Giuseppina Scotto di Carlo. Journal of Language & Politics. Volume 19, Issue 1, 2020.
The present paper is part of an overview of the discursive manifestations of the U.S. President Trump’s sexist attitudes and practices. Drawing upon Mills’ model of sexism (2008) and Van Dijk’s socio-cognitive framework (2006), the study will analyse a corpus of all the negative Tweets against women tweeted by President Trump since the beginning of his 2016 campaign (July 2015) to February 2019. The study sheds a light on how President Trump’s vocabulary perpetuates a male-centric hierarchy. Considering the outcome of the 2016 elections, it can be said that his ideology has had a significant impact, particularly amongst his supporters. His political ascendency speaks to how these ideological beliefs risk to become dangerously ingrained in language and society.
The present paper is part of an overview of the discursive manifestations of U.S. President Trump’s sexist attitudes and practices. It aims to investigate the linguistic strategies utilised by President Trump to negatively represent women, by specifically analysing his Tweets, which are one of his privileged forms of communication.
From his remarks about former Hewlett-Packard’s CEO and Republican candidate Carly Fiorina “Look at that face. Would anyone vote for that?” to more eyebrow-raising remarks referring to touching women without their consent “[…] grab them by the p****”, Trump has been notoriously and widely called out for his objectification of women through sexist language.
Though Trump has dismissed his comments as “locker room talk” several times, his statements represent a complex sexist rhetoric and offer a particularly loaded corpus for an investigation on gender discrimination.
The most exemplary case is perhaps the media’s exposure, towards the end of the 2016 electoral campaign (Oct. 7, 2016), of an ‘Access Hollywood’ tape), in which Trump made sexist comments during a conversation with the television presenter Billy Bush. The publication of this private conversation caused great rage among a part of the American and international audience (Khazan 2016):
Women tweeted accounts of their molestations at a rate of 50 per minute. Parents used it to teach their kids about respect and boundaries. […] Even women who [were]n’t sexual-trauma survivors found themselves, as Michelle Obama put it, ‘shaken to the core’.
The President’s words have had a strong impact on his audience and his apologies have not erased their effects. The problem is that his linguistic choices may actually reflect and reinforce cultural prejudices concerning gender differences in the contemporary United States. His eventual victory in the 2016 U.S. elections could suggest that his ideologies might be widely shared by part of the American population, and thus the findings of this study may serve as an overview of Americans’ attitudes towards gender discrimination. Dismissed as jokes played by a public personality, the President’s statements might not be “just words”, but a mirror of gender discrimination that is difficult to shatter.
Politics and Trump’s Tweets
In the last decade, social media have been widely used as a public relation tool, also in political discourse. Twitter, from which the corpus of this study has been retrieved, is part of the evolution of communication technologies that has influenced political discourse: no longer constrained in unilateral communication from politicians to voters (i.e. television debates or interviews), information can be equally shared and commented on by users in real time.
Politicians like former President Obama have exploited this function to create relationships with social media users and analyse their level of engagement through likes, retweets, replies, and impressions. More recently, right-wing populist politicians seem to be particularly successful in adopting social media for campaign purposes and have used them as a strategic communication tool to convey their ‘us versus them’ political agenda, promote themselves, and criticise opponents.
Current U.S. President Donald Trump is among the most prolific users of the platform, with almost 60 million followers, 41,000 Tweets, and an average of 7.5 Tweets posted per day (Twitter 2019). Often defined as the “Tweeter-in-Chief”, President Trump has understood how to use this platform at its best: with its high penetration and information sharing nature, it allows reaching those who would be unreachable through conventional campaign tools. He uses it to represent himself, justify his positions, and interact with his audience. “His language is simple and direct, his messages are succinct and polarising, which is a common strategy of right-wing populist discourse.”
Ott (2018, 63) goes even further by interestingly claiming that “Trump’s natural style of speaking and Twitter’s underlying logic are wholly homologous.” He notes that Twitter is defined by three key features: simplicity, impulsivity, and incivility, which perfectly match with Trump’s usage of the platform and especially with his public discourse style in general.
As for the first aspect, namely ‘simplicity’, when Trump’s public discourse is run through the Flesch – Kincaid grade-level test, it rates at a 3rd or 4th grade reading level. However, according to Shafer, his simplicity might be for strategic political purposes: “Trump isn’t a simpleton, he just talks like one […] he resists multisyllabic words and complex, writerly sentence constructions when speaking extemporaneously in a debate, at a news conference or in an interview.” Whatever the reason is, his simple language perfectly fits Twitter’s style and allows him to reach and be understood also by less educated users, which eventually became the main part of the electorate who voted for him in the 2016 elections.
As for impulsivity, Trump’s speech definitely “favours the momentary over the considered” (Ott 2018, 63), reflecting Twitter’s style of immediate communication. As has noticed, “above all else, Donald Trump is the candidate of impulse running against candidates of calculation.” He is notoriously known for his aversion against teleprompters and prepared speeches, in favour of apparently more ‘off-the-cuff’ remarks. Also in this case, his extemporaneous style matches Twitter’s characteristics.
Finally, as for incivility, President Trump has a history of mocking people, especially women, for their bodily functions, demeaning their looks, or comparing them to animals. Based on an analysis of Trump’s public utterances during the 2016 campaign, Merrill concluded, “Mr. Trump’s language is darker, more violent and more prone to insults” than other candidates’ style. As a matter of fact, several studies have tried to keep record of his offences and insults sent via Twitter, using a derogative and impertinent vocabulary.
As Ott has commented, the homology between Trump’s public rhetoric and the logic of Twitter suggests that Trump’s popularity is due, at least in part, to the fact that “he is a man of his technological moment”. However, this is not the only aspect that may account for the popularity of Trump’s Twitter account.
As other scholars have remarked, Twitter users often send messages that align with what their audience believes. A very interesting analysis is provided by, who asserts that we are living in a ‘post-truth’ era, in which objective facts are less influential in shaping public opinion than emotions. Montgomery analysed Trump’s rhetorical style on the basis of the Aristotelian triangle of persuasion, concluding that the relationship between Trump’s credibility (ethos) and his way of creating an emotional link between his audience and what is being reported (pathos), creates a truth that seems credible regardless of the set of logical evidence behind his statements (logos). These three aspects encourage the reader to accept a reality in which logos has lost its traditional prominence. Logos gets lost behind an ‘authentic style’ in which according to Kreis:
Even his username (@realDonaldTrump) indexes authenticity and closeness to the people because it supports his claim that his tweets come from the ‘real’ Donald Trump and are not sent by his staff. This might be a reason why he has continued to use his personal Twitter account instead of the official account of the President of the U.S.
Caught in messages that appeal to pathos and ethos, many accept alternative ‘truths’ that justify their point of view. This might suggest that Trump’s thoughts and ideologies might be widely shared by some of his followers. As a matter of fact, with specific reference to sexism expressed via Twitter, a 2018 Amnesty International report on sexism on Twitter has described this social media as a “toxic place” for women (Amnesty International 2018), because of the relentless abuses, threats, and harassments used throughout the platform. According to the report (Amnesty International 2018):
Abusive content violates Twitter’s own rules and includes tweets that promote violence against or threaten people based on their race, ethnicity, national origin, sexual orientation, gender, gender identity, religious affiliation, age, disability or serious disease.
For this reason, this study provides an overview of President Trump’s negative Tweets concerning women, as the findings of this study may serve as an overview of Americans’ attitudes towards gender discrimination.
Sexism can be defined as the practices whereby someone foregrounds gender when it is not the most salient feature of a communicative event. It encompasses the use of language to discriminate and trivialise women and all activities they are involved in.
In Lakoff and Bucholtz’s words,
[…] women experience linguistic discrimination in two ways: in the way they are taught to use language, and in the way general language use treats them. Both tend, as we shall see, to relegate women to certain subservient functions: that of sex-object, or servant; and that therefore certain lexical items mean one thing applied to man, another to women, a difference that cannot be predicted except with reference to the different roles the sexes play in society.
Similarly, Cameron argues that sexism does not reside in certain words and phrases, but in the deeply ingrained beliefs that see women as being inferior to men. Sexist language cannot be considered simply as the naming of the world from a masculinist perspective; it is rather a multifaceted phenomenon occurring in a number of complex systems of representation, as will be described in the following section.
Overt and Covert Sexism
Just like other forms of discrimination, sexism stems from larger societal forces aiming at institutionalising inequalities. It tends to endorse and monitor traditional gender roles, “legitimising ideologies” that protect the status quo.
The ultimate consequence is that women, depicted as communal caregivers, are systematically denied access to power on the grounds that unlike men, who are assertive and agentive, they are not capable of achieving and holding it.
Mills, 11-12) distinguishes between overt (direct) and covert (indirect) sexism. The former can be easily detected through the use of lexical indicators of discrimination. The latter expresses sexism through humour, attempting to deny responsibility for it or prefacing sexist statements with disclaimers or hesitation such as ‘I don’t want to be sexist, but […].’
According to Mills, 35-76), some examples of main linguistic cues that convey overt sexism are:
- Generic male pronouns and nouns used as the unmarked form: The generic pronoun ‘he’ and the terms ‘mankind’ and ‘man’ are often used to refer to both males and females in general. This linguistic strategy perpetuates a view of males as the norm.
- Suffixes used to refer to women, such as [-ess], [-enne], [-trix], [-ette], etc.: While attempting to fill that gap created when women started to be involved in positions that were a male prerogative in the past, these affixes are still perceived as generally belittling.
- Sexualised insult terms, such as ‘bitch’, ‘ho’, ‘prostitute’, etc.: These terms consider women as objects at men’s disposal.
- Ready-made phrases and proverbs, such as: ‘A woman has even cheated the devil’, ‘He who follows his wife’s advice will never see the face of God’, or ‘Women have got long hair and short sense’, which perpetuate a stereotyped negative image of women.
- Other strategies include: metaphors, similes, negative lexicalization, sexist slurs, etc., which are all used to discriminate women.
As far as covert cases of sexism are concerned, some of the strategies used include
- Humour: as Lakoff comments: “Saying serious things in jest both creates camaraderie and allows the speaker to avoid responsibility for anything controversial in the message. It’s just a joke, after all.”
- Presuppositions and implications: As Christie remarks, sexism at the level of presupposition is difficult to challenge because of the indirectness chosen to mark sexism, which gives the speaker the potential for denying any sexist allusion.
- Disclaimers: These are used to give a negative description about women, then denying it by using the coordinating conjunction ‘but’ in the same sentence. For example, “I don’t want to be sexist but […]”
After this literature review, the paper will now proceed with a brief description of the theoretical framework and of the corpus collected. Next, the findings will be discussed and summarised. Finally, the article will offer conclusions, limitations, and directions for further studies.
The theoretical framework of the study draws upon Critical Discourse Analysis (CDA), an interdisciplinary approach to the study of discourse, which views language as a form of social practice enacting, legitimising, reproducing, or challenging relations of power and dominance in society. It also takes into account the social and political background in which discursive events are embedded, to make “opaque structures of power relations and ideologies manifest”.
Given its emphasis on the strong correlation between linguistic and extralinguistic aspects involved in discourse analysis, this approach is particularly apt to the purpose of this study, as it allows the unveiling of the interrelation between discourse structures and ideological structures.
Actually, Van Dijk essentially perceives discourse analysis as ideology analysis, since “ideologies are typically, though not exclusively, expressed and reproduced in discourse and communication”. In this sense, ideologies indirectly influence personal cognition in comprehension of discourse. These mental representations are known as “models”: they “control how people act, speak or write, or how they understand the social practices of others”.
For instance, according to, some models and strategies related to sexism are:
- Valuing women based on their appearance rather than their intelligence or personality
- Considering males as the norm, that is, females appear as dependent beings and as followers
- Comparing women to inanimate objects
- Considering women as no more than possessions
- Semantic derogation of women
- Considering women as weak, lacking in strength and ability, incompetent
- Using vulgarity when speaking about women
- Glorifying the maltreatment/mistreatment of women
For the purposes of this analysis, the corpus chosen for this study will be analysed according to this theoretical framework using an eclectic model adopted from both Mills’ model of sexism and Van Dijk’s socio-cognitive framework.
This Section describes the ad-hoc corpus on which the qualitative and quantitative analysis of this study is based.
The corpus has been retrieved from the New York Times article “The 567 People, Places and Things Donald Trump Has Insulted on Twitter: A complete list” by Jasmine Lee and Kevin Quealy.
The corpus only includes the negative Tweets against women tweeted by President Trump since the beginning of his 2016 campaign (July to the current date (Feb. 20, 2019), for a total of 48090 tokens.
To investigate the co-text of specific words and phrases, the study has retrieved useful data through the use of the concordance tools available in AntConc (2019), a concordancer developed by, the features of which include word and keyword frequency generators, concordance distribution plots, and tools for clusters, n-grams, and collocation analysis.
Considering the nature of the information sought, automated interrogations will be supplemented with manually retrieved data and qualitative analysis.
It must be specified that the analysis itself is not corpus-driven but corpus-based, which means that it is not compared with general external corpora, but with linguistic frameworks within the corpus of the study itself.
With reference to the Tweet extraction process, all the Tweets directly addressing or making reference to women were extracted manually from Lee and Quealy’s list which was created by collecting data using the public Twitter Search API. This database of Tweets was analysed on the basis of Mills’ model, critically scrutinising each of the selected Tweets to highlight the items, phrases, expressions, clauses, and sentences signalling the existence of sexist attitudes. The corpus only included posts Tweeted directly by Trump, thus it excludes retweets by other users.
After the qualitative analysis, the corpus was analysed quantitatively, in order to retrieve the number of occurrences of negative phrases and words used throughout the corpus and thus establish which were the most frequently used by President’s Trump. The corpus was thus queried with Antconc’s Text Mining (keyword frequency generator) option, in order to obtain the number of tokens used for each of the words/phrases under examination.
Findings and Discussion
This section is devoted to the analysis of the data collected from the corpus, based on Mill’s categories, as described in paragraph 3 of this study.
Women are Weak, Lacking in Strength and Ability, Incompetent and ‘Mentally Instable’
This idea is the one Trump uses the most when using sexist language against women. This group of Tweets conveys the idea that women are weak, incompetent, and lacking physical and mental abilities. Most of the Tweets that belong to this category refer to women as “crazy”, “very dumb”, “neurotic”, prone to having “mental breakdown(s)”, and thus mentally unstable.
These characteristics lead Trump to depict women as “nothing but problems” and “disgrace(s)”. They are weak beings who “will never make it” in their careers. With their “bad judgment”, they “would be a disaster” for the country.
Another significant portion of Tweets belonging to this category highlight women as ‘weak’: specifically, Hillary Clinton is defined as having “no strength or stamina”, therefore she is “unfit to serve as #POTUS” [President of the United States]. Her “bad judgment and temperament” would be “dangerous” for the United States. “ISIS, China, Russia and all would love for her to be president” because she would have “no strength” to fight them.
Moreover, most of the women mentioned by Trump are all defined as incompetent in some way. They are said to have “zero natural talent” and a “low I.Q.”. They are “dopey(s)” that are “dumb as a rock”, “highly overrated” “loser(s)” who “will Make America Weak Again”. The following Table (1) summarises Trump’s words used for this category, dividing them by types and tokens:
Table 1. Words used by Trump to express that women are weak, lacking in strength and ability, incompetent and ‘mentally instable’
|Women are weak, lacking in strength and ability, incompetent, and ‘mentally instable’|
|No strength or stamina||9|
|Prone to mental breakdowns||2|
Used against both news reporters and women involved in politics, Trump’s presuppositions seem to embrace the idea of women as being the weak sex, lacking decisional strength and competence. Constantly on the verge of a neurotic crises or guided by their hormones, women would thus be unable to guide the nation or have success in the news and political fields, from Trump’s point of view.
Males as the Norm, That is, Women Appear as Dependent Beings
Portrayed as emotional and dependent, women in Trump’s world are not capable of having their own identities separate from men. His Tweets mention cases of several women going to his office “begg[ing him] for a job, tears in [their] eyes” or “begging for campaign contributions not so long ago (and would do anything for them)” in totally submissive positions. Moreover, it is possible to see sexual allusions in his words that devalue women and promote male superiority even more. The implication in these statements is that not only women are seen as totally dependent on men, but that they can use their bodies to obtain whatever they want.
In other cases, such as his words against the news reporter Megyn Kelly, he reduces her to a totally dependent being, by Tweeting that she is “always complaining about Trump and yet she devotes her shows to [him]”, and that “without [him] her ratings would tank”. Once again, women’s success is represented as depending on him and on men in general: their lives and success totally depends on him.
Table 2. Words used by Trump to make women appear as dependent beings
|Males as the norm, that is, women appear as dependent beings|
|She begged me||4|
|Without me […]||1|
Valuing Women Based on Their Appearance Rather Than Their Intelligence or Personality
Compared to what Trump usually says in other contexts, there are a very limited number of occurrences of judgments on women’s physical appearance in Trump’s Tweets. In the case of the corpus, there is reference to Hillary Clinton as not “even look[ing] presidential”.Trump degrades her by judging her possibility of becoming a president by her looks. This is similar to what he said about Carly Fiorina, a fellow presidential candidate: “Look at that face! Would anybody vote for that? Can you imagine that, the face of our next president? I mean, she is a woman, and I’m not supposed to say bad things, but really folks, come on. Are we serious?”
His Tweets completely undermine women’s intelligence, hard work, and competence, reducing them to their appearance.
Other comments on looks range from the goliardic “bad timing, she looked like a Snowman(woman)”, referring to the candidate Amy Klobucher, to more serious comments like “[she] was bleeding badly from a face-lift” referring to lawyer Jill Becks, against which he also complained because she “wanted to breast pump in front of [him]” (July 29, 2015). Another notorious case is the Tweet against the politician Elizabeth Warren, nicknamed “Pocahontas” by Trump, invoking a racial comment, for her Native American origins.
Table 3. Words used by Trump to judge women based on their appearance rather than their intelligence or personality
|Valuing women based on their appearance rather than their intelligence or personality|
|She looked like a Snowman(woman)||1|
|She does not even look presidential||1|
Negative Evaluation of Women: Women as Dishonest Liars
To Trump, women are two-faced. While describing them as weak and dependent, he also accuses them of being hypocritical, and worse than men. It is the case of all the Tweets devoted to Hillary Clinton: of the 567 Tweets included in the corpus, 299 name Hillary as “crooked”. She is also portrayed as a “corrupt” and “colluded” person, who is “100% owned by her donors”, “bought and paid for by Wall Street, lobbyists and special interests, [and that] will sell our country down the tubes!”. She is defined as a “Guilty [candidate and thus she] cannot run”.
Hillary and other women are also often described as liars. Specifically, Hillary Clinton is referred to as a “A PATHOLOGICAL LIAR”-capital letters in the Tweet) and a “hypocrite” “disloyal person”, and thus she is “unfit to be president”.
The same is said about female news reporters, who are accused of “fraudulent editing” and “mak[ing] up things that [he] never said”.
Table 4. Words used by Trump to convey negative evaluation of women: Women as dishonest liars
|Negative evaluation of women: women as dishonest liars|
Semantic Derogation/Disparagement of Women
Trump makes his sexist and misogynistic remarks on several occasions by using negative lexicalisation. He describes women as being “disgusting” “clown[s]”, who are “terrible”, “sneaky”, or “ill-fit”, just to name a few examples of his labellings.
His former political aid Omarosa Manigault has been a particularly targeted victim of this type of disparagement. She is often called “dog”. Dogs are the most prototypical pets, known for being man’s best friend. However, when applied to a female, the word conveys negative connotations, implying ugliness and promiscuity. The linguistic term used to denominate the generic female dog is ‘bitch’ and it is one of the most common term of opprobrium for a woman, condensing the senses of malicious, spiteful, and bossy.
Trump’s comments belittle women by comparing them to disgusting animals; his words convey the idea that women are plainly disgusting, or at least closer to beasts than to human beings.
Table 5. Words used by Trump to express semantic derogation/disparagement of women
|Semantic derogation/disparagement of women|
|Unfit or ill fit||14|
Women Are No More than Possessions
For Trump, women are only possessions that can be owned, bought, or sold. In a Tweet referring to former Miss Universe Alicia Machado, he calls her: “My worst Miss U.” The possessive adjective ‘my’ might be linked to the fact that Trump is the patron of the Miss Universe contest, or that he actually thinks that she is ‘his’, one of his possessions. Again, this represents women as submissive dehumanised sexual commodities at his disposal.
Vulgarity When Speaking About Women
One of the President’s Tweets reads “@megynkelly The Bimbo Back in Town. I Hope Not for Long” (Aug. 25). This Tweet refers to a preceding situation in an interview where Trump made sexist comments about Megyn Kelly:
She’s a lightweight and, you know, she came out there reading her little script and trying to be tough and be sharp. And when you meet her, you realize she’s not very tough and she’s not very sharp […]. She gets out there and she starts asking me all sorts of ridiculous questions, and you could see there was blood coming out of her eyes, blood coming out of her… wherever…Kelly was a bimbo.
This comment, made by Trump the day after the first Republican debate when Kelly challenged him with several questions, is a clear sexual reference to a woman’s menstrual cycle. In the Tweet included in the corpus, Trump uses a negative lexicalisation in an attempt to discredit Kelly by calling her a ‘bimbo’, a term with a sexual connotation meaning a physically attractive woman who lacks intelligence.
Other sexualised negative lexicalisations used in the corpus are “disgusting (check out sex tape and past)” and “a con”, referring again to former Miss Universe Alicia Machado.
Table 6. Vulgar words used in Trump’s Tweets when speaking about women
|Vulgarity when speaking about women|
This study has analysed the ways in which sexist ideologies and practices manifest themselves in Trump’s Tweets about women. They include a variety of lexical and rhetorical strategies that can be summarised in the following seven points:
- Women are weak, lacking in strength and ability, incompetent and ‘mentally instable’
- Women are dependent beings
- Women are to be judged based on their appearance rather than their intelligence or personality.
- Women are dishonest liars and worse than men
- Women are disgusting animals
- Women are no more than possessions
- Women can be described with vulgar terms
These points highlight that Trump’s attitude towards women is guided by patriarchal ideologies implicated in the denigration and the objectification of women. According to him, women are weak, incompetent beings who are mentally instable on one hand, and dishonest dangerous liars on the other, and thus not capable of achieving and keeping significant roles in society.
With reference to Mill’s (2008) distinction between overt and covert forms of sexism, it can be said that Trump’s Tweets convey his sexist ideologies prevalently in a rather overt way. A mix of (often sexualised) insults (e.g. ‘dog’, ‘very dumb’, ‘neurotic’), catch-words (e.g. ‘dopey’, ‘loser’, ‘dangerous’), and humour (e.g. ‘snowman(woman)’, Pocahontas) are used to negatively represent female opponents and women in general. Following the “model” of hegemonic masculinity, Trump reiterates the ideals of physical power that are “deeply embedded in the American culture” and so his messages are perhaps appealing to those who prioritise such principles and who are moved more by ‘pathos‘ than by ‘logos‘.
It must be said that Tweets are not a private context and thus his speech is different from a non mediatised context, such as the Access Hollywood tape where he spoke frankly and revealed what was going on in his mind. His Tweets are fuelled by the underlying motives of attaining -and later on keeping- his presidential status and consent. Thus, his Tweets are less straight-forward than he might have us believe, perhaps fearing that his words might negatively affect his run for the US presidency.
However, his vocabulary still perpetuates a male-centric social hierarchy in which women are relegated to a submissive position, away from significant social positions.
Of course, further investigation is needed. Further studies could analyse whether Trump also uses instances of benevolent sexism, that is to say cases of sexism that represent evaluations of gender that may appear subjectively positive (subjective to the person who is evaluating), but are actually damaging to people and gender equality more broadly (e.g., the ideas that women need to be protected by men because they are weak and that they should respect ‘traditional’ gender roles). The hypothesis is that his use of benevolent instead of sexism is actually the other side of the same coin: patronising language would further confirm Trump’s idea of women as an inferior sex.
Trump is articulating an ideological stance which suggests that men are superior to women, and this ideology is perhaps diffused amongst his supporters. Moreover, his political ascendency speaks to how these ideological beliefs risk to become dangerously ingrained in language and society.
This is true not only for the US’ case, but also at an international level. Sexism as a populist discursive strategy has been prevalent in conservative politics also in other parts of the world (e.g. Haider, Strache, Abbott, etc.) Moreover, given the growing number of prominent female populist leaders (such as Marine Le Pen, Roxana Miranda and Sarah Palin), the “weak yet complex” relationship between populism and gender needs further investigation to understand future politics. Sexism will continue to have negative effects if it is not recognised as a form of discrimination and injustice and contested.