ‘unworthy’ to be there, that one doesn’t realize that what needs to be questioned is their political action, not their sanity”.  

The effects of this kind of comment are manifold, according to her. “Corroborating this kind of narrative is extremely harmful for many reasons. First, because it perpetuates the idea that women who take a stand are unstable, are ‘crazy’. Then, because it contributes to the understanding that ‘character flaws’ are pathologies or mental illnesses, and that disorders lead to aggressions of others. All of that corroborate the manintenance of social medicalization”.   

“There is a great stigma related to madness, to psychic illnesses, to disorders, and this resource [using it to attack candidates] shows lack of knowledge and reflects the place madness has taken for a long time in society. A mad person was someone who would not fit into the norms, who would question standards and would be considered unable to make decisions for themselves and for others”. Giovana Durat, psychologist. 

Besides mentions to mental illnesses, terms as idiot, imbecile, illiterate, unprepared, incompetent and loser are also employed with the aim of disqualifying the candidates. Associated to them, silencing resources as “shut up” and “be quiet” suggest that they should not manifest their opinions. “Positions that diverge or question social norms are severely punished and that is gender violence: a punishment for deviating from a socially established gender role. Under these slurs and insults there is a power issue”, reinforces the psychologist.

1 out of 3 tweets has offenses to candidates

MonitorA analyzed 10,346 potentially offensive posts (check the classification methodology at the end of this report). In total, 30.76% of the publications, that is, 3,182 tweets, treat candidates with a certain level of hostility. In almost 900 tweets, at least two offenses were identified.

Misogyny leads the themes of attacks to candidates

In 1 week, 10,346 tweets were analyzed

97 candidates were mentioned

3,182 are offensive, divided in:

1,683 milder insults

2,785 more aggressive attacks

Attack categories

41.94% Misogyny

17.02% Dehumanization

10.48% Degrading

9.55% Moral offense

6.32% Intellectual discredit

3.41% Political ideology

2.94% Be disgusted

2.23% Ableism/Psychophobia

1.72% Ageism

1.33% Sexual offense/Harassment

Misogynistic discourse is the main kind of offense, followed by narratives that downgrade candidates, underestimating their intellectual capacity, insulting their bodies and questioning their morality. Racist terms are also present, with ethnic or regional prejudice. 

 “Of course it can! Just as watching the end of the event! But you’re not interested in watching, right? Phoney and unloved indian!!!”

Dehumanization, which associates candidates to animals – pig, donkey, snake – is also a common resource among haters. On the survey, the most frequent term was “Peppa Pig”, present on 372 posts. The reference to the cartoon is used against the Federal Deputy Joice Hasselmann (PSDB-SP), candidate to reelection and most quoted representative in this first week of campaign.

“When you decide to refer to a candidate with nouns used to name animals, you deny the place of human being to that specific person. This is an old tactics to feed the idea that some people don’t even deserve to be considered humans. In the case of the candidates, we see a similar movement. You deny them the political space, reducing them to a non-human subject”, explains Fernanda Martins, anthropologist, director at InternetLab and one of the heads of research.

“Hi @SF_Moro, your canditate to President is that bawd, conservatart, whorehouse owner in Mato Grosso do Sul? It’s just a question.”

Posts degrading or promoting intellectual discrediting of the monitored candidates respond to almost 17% of the attacks. “Moral offenses and degrading candidates, in their turn, have the role of reinforcing their supposed lack of qualification to hold offices in institutional politics. “Trash” and “crap” are examples of this attempt of degradement”, Martins adds.

Beyond aggressive, the detractors are creative. Besides tweets containing misogynistic and dehumanizing attacks, there are other offenses targeting the candidate’s bodies or looks: those are fatphobic and ageist tweets, that use terms such as “old”, “mummy” and “fat”, or that recommend “bariatric surgery” to the candidates.

Although the platform counts on policies to prevent sexual harassment, the report found 37 cases of it. Joice Hasselmann, Gleisi Hoffmann and Mayra Pinheiro are the ones concentrating more mentions of the kind.

“Mrs you cause disgust, what a pig this man is to lie down with a disgusting thing like you”

“Get a broomstick and make you suck it!”

In a few cases, sexual offenses also reproduce previous attacks to victims of violence, as happens with the Deputy Maria do Rosário.

“You don’t [even] deserve to be raped…”

Purposeful hostility towards women

Although not every offensive tweet can be considered violent, 1,683 posts carry some kind of insult, contributing to the creation of a hostile environment to the political participation of women. Azmina’s data journalism project manager, Ana Carolina Araújo, explains that distinguishing offenses from insults is an important methodological step to safeguard freedom of speech. “We don’t want the end of discussions on platforms, but a greater animosity towards women is noticeable”. 

“Every kind of violence is a barrier to women’s participation, a very effective way to exclude women from the political game. This is a point of agreement to the current representatives: a healthier environment for women to take political action is needed”, affirms Cristiane Brum Bernardes, PhD in Political Science. The National Observatory for Women in Politics, created this year by the representatives, is an initiative to combat gender political violence.  

On social media, the large volume of posts including terms as pathetic, hypocrite and corrupt, for example, or texts accusing candidates of defending criminals and rapists, make the field more hostile. It does not seem coincidental that, even when they are on politics, women are attacked through their relation with men.

Hey Joice that’s your name right, tell me how was that fall you had at night and woke up all bruised in the morning tell me, was that a spiritual beating was it honey, explain that you thief’s sweetheart

Expressions such as “be ashamed”, “aren’t you ashamed” and “I’m ashamed of having voted for you” are also recurrent. To Cristiane Brum Bernardes, these attacks do not acknowledge the legitimacy of women’s presence on the dispute for positions of power. “A man will be attacked for belonging to a certain party, for doing something or not, agreeing or not with my position. But, in the case of women, it is an attack against their presence in politics, that says ‘you shouldn’t be here doing this’. That is never said to a man”. 

Physical and intellectual offenses on top

Most frequent terms

you are a shame

get a treatment/get committed

lover

old 

crazy 

pig 

mad 

sweetheart/hoe

disqualified/incompetent

peppa pig 

snowflake/victimism

mention to a previous violence/revictimization

stupid

cry/whine 

betrayer

wacko

be ashamed 

uncontrolled

ugly

disgusting

These ways of addressing candidates show that the necessary border between women’s public actions and personal lives is not respected. On the contrary, it is used as a weapon to downgrade and disencourage them. “Those are adjectives as ‘badly fucked’, ‘unloved’, always referring to their body, sexuality, women’s private issues, it is a very different content from the one received by men”, Brum explains. 

Professor Brum also reinforces that, in the case of comments related to looks, even when they are complimenting, they can act against the candidate. “What’s being communicated through these comments is that they don’t have content, that they’re nothing but beautiful bodies to decorate the room. What legitimizes this public opinion about women’s bodies?”.

Who are the victims?

A quick look at the ranking of most attacked candidates in the first week of campaign shows that offenses were distributed through all political spectrums and directed to women belonging to different ethnic groups.

Most offended candidates

Candidates to president and deputy offices lead the ranking of most offended candidates on twitter in the first week of elections

___% of the offensive tweets

Joice Hasselmann (PSDB-SP) has, once again, received almost half of the mapped offenses (2,070). She is the prime target of President Jair Bolsonaro’s supporters (PL). Besides fatphobic, dehumanizing and misogynistic terms, she is also harassed for having turned away from the president, her previous ally. “Peppa pig”,”pig”, “traitor”, “ridiculous” and “be ashamed” or “you are a shame” are the most frequent terms, besides more than 50 mentions to an episode of physical violence suffered by her in 2021.

Another opponent of Bolsonaro, Gleisi Hoffmann (PT-PR), who is running for the Senate, is the second most offended candidate (822 slurs). In her case, the majority of aggressions relate her to corruption and to the support of ex-president and current candidate Luís Inácio Lula da Silva. The predominant offenses are “lover”, “be ashamed” and “liar”. The terms “ridiculous”, “thief”, “corrupt”, and accusations of “outlaws’ defender” also appeared. Some tweets gather so many accusations that the exclusive aim to attack and undermine the candidate’s presence on the media becomes explicit.

“Take your medicine, mistress of Odebrecht list [politicians] and wife of inss money’s thief”

Senator Janaína Paschoal (PRTB) stands on the third position of the list, and she is mostly attacked by offenses charged with psychophobia and ableism. Terms such as “snowflake”, “crazy”, “mad” and “uncontrolled” are more frequently used against her and against Federal Deputy Maria do Rosário (PT), who is also called “ugly” and “old”.

The three women candidates to the presidency are also attacked, although Vera Lúcia (PSTU) receives fewer mentions. The Senators Simone Tebet (MDB) and Soraya Thronicke (União Brasil) are prime targets of the president’s supporters. In the case of Tebet, there are many references to her work at the Parliamentary Committee of Inquiry about Covid. Thronicke, on her turn, is accused of taking advantage of Bolsonaro to gain visibility, because she was elected a senator as a part of PSL, the former party of the president, with the slogan “Bolsonaro’s senator”.  

Among the candidates to an office at the Federal Chamber of Deputies, the most attacked ones are Mayra Pinheiro (PL-CE), known for her defense of the use of hidroxicloroquina during the pandemics of Covid-19; the activist for indigenous peoples’ rights Sônia Guajajara (PSOL-SP), the black Deputy Benedita da Silva (PT-RJ) and the trans candidate Duda Salabert (PDT-MG).

Gender political violence online is a central feature in the current elections, in which we expect not only messaging apps, but also relationship sites to be central to the political debate. At the same time, these will be the first elections happening after the enactment of the law to combat political violence against women (Law no. 14.192/2021), which implements new tools to curb aggressions and to stimulate women’s participation on institutional politics.

Methodological note:

200 profiles of candidates – 175 women and 25 men – were monitored on Twitter from August 17 to 22, in which the survey found 130,454 tweets aimed at them. Based on a lexicon composed of offensive, misogynistic, sexist, racist, lesbo, trans and homophobic words, we collected 11,837 tweets that contained words from this offensive lexicon, but that needed context analysis to determine whether they could be considered attacks. After that, we excluded repeated lines from this initial sample and carried out a qualitative analysis of 10,3 thousand tweets. Each tweet was read by a group of 8 codifiers, to identify whether the content was an attack or an insult targeting the candidates. The data were qualitatively analyzed after this manual categorization. The percentages presented on this article refer to this sample of 10,3 thousand tweets that went through qualitative analysis. 

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