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BY 4.0 license Open Access Published by De Gruyter Open Access November 7, 2023

Analyzing Hate Speech Against Women on Instagram

  • Sandra Lopes Miranda EMAIL logo
From the journal Open Information Science


The popularization of digital technologies, such as social media, has driven remarkable changes in the way citizens participate in public life. On the one hand, they gave power to social actors, who began to act in a new media environment, with a considerable impact on the political and economic spheres. On the other hand, they laid the material foundations for the dissemination of hate speech against vulnerable groups and minorities. The present investigation has as its main objective to analyze the misogynistic hate narratives that are uttered in social media. For this purpose, a netnographic study was carried out, of the qualitative type, organized in three sequential moments: extraction, exploration/treatment, and content analysis of the data from the platform of the social network Instagram. The data highlighted from 74 profiles aligned with hate speech show, essentially, the presence of 40 publications, largely linked to extreme right-wing cultures with discursive and imagery manifestations of a misogynistic nature, highlighting the use of irony and the ridicule of women. The most offensive dimension of hate speech was measured in the comments of the followers of these publications, present in the form of insult and direct offense, confirming that the digital environment has aggravated hostility and online harassment against women.

1 Introduction

The popularization of Information and Communication Technologies has driven remarkable transformations in the way citizens participate in public life. In this new scenario, the network society, and the internet, reorganized the world space and broke down borders, giving us the power and the possibility to consume, create, communicate, and distribute content in a space of participation and free personal expression. But if, on the one hand, internet interaction is a determining factor in social organization and structuring, interfering in the exercise of citizenship, in political, social, and economic relations, it is also a fertile ground for the amplification of conflicting aspects of reality and social relationship, such as hate and all its manifestations (Pezzella & Borba, 2012). Ironically, Tin (2012) states that the Internet has become a place where “even the meekest of people have become ground-shaking titans who crusade and burn and unleash hell on… imaginary enemies in all-caps rants” (Tin, 2012, p. 13).

For Timofeeva (2003), the internet created the right conditions and provided unique resources to expand the verbosity of hate. It is a relatively inexpensive and highly effective tool for racist individuals or groups to spread hateful ideas to an audience. Dias (2007) adds that the internet is witnessing the production, legitimation, and reproduction of these discourses. For the researcher, the content of hate speech eliminates or minimizes the communicative character since the messages, when expressed, are no longer received as messages and start to be interpreted and felt as attitudes and behaviors. The urgency of studying this subject has been increasingly recognized, since the European Union data showed that around 80% of women reported encountering hate speech and 40% claimed to have been attacked or threatened in social media (Castano-Pulgarín, Suárez-Betancur, Vega, Harvey, & López, 2021).

Revisiting the literature, we found that although hate speech is a phenomenon clearly on the rise in contemporary societies, there is no universal definition in relation to it, with several multidisciplinary understandings and approaches to the phenomenon coexisting (Costa, 2020; Di Fatima et al., 2021; Di Fatima & Miranda, 2022; Miranda et al. (2021); Miranda, Gouveia, Di Fátima, & Antunes, 2023; Selma, 2019). There are those who advocate that you can recognize it when you see it, but the criteria for doing so are often elusive or contradictory. In fact, scientific work in this domain has not provided consensual elements that support a widely accepted definition of the problem. The term hate speech has been used interchangeably to refer to various types of negative speech, including hate and its incitement, abusive and defamatory content based on characteristics of belonging to a specific social group, including extreme forms of discrimination and prejudice (Siegle, 2020).

According to Brugger (2007), the term originates from English hate speech and is much more than an opinion, mere displeasure, or bias, and is an indication of an emotional state or an opinion that involves intense and abusive animosity, always discriminatory. It contains words that tend to insult, intimidate, ridicule, or harass people because of their race, color, ethnicity, nationality, gender, or religion, among other attributes. It is an attitude of systematic hatred and aggressiveness toward the way of being, lifestyle, beliefs, and convictions of an individual or group of individuals having “the capacity to instigate violence, hatred or discrimination against such people” (p. 21).

Meyer-Pflug (2009) broadens the debate by extending it to intolerance and discrimination based on gender, sexual orientation, and identity, describing that discrimination and externalization are the two elements that shape hate speech. In his words, the problem sets in when thoughts go beyond limits and hate takes shape through words. Wieviorka (2007) also addressed the issue, for whom hate speech perpetuates violence, which is, above all, symbolic, which is perceived through language and discourse and whose effects can remain in this context or go beyond it, passing to the Physical violence.

According to Anderson (2014), there is always the danger of hate speech spilling over into direct and offline verbal and physical aggression, as is, for example, what happens with the case of rumors against ethnic, racial, or political minorities who are threatened and physically attacked because of their group identity. Johnson et al. (2019) showed the link between online extremist narratives and abhorrent real-world events, including mass shootings such as the attack on Chirstchurch, bombings, recruitment of extremists and entrapment, and sex-trafficking of girls. But the topic of hate and its exultation in the public sphere is not new! It is enough to remember Mandeville (1715) and his famous work Fable of the bees, pointing out that some private vices, such as hatred, are acquiring public acceptability.

It is certain that, in the last 20 years, this addiction to the public demonstration of hatred has expanded (Waldron, 2010), favored by the explosion of digital social networks that function as a resonance chamber, propagating and amplifying its effects; and radicalizing the conflicts of social reality. Kaplan and Weinberg (1998) stand out as having been pioneers in observing the websites of extremist organizations and mapping the modus operandi of their hate speech. The supposed anonymity of the haters, the absence of a face-to-face interlocutor, and the isolation when constructing argumentative reasoning favor the distillation of hate in the posts, in the comment boxes, in the emojis, or even in the memes, pregnant with irony. With a few clicks, a situation of non-recognition is installed on a vast scale, which offends an uncontrollable number of people and summons countless other Internet users to perpetuate this asymmetry (Boyd, 2010; Boyd and Crawford, 2012). Busso (2011), when commenting on the unbridled increase in expressions of hate in digital social networks, states that the effect of hate speech narratives is even more, the greater the diffusion power of the means of transmission. Baurin (2017) argues that haters use social networks to promote their hateful cause and recruit new members, resorting to the most diverse expedients such as free music downloads with messages full of hate, racist games, cartoon characters, and images of people maimed by racial, nationalistic, or gender-based violence.

It is based on these concerns and circumstances that this investigation arises and seeks to analyze, in Portugal, the misogynistic hate narratives that are uttered on the social network Instagram and whose main results are presented in this article.

2 Misogynistic Hate Speech on Social Media

It is undeniable that, in recent years, hate speech against women has increased considerably on social platforms (Hewitt, Tiropanis, & Bokhove, 2016; Poland, 2016). In 2017, a study conducted by the Pew Research Center in the United States revealed that women, when compared to men, experience several types of gender-based or sexual harassment.

In Italy, the so-called “Italian Hate Map” Project analyzed 2,659,879 Tweets and concluded that women were the most insulted group, having received 71,006 hateful Tweets (60.4%), followed by gay and lesbian persons (12,140 tweets, 10.3%; KhosraviNik & Esposito, 2018). More recently, a study conducted by Unesco (2020) shows that of the 714 women journalists interviewed, 73% of them claim to have been the target of hate speech on social networks. In fact, although it is shown that men are sometimes also the target of attacks, those committed against women tend to be more serious and highly disproportionate.

The phenomenon manifests itself as a combination of brutal and prolific harassment, threats, and abuse, together with threats of physical and sexual violence, identity theft, disclosure of personal data, manipulation, and publication of photographs without consent, many of which can go beyond the merely virtual domain (Engler, 2017). In the same sense, Gardiner (2018) refers to the case of the British newspaper The Guardian which, when analyzing the comments on its website, found that the most abused journalists were not non-white, Muslim, and/or gay, but rather women and men, articles written by women journalists. They were the ones that attracted the most harassment and trolling online, regardless of the subject discussed in the article.

In “Your an ugly, whorish, slut,” Jane (2017) portrays e-bile directed at women, using the example of blogger Laurie Penny who, after speaking out against her country’s neoliberal economic policies, no longer had the courage to leave the house and do your day to day tasks. There were dozens of messages she received threatening her with rape, murder, bash, as well as indicating a knowledge of personal details such as the addresses of their home, workplace, among other things.

Regarding the women’s reaction to these attacks, on the one hand, they describe the experience as being emotionally exhausting, causing feelings such as anxiety, sadness, loneliness, vulnerability, fear, terror, distress, and devastation (Unesco, 2020). On the other hand, some women report that they started to censor themselves, delete their accounts, and measure the words and images used when making any type of publication.

In 2007, influencer Kathy Sierra withdrew at the last minute from giving a conference, because she received posts on her account with a sexually mutilated corpse. She canceled the conference by saying: “I have canceled all speaking engagements, I’m afraid to leave my home, I will never fill the same, I will never fill de same (Harris in Jane, 2017, p. 536).”

Another aspect that has been highlighted by the analyzed investigations concerns a kind of tyranny of silence (Jane 2011, 2017), since the overwhelming majority of women who are the target of this type of hate speech report a lot of reluctance to speak openly about their attacks they are targeted on social media and to denounce them in court (Unesco, 2020), contributing, in a way, to a normalization of this type of violence (Silveirinha, Sampaio-Dias, Miranda, Garcez, & Dias, 2022).

It is noteworthy to note that the violence propagated through language against women aims to provoke what many of them have struggled to break, for years, silence.

On the one hand, this fact brings our attention to the ethical boundaries of freedom of expression on social media. While it is a fundamental value in democratic societies and on the platforms themselves, the latter bear the responsibility to create an inclusive and safe environment for all users, regardless of their gender. This entails the implementation of policies and the promotion of values that reflect this responsibility (Donovan, 2019). It also involves control over the algorithms themselves, which can inherently promote polarization and the formation of extremist communities (Diakopoulos & Friedler, 2021; Noble, 2018). As highlighted by FRA (2022), algorithms can influence people’s behavior over time. Low data quality or poorly developed machine learning algorithms can lead to predictions that disadvantage certain groups of people.

On the other hand, this fact demonstrates the imminent need for greater state action in public policies to combat practices that, although belonging to the virtual environment, have an enormous impact on the “real life” of countless women victims of this type of discourse (Unesco, 2020). Furthermore, it appears that women who choose to make complaints based on hatred and discrimination are not aware of the results or implications that this entails for the aggressors. There is, to this day, some legal impassivity and a considerable lack of interest in acting at this level.

Analyzing the specialized literature, it is clear that the preponderance of hate speech against women in the social media is unequivocally the perpetuation of a patriarchal historical, social, and cultural system that reverberates latent inequality and gender discrimination, through the idea of male supremacy and female submission, culminating in the most varied forms of violence against women. In addition, according to Escobar (2019), women haters have a relationship with the idea of white supremacy, in addition to a far-right political position, aged between 25 and 35 years, attacking, preferably, women defenders of women’s rights or those who do not fit the socially accepted pattern for them (Aguero, 2015).

Added to this is the frequent use of anonymous forums located on the so-called deep web, characterized, above all, by decentralization and anonymity (Antonioli, 2019). In essence, these forums cannot be accessed through traditional search engines such as Google or Yahoo, requiring the installation of specific browsers to do so. They are therefore more difficult to control, intercept, and surveil.

3 Method

To analyze misogynistic hate speech, the method chosen for this investigation is based on a netnographic approach, of a qualitative type, operationalized through content analysis organized in three stages: extraction, exploration/treatment, and analysis of data from the social network platform Instagram. This social network was analyzed considering that it has been a very popular platform and little studied in terms of hate speech, focusing most of its approaches on Facebook and Twitter. We opted for a search for keywords in the text and tags used in Internet users’ interactions.

Bearing in mind that experience and our analysis of reality are mediated by language (Rapley, 2014), we believe that the analysis of negative expressions used in conversion offers us an important frame of reference for the treatment and perception of women in social contexts. From a proprietary database, 74 profiles aligned with hate speech in the national context (Portugal) were identified to respond to the study objectives.

In this sense, and following the guidelines of the specialized literature, a manual curation was carried out between the selected pages, focusing on posts and comments with a misogynistic bias (i.e., considered negative when prejudiced, urging, or reinforcing hate speech), which resulted in pages, above all, with conservative characteristics aligned with far-right ideologies. It is important to emphasize that the misogynistic bias consists, in most of the analyzed publications, of only one of the forms of hate speech also crossed by xenophobia, transphobia, homophobia, racism, and other types of violent narratives found in the digital environment. In this way, the analysis of the identified profiles was carried out in a time frame that includes publications between January 1, 2020, and January 1, 2023.

The advantage of this manual curation was having access to official Instagram data in order to identify forms and expressions of digital interaction that extraction through statistical tools is sometimes not able to identify. For example, offenses like “p* de m*” and “v4g4bund4” would be banned by the rules of use of the platform under study, if they were written with the spelling of the standard norm, as well as the non-recognition of terms by research, since its forms do not follow specific rules. A difficulty encountered was accessing the content, since several profiles do not have publications, they only serve as a kind of intermediary for pages located on the deep web, private or directing to private WhatsApp and Telegram groups in which identification is made of the real person of the digital profiles, in order to avoid that individual’s contrary to their ideologies remain in these private groups.

As a result, public information on social networks is less numerically representative, as well as expressed in more subtle ways through irony, ridicule, and the use of emojis, instead of written texts. For this reason, 40 publications and 534 comments were extracted from the pages: @atividadededireta; @super_indignado; @spinnotícias; @o_lusoniversalista; @__politically_incorrect__ and @chegacartoon.

Then, in the data exploration/treatment stage, the Voyant Tools tool (specialized in digital text analysis) was used to determine the frequency of terms and the association between words by competition, resulting in two-word clouds. In addition, it was considered relevant to identify and count the frequency of Emojis and hashtags, since they are digital language terms that indicate the positioning and message content of the issuers. This accounting was done using Excel software.

4 Results

The results found were extracted from six profiles, taken from the database consisting of 74 profiles in total, in which those that integrate this investigation showed a greater inclination to utter hate speech in relation to women in contrast to other types of hate as well identified and disseminated in the digital medium, as is the case of racism, homophobia or xenophobia.

Table 1 shows the number of misogynistic publications (40 in total) identified on each of the pages consulted. Of the pages analyzed, three profiles appear in the sample in a more expressive way (@ativistadedireita; @super-indignado; @spinstanoticias), with the profile @super_indignado, reportedly represented by the leader of the extreme right group “Proud Boys PT,” being the profile with the highest number of publications with misogynistic discourse out of the total investigated.

Table 1

Distribution of misogynistic publications by profile

Perfil N %
@ativistadedireita 7 10
@super_indignado 15 35
@Spinstanoticias 15 35
@Chegacartoon 1 5
@__politicamente_incorreto__ 1 5
@o_lusoniversalista 1 5

In the 40 publications analyzed (Table 2), the number of images/photos measured adds up to more than half (65%) of the other three categories – memes, videos, and cartoons, in which feminists or women outside the beauty stereotype are ridiculed through photos, valuing the conservative status of women’s role in society, hypersexualizing their bodies and even explicitly showing images of the result of acts of physical violence. It is also clear that some of the published photos have been altered and are, therefore, montages, possibly taken out of their original context, conveying misinformation, as is the case with the examples presented below.

Table 2

Distribution of visual media present in misogynistic publications

N %
Photo 13 65
Vídeo 4 20
Meme 2 10
Cartoon 1 5

In Figure 1, we can find an example of a misogynistic post composed of three women partially undressed and with indecorous phrases written on their bodies, alluding to their sexual organs and their ownership. The image is, ironically, accompanied by a sentence: – “Finalists of Rita Ferro Rodrigues’ Feminism Course.” Rita Ferro Rodrigues is a Portuguese journalist, and founder of the Capazes Association known for defending gender equality and defending women’s rights.

Figure 1 
               Example of a misogynistic post. Source: @superindignado, Instagram, March 4, 2020.
Figure 1

Example of a misogynistic post. Source: @superindignado, Instagram, March 4, 2020.

In Figure 2, we see the presence of a post published by a woman in a bikini who was allegedly the victim of rape by a young Portuguese international footballer, with a playful caption on her photo suggesting that, to the published image, the alleged rape victim deliberately provoked the act.

Figure 2 
               Example of a misogynistic post. Source: @spinstanoticias, Instagram, August 31, 2021.
Figure 2

Example of a misogynistic post. Source: @spinstanoticias, Instagram, August 31, 2021.

In Figure 3, we see a post that presents an old board game in which two men (father and son) are presented, in an evening, living together and having fun through the game and, on the other hand, two women (mother and daughter) who just watch the men’s game while washing and cleaning dinner dishes.

Figure 3 
               Example of a misogynistic post. Source: @politicamenteincorreto, Instagram, March 3 2021.
Figure 3

Example of a misogynistic post. Source: @politicamenteincorreto, Instagram, March 3 2021.

With regard specifically to the comments in the posts, it is evident that there is no concern with the veracity of the images and information published and discussed, just as there is no demonstration of concern with the identity of the people exposed in the publications. From the tool of the Voyant tool, a word cloud (Figure 4) was obtained that reveals the frequency of the most used terms from the 534 extracted comments. Thus, four main axes can be removed from the cloud: woman/s (143), man/s (128), feminist/feminism (119), and terms with nationalist allusions (society + Portugal + by the Portuguese + by portugal + I’m patriotic, 144).

Figure 4 
               Word cloud. Source: Voyant Tools.
Figure 4

Word cloud. Source: Voyant Tools.

As we can see, the terms woman(s) and men stand out as central points for other words, being unequivocal in the posts analyzed the appreciation of the submissive and traditional role of women in society, their subordination to men and conservative and patriotic values and the repudiation of existing feminist approaches and movements in society.

Regarding comments on posts from followers of the profiles found (a total of 534 were extracted), the analysis of hate speech based on abusive language allowed us to determine a set of more common expressions about these women. Thus, we highlighted seven insulting/abusive terms uttered in Portuguese, which appeared more frequently in the sample. In this way, as we can see from Table 3, the negative term that is repeated more often in the sample is grubby (55), lesbians (46), and sapatona (51) (sapatona is a jocular Brazilian term to refer to women who like other women). It is verified, therefore, in addition to a misogynistic hateful speech, that he intersects with his aspect of phobia with homosexuality. Added to this is the manifestation of disgust and repulsion for the women represented, being nicknamed badalhocas (19) and prostitutes (10).

Table 3

Most frequent sexist/misogynistic insults in the sample

Term N
Sapatona (shoes) 51
Grubby 55
Lesbians 46
Disgust 24
Miserable 21
Badalhoca 19
Prostitutes 10

The analysis of Emojis (Table 4) proved to be central to the dynamics found both in descriptions of the publication itself and in the comments. These, many times, configured the comment itself. Thus, it was concluded that it was important to identify them and analyze the frequency of the five most mentioned, since many of them appear only once or repeatedly in the same comment; 28 different types of emojis were identified that configured approval/agreement, disapproval/astonishment, and indignation regarding publications or other comments. More representatively, the content of satire, irony, ridicule, and disgust (vomit) was the most recurrent in the analyzed data, demonstrating inferiority or contempt for the image, video, meme, or cartoon in question where women are represented. The table lists the five most recurrent emojis:

Table 4

Emojis present in publications


In addition to emojis, hashtags (Table 5) were considered important in the interactions verified in the comments, as they configured agreement and ratification through a digital trend of that moment, also indicating recognition of the same ideological biases and party preferences. So, 19 different hashtags were identified in the investigated sample and the five most recurrent ones are shown in Table 5. It should be noted that most of the hashtags found refer to extreme right ideological and party preferences, as is the case of the Portuguese party Chega – a national, patriotic, and conservative party.

Table 5

Main hashtags present in publications

#soupatriota 7
#spinstanoticias 6
#porportugal 7
#pelosportugueses 7

5 Discussion and Conclusions

It was clear from the present investigation that the emergence of social media provided a new digital territory where the expression of hate speech toward women takes place, as well as finds echo and amplification, allowing its dissemination with an unprecedented reach. Although there is already a considerable amount of research on this topic and its correlates (Free et al., 2017; Ging & Siapera, 2018; Jane, 2014, 2016; Mantilla, 2013), research in this area is relatively recent, generating scattered evidence of its occurrence, its individual impacts, and its cultural and democratic consequences. There are still gaps in knowledge about this social phenomenon, its true expression in digital social networks, and the development of effective strategies and responses likely to resolve it. In Portugal, the exploratory studies (Miranda, David, & Tutui, 2022; Silveirinha et al., 2022) carried out to date do not yet allow to adequately map this phenomenon. This research aims to deepen knowledge about hate speech towards women, more specifically on the social network Instagram, which tends to be less studied when compared to other more popular ones such as Facebook or Twitter – the latter being particularly verbose in this type of discourse (Poland, 2016; Piñeiro-Otero & Martínez-Rolán, 2021).

The netnographic analysis carried out on Instagram, over a period of 1 year, reveals the presence of a significant number of publications with a tendency to be misogynistic, extracted, in their entirety, from activist profiles of extreme right ideology and toxic cultures in Portugal. From the analyzed publications, it is verified that, more than direct insults, the use of irony and ridicule of women is very present, mainly through the use/adultation of images, photos, memes, and cartoons, highlighting, above all, the ridicule of feminist women, women that the aggressors consider to be outside the beauty stereotype, hypersexualizing their bodies and exalting the conservative and subaltern role of women in society. In essence, it turns out, as feminist and gender studies (Ging & Siapera, 2018) suggest, that technologically mediated practices invariably reproduce crystallized hierarchies and privileges and are also driving forces of new phenomena such as male movements and toxic masculinities.

The most abusive and offensive dimension of hate speech was measured in the feed of comments on the identified posts, uttered by the followers of the identified pages, manifesting themselves in the form of direct insults, as is the case with pigs, lesbians, shoemakers, badalhocas, and prostitutes, verifying here the existence of intersectionality in hate speech, intersecting with its aspect of phobia for homosexuality and even with race.

The data highlighted by this investigation show the need to develop ethical guidelines and responses against hate speech and to strengthen them, both regarding technological sophistication, public policies, and collaborative actions, capable of combating this phenomenon.

The climate of disinhibition, impunity, and the passivity of the community in the face of gratuitous abuse and aggression raises a set of questions that must be studied in greater depth, namely regarding the limits of freedom of expression. In fact, more than an individual problem or a personal experience, the hostility to which women have been subjected requires an awareness that this phenomenon is a collective reality. As Piñeiro-Otero and Martínez-Rolán (2021) argue, it is necessary to intervene to reduce the spread of rumors and false news about women, as well as to act in the face of the expansion of cyberviolence. In this regard, we conclude with a recent set of recommendations that emanated from the Unesco Report (2020) which, although very directed against hate speech by women communication professionals (specifically journalists), serve as a guide for all similar situations, namely: women victims of hate speech should not have the responsibility of fighting the problem alone, it is fundamental to help them to denounce these cases; communication companies and digital platforms must equip themselves with robust systems to identify and block hate speech, as well as develop effective reporting systems, detailing robust and transparent systems and procedures where it is easy to understand what measures are adopted to respond to this type of attack. The lack of a solid framework for online attacks and the protection of women contributes to maintaining a space free of limits and sanctions.

It became clear through this research that hate speech against women is a worldwide phenomenon. The climate of impunity in the face of this phenomenon, in addition to being a wound against the inalienable rights of men and women, is a ferocious attack on democracy and freedom of expression, raising concerns and opening space for, in a collaborative way, and integrated, urgent action is taken to resolve and minimize it.

  1. Conflict of interest: Author states no conflict of interest.


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Received: 2023-07-17
Revised: 2023-09-28
Accepted: 2023-10-09
Published Online: 2023-11-07

© 2023 the author(s), published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

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