Transformation of Political Discourse: Language Weaponisation

Full Text

Introduction

Weaponisation of language is a phenomenon which clearly demonstrates the immense power a language holds. From political propaganda to online hate speech and disinformation, the manipulation of language can have far-reaching consequences for societies and individuals. This article explores the weaponisation of language in linguistics, examining how language can be used as a tool to divide, manipulate, and control people.

One of the key aspects of weaponisation in language lies in framing [1. Р. 157], which involves presenting information or ideas in a particular manner to shape public opinion. Politicians and media outlets, such as newspapers, magazines, radio, TV, and websites, often employ framing techniques to influence the perception of events among the masses. By using selective language, emphasising certain aspects, or employing loaded terms, individuals or groups can manipulate public discourse and steer it towards their desired narrative. The media’s role is significant due to design, argument, and dissemination of ideology [2; 3]. Instances of conflicts in politics are as follows: neo-Nazi movements across Europe, Trump’s election campaign, Brexit, and closing of borders (e.g. Serbia, Hungary) to refugees and asylum-seekers [4].

Current approaches to discourse practices address to critical discourse analysis (henceforth CDA) when considering social and political construct to which language weaponisation can be attributed. Even though CDA encompasses abundance of theoretical and methodological approaches, we need to pay tribute to the initial works by N. Fairclough, R. Wodak, T. Van Dijk, to name just a few, who incited further studies of the discourse analysis [5–7]. The authors share van Dijk’s viewpoint on the multidisciplinary nature of CDA, as language is no longer used as an ideologically neutral means of communication [7].

Nowadays, researchers apply a corpus-based approach (a quantitative study), together with CDA (a qualitative study) to augment the potential of linguistic research. Baker (2006) describes the advantages of the corpus-based approach to discourse studies, stating that corpus can reduce biases, remove constraints in communication, and show the changing nature of discourses [8]. Chao Liu (2020) investigates national image, adopting corpus-based critical discourse analysis to social media [9]. L. Flowerdew (2012) speculates on multimodal view on the discourse presenting overlapping corpus-based, textual, critical, and contextual approaches [10]. These tendencies, together with a synergy of CDA and corpus-based discourse analysis (henceforth CBDA) motivated the authors to study the weaponisation of language of D. Trump. The authors’ choice for merged methodology is relevant as weaponised language is studied within the political discourse on micro- and macro levels [11].

The evaluation of Donald Trump’s speeches at the Republican National Convention in 2016 and 2024 was used for the data analysis.

We hypothesise that CBDA, together with CDA, increase the understanding of how leaders use language weaponisation to gain dominance in social and political groups. Research Questions

The article aims to investigate the shift of the weaponised language in D. Trump’s political speeches.

RQ 1: Has Trump’s language in 2024 become more weaponised compared to 2016?

RQ 2: Are there any specific rhetorical devices in Trump’s weaponised language which can manipulate society’s opinion?

RQ 3: What kind of linguistic strategies does Trump use in his speeches at the Republican National Convention to achieve his political goals?

Let us briefly outline the sociopolitical events from which the term weaponised language comes.

Historical Aspects

Since the inception of the concept of warfare tactics, formulated by the Chinese philosopher Sun Tzu (6th century BC) in The Art of War, that “supreme excellence consists in breaking the enemy’s resistance without fighting’, politicians applied the similar principle to the use of language as a weapon” [12]. The earliest usage of the term language weaponisation or — weaponisation of language — can not be traced exactly due to the lack of explicitness in the meaning. It dates back to early 1900s, starting with a metaphorical meaning and transforming to a weaponised political discourse^[1]. The propagation of a newly coined term encompassed the erupted linguistic battles. Alfred Korzybski in Science and Sanity (1933), and Stuart Chase in The Tyranny of Words (1938) discussed the ecological usage of language [13; 14]. Hayakawa’s ideas in Language in Thought and Action (1945) were further developed and extended by George W. Kelling in Language: Mirror, Tool, and Weapon (1975) where he hypothesised that language determines the perception and cognition of a person together with their social behaviour [15]. The similar idea was expressed in La Manipulación del Hombre a Través del Lenguaje (The manipulation of men through language) [16]. The breakthrough in linguistics, which analysed weaponised language from the perspective of communicative problems was in Language, the Loaded Weapon: The Use and Abuse of Language Today by Bolinger [17].

Since then, weaponisation of language has received different interpretations as increasing number of vivid practices or pillars of material violence [18]. This definition emphasises the idea of language weaponisation as a systematic process, which does not include inaccurate or false information produced by software bugs [19]. Subversive activities of the weaponised language are aimed at undermining community’s information-psychological core, affecting public trust and interaction. Weaponised narratives achieve influence on strategic level being very often integrated on various levels simultaneously to achieve maximum effect. In other words, it is an attack on the sociopolitical center of gravity [20].

Population may be oppressed “not only because of their language, but through it” [21]. Therefore, linguistic means may be harmful and linguistic choices people make could be associated with the dehumanisation of others [18; 22]. The term harm acquires significance in this context since it refers to minoritised individuals being affected by certain practices to destabilise their environment [23].

Theoretical Background

Weaponisation of language is particularly evident in political propaganda, where rhetoric is used to sway public opinion and consolidate power. Through the strategic use of persuasive techniques such as emotional appeals, euphemisms, or demonisation of opponents, politicians can manipulate language to create divisions, incite fear, and rally support for their agendas [5. P. 56].

In this respect good, defensible war rhetoric should be distinguished from pathos, propaganda, non-constructive “rhetrickery” [24]. Historical examples, such as Nazi Germany’s use of propaganda during World War II or more recent instances of political manipulation, highlight the dangerous potential of weaponisation of language. For example, a euphemism ‘‘Final Solution’’ applied by the NAZI leaders in Germany to implement their destructive policies against the Jews meant political, economic persecution and finally physical annihilation^[2]. However, contrary to euphemisms, other lexical means may be used to reveal threat and violence. The Washington Post (29 April, 2011) named the US Air Force’s “new revolutionary surveillance system” the “Gorgon Stare”^[3] using an allusion to Greek mythology and deliberately creating the feeling of fear and uneasiness.

Dehumanisation of vulnerable groups or political opponents is manifested in “depersonification” on the stylistic level. For example, Trump’s figurative comparison of immigrants with “a garbage can for the world” because of illegal border crossings; Hillary Clinton’s calling Trump supporters as ‘basket of deplorables’, or Benjamin Natanyahu’s reference to the Italian government as ‘wolf in sheep’s clothing”^[4].

Manipulation of public opinion in order to demonise the opponent may occur in the so-called truthful sandwiches when a lie is inserted deliberately in some context serving as a misleading factor. For instance, the Japanese Representative to the UN, Shino Mitsuko^[5], claimed that Japan is the only country that has ever suffered atomic bombings during war and highlighted the catastrophes of Hiroshima and Nagasaki without naming the country responsible. However, Russia’s nuclear threats were mentioned in this context, which was nothing but shifting the blame of using nuclear weapons to the other country.

Through linguistic manipulation, oppressive regimes or dominant social groups can reinforce existing power structures, suppress dissent. By controlling the narrative through censorship, surveillance, or linguistic restrictions, those in power can maintain their authority and silence opposition.

Research Methodology

Corpus-based Discourse Analysis

Data collection was focused on Donald Trump’s speeches after the first and second election campaigns at the same event The Republican National Convention, July 21, 2016 and July 18, 2024 in order to identify, if there was a shift in his discourse.

The structure of the two speeches was comparable because of particular genre and communicative conditions, aimed at the wide heterogeneous audience. Primarily, the speeches were analysed using CBDA to identify common speech patterns, find general and specific lexis characteristic to Trump’s discourse, and infer his lexicon to effectively manipulate social groups’s opinion.

We formulated a research hypotheses on how the speaker’s lexical and pragmatic choices may differ, and tested it through quantitative and qualitative analyses.

For CBDA the authors used AntConc and Voyant Tools as freeware instruments to analyse and visualise concordance lines, study words associations, semantic prosody and semantic preferences, identify frequencies, modality, and rhetorical strategies in Trump’s speeches. The number of words in the first corpus amounted 5.264 words, and in the second one — 12.252 words, accordingly. The words related to the language weaponisation were extracted from the two corpora, and then raw frequencies were counted in both documents. As the speeches were unequal in size, relative frequency of the words was calculated to estimate the occurrence of the word in both corpora as if they comprised one million words (frequency was divided by the sample size). The frequency of the language weaponisation usage is presented in Figure 1.

Figure 1. The increase in the frequency of weaponised language in 2024 compared to 2016
Source: compiled by Anna V. Zabolotskikh, Elena E. Sokolova, Daria V. Tavberidze, & Yuri S. Medvedev.

The obtained results presented in Figure 1 demonstrate an increase in the frequency of weaponised language in 2024 compared to 2016. Another set of words displayed the uncommonly low frequency rate of some of the weaponised words in 2024 compared to 2016 (Figure 2).

Figure 2. The decrease in the frequency of weaponised language in 2024 compared to 2016
Source: compiled by Anna V. Zabolotskikh, Elena E. Sokolova, Daria V. Tavberidze, & Yuri S. Medvedev.

Figure 2 represents the decline in using of such weaponised words as violence, terror, threat, etc. This discrepancy demonstrates that in 2024, Trump continued to concentrate on weaponisation, however, he changed his focus because of the political situation in the country.

The analysis of concordance lines using Key Word in Context (KWIC) in AntConc tool revealed, that negative semantic prosody was expressed through traditional weaponised language, such as crime (violence, terrorism, chaos, and threat) and immigration (illegal, lawlessness, wall). The following example is overloaded with weaponised rhetoric. “Our convention occurs at a moment of crisis for our nation. The attacks on our police, and the terrorism in our cities, threaten our very way of life. Any politician who does not grasp this danger is not fit to lead our country. Americans watching this address tonight have seen the recent images of violence in our streets and the chaos in our communities. Many have witnessed this violence personally, some have even been its victims”. Along with that, in 2016, Hillary Clinton, framed negatively, was associated with disaster, weakness, corruption, and failed polices. However, in 2024, the word border was a predominant negative association, which collocated with ‘border crossing’, ‘closing our border’, ‘border patrol’, ‘border security’, ‘border nightmare’, ‘border polices’, ‘seal the border’, etc. These tendencies in Trump’s speeches are rather predictable, as through such strong negative emotional loading, he demonised his opponents and developed emotional attachment to him and evoked the feeling of the ‘perpetual existence of a hostile external world” [25].

Modality did not vary much in Trump’s speeches in both years, as he was still inclined to use will heavily to express certainty and give future promises (Table). E.g. “Nothing will stop me in this mission because our vision is righteous and our cause is pure. No matter what obstacle comes our way, we will not break, we will not bend, we will not back down, and I will never stop fighting for you, your family, and our magnificent country. Never”.

 Distribution of modal verbs and expressions in Trump’s speeches (2016, 2024) 

Modal verbs	2016	2024
	Total number	Total number
Can	14	39
Will	90	120
Must	7	8
Should	0	9
May	1	2
Have to	7	21
Need to	2	0

 Source: compiled by Anna V. Zabolotskikh, Elena E. Sokolova, Daria V. Tavberidze, & Yuri S. Medvedev.

Critical Discourse Analysis

As the conducted research was twofold, the authors turned from the textual level, which is considered to be a micro-level, to a macro-level — critical discourse analysis — as an interpretative approach [26]. Such holistic approach reflects how the language weaponisation reinforces power dynamics, ideologies and social structures. Weaponised discourse used by Trump lacked logical and sophisticated thought processes [27]. For this purpose, he implemented a stylistic device called parataxis, which was attributed to a prominent feature of his speeches. To create a sense of urgency, emphasis, or to mimic natural speech patterns, Trump used short simple sentences and clauses without conjunction and subordination.

(1) “We rise together or we fall apart.”

This is an illustrative example of parataxis, with two contrasting ideas placed together. The simplicity of the sentence makes it memorable and impactful, reinforcing the idea of unity and collective action. This framing reinforces Trump’s populist narrative us versus them, depicting him and his supporters fighting against a corrupt establishment. This binary framing (rise vs. fall) creates a sense of urgency and positions Trump as the leader who can guide his electorate toward success.

(2) “I am running to be President for all of America, not half of America, because there is no victory in winning for half of America.”

This example emphasises Trump’s claim to represent all Americans, not just a portion. The paratactic structure simplifies the message, makes it accessible to a broad audience, particularly to those who may not engage with more nuanced or formal political discourse. This strategic use of language appeals to a specific demographic—often working-class or less politically engaged voters—who value straightforward, relatable communication. Trump represents himself as a unifying figure and, at the same time, subtly critiquing his opponents as divisive.

(3) “Bullets were continuing to fly as very brave Secret Service agents rushed to the stage, and they really did. They rushed to the stage. These are great people at great risk, I will tell you, and pounced on top of me so that I would be protected.”

The sentences are abrupt and fragmented; the repetition of “they rushed to the stage” creates a real sense of danger. Here the style heightens the drama of the moment to its peak, and the audience views Trump as a resilient leader who survived a life-threatening attack. This narrative humanises his image and serve to legitimise his leadership and reinforce his political agenda.

(4) “They’re coming for your jobs, they’re coming for your homes, they’re coming for your families.”

This statement uses repetition and vivid imagery to create a sense of existential threat. The phrase “they’re coming for” implies that immigrants are actively seeking to harm Americans, reinforcing the idea that they are a dangerous, predatory force. This language stokes fear and resentment, which can be used to justify restrictive immigration policies and rally support for Trump’s nationalist agenda.

Comparing rhetorical strategies in 2016 and 2024, the authors revealed that Trump used tried-and-tested methods to influence people’s minds. He reinforced his central message by repeating key phrases (law and order), he contrasted his political views with the perceived failures of previous administrations (failed polices, weakness), he used emotional appeal to reinforce ideological alignment among his supporters (crying mothers, forgotten men and woman). In 2014, being a right populist, Trump contrasted himself (I) with elite media, big business and major donors; however, in 2024, he was prone to use us in contrast to them (elites).

Findings and Discussion

The authors’ major findings are rather illustrative, and highlight the dynamic nature of Trump’s weaponisation discourse, reflecting both continuity and change in his rhetorical strategies. Figure 1 reveals a significant shift in the frequency of weaponised language to create a sense of crisis or threat. For example, describing immigration as an “invasion” and warning that “bad things are going to happen” exploits fears of crime, terrorism, and economic insecurity. This fear-mongering is used to justify his harsh policies and mobilise support by appealing to emotions, rather than rational argument. Unlike Figure 2 demonstrates a contrasting trend, with a decline in the usage of specific weaponised words such as violence, terror, and threat. This indicates a possible strategic recalibration of Trump’s rhetorical focus, avoiding overtly aggressive terminology which has become less effective with his electorate in 2016. Trump continues to maintain a weaponised discourse through other means, such as negative semantic prosody, however, he diversifies his rhetorical toolkit.

This deliberate spread of weaponised narratives leads to confusion, mistrust, and social division. By manipulating language, Trump creates a distorted reality, undermines public trust in institutions, sows doubt, and furthers his own agendas.

Overall, Trump’s rhetoric in both speeches can be considered as nationalist populism, as he positioned himself (I) as the voice of the people, fighting against “special interests,” “elites,” and “rigged systems”. This proved to be an affective genre cultivating people’s sense of confrontation to ‘dangerous’ others, which means an elite and immigrants, refugees, and terrorists. On the contrary, in 2024 his topicalisation changed to we fighting with decision-makers them. Expressing anger, rage, malice, and revenge has become a marker of his presidential leadership. ‘Going negative’ as a phenomenon of political communication is coupled with vulnerability, which is expressed by simplicity, impulsivity, cruelty, and narcissism [28. Р. 283]. To be easily understood, Trump’s bumptious language is marked by simplicity and informality, which manifests itself in parataxis and certain rhetorical strategies. The choice of a personal pronoun signifies that the speaker wants to become closer to the audience.

Two of US parties are known to frame their key issues around different values: Democrats are focused on empowerment and recovery, whereas Republicans emphasise personal accountability, discipline, law and order [29]. Thus, Democratic leaders, in comparison with conservatives, show a stronger positive valence in terms of the language employing more abstract words. Republican rhetoric is simple, its direct language is characterised by the tendency to use more concrete words and less subjectivity.

We identified the top words by frequency from Trump’s speeches, which demonstrate a tendency for the Republican leader to become more subjective in terms of evaluation (See Fig. 3.). The 2024 speech amplifies less resentment targeting scapegoats. In comparison with 2016, it includes positively charges words: great, beautiful, good, wonderful, incredible. If in 2016 speech the marker of an opponent was marked as Hillary and Clinton, in 2024 it was not so obvious. Weaponised and more concrete language is displayed to a bigger extent in 2016 speech: violence, trade, law, terrorism, percent, work, opponent.

The obvious rhetoric shift may be the evidence of language weaponisation through propaganda, disinformation, and mundane discourse, losing its relevance in today’s world. Trump’s campaign rhetoric suggested a shift in US priorities, with some tactical modifications but with no substantial transitions. The attempt of escalation to be reduced is noticeable, however, the hostile character of the language remains the main strategic approach to convey the key messages.

Figure 3. The word cloud shows Trump’s speeches representation with word size highlighting frequency of the most common lexis in their responses
Source: compiled by Anna V. Zabolotskikh, Elena E. Sokolova, Daria V. Tavberidze, & Yuri S. Medvedev.

Conclusions

The article analysed D. Trump’s speeches at the Republican National Convention in 2016 and 2024 using CBDA analysis merged with CDA. Both methods helped the authors understand how D. Trump used weaponised language to gain dominance in social and political groups. The key findings revealed three tendencies in Trump’s speeches.

First, in 2024, Trump’s language became less weaponised compared to 2016. He reinforces his appeal to the audience using fear and division. Trump’s weaponisation discourse has become less consistent in relying on negative semantic prosody and conflict-oriented framing. The researchers identified Trump’s discourse adaptation to changing contexts and audience expectations.

Second, Trump heavily used parataxis to construct vivid narratives and to express emotional appeal. He used the utmost of this rhetorical device in his speeches: binary oppositions, abrupt, fragmented sentences, which helped him create emotional intensity and the need for immediate actions.

Third, Trump positions himself as the voice of people (I), fighting against elites, however, later he used we who fought against them. This so-called flexible populism in Trump’s speeches showed that he learned lessons from the previous election campaign and unified himself with the people.

This study has some limitations due to the choice of the specific genre of the speeches. Further research can be conducted on a bigger dataset to investigate the nuances which were not studied within the scope of this research.

 

_{¹ The Guardian. URL: https://www.theguardian.com/science/2017/mar/27/weaponise-the-meaning-of-2017s-political-buzzword (accessed: 15.10.2024).}

_{² Holocaust Encyclopedia (2020). URL: https://holocaustencyclopedia.com/ (accessed: 28.10.2024)}

_{³ The Washington Post, 29.04.2011 Whitlock C. Gordon Stare surveillance system gazes over Afghan war zone. URL: https://www.washingtonpost.com/national/gorgon-stare-gazes-over-war-zone/2011/04/29/AF2xIiGF_story.html (accessed: 17.12.2024).}

_{⁴ NPR 01.10.2013 Netanyahu: Iranian President ‘Wolf in Sheep’s Clothing’. URL: https://www.npr.org/2013/10/01/228198603/netanyahu-iranian-president-wolf-in-sheeps-clothing (accessed: 03.11.2024).}

_{⁵ Global Research, 09.08.2022 Chossudovsky M. Commenting Hiroshima and Nagasaki. Blaming Russia for U.S. War Crimes. URL: https://www.globalresearch.ca/commemorating-hiroshima-and-nagasaki-blaming-russia-for-u-s-war-crimes/5789233 (accessed: 28.10.2024).}

About the authors

Anna V. Zabolotskikh

RUDN University

Author for correspondence.
Email: zabolotskikh-av@rudn.ru
ORCID iD: 0000-0002-5253-2733
SPIN-code: 6520-1445
Scopus Author ID: 57217873153
ResearcherId: AAB-4687-2019

Senior lecturer, Department of Foreign Languages, Faculty of Humanities and Social Sciences

6 Miklukho-Maklaya str., Moscow, Russian Federation, 117198

Elena E. Sokolova

Moscow Institute of Physics and Technology

Email: sokolova.ee@mipt.ru
ORCID iD: 0000-0002-1467-3455
SPIN-code: 2013-1826
Scopus Author ID: 56579818200
ResearcherId: G-4265-2019

PhD in Philology, Associate Professor, Department of Foreign Languages

9 Institutsky lane, Moscow region, Dolgoprudny, Russian Federation, 141701

Daria V. Tavberidze

RUDN University

Email: tavberidze_dv@pfur.ru
ORCID iD: 0000-0002-2727-6803
SPIN-code: 3183-1668
Scopus Author ID: 57195529929
ResearcherId: ABW-5226-2022

PhD in Philology, Associate Professor, Department of Foreign Languages, Faculty of Humanities and Social Sciences

6 Miklukho-Maklaya str., Moscow, Russian Federation, 117198

Yuri S. Medvedev

RUDN University

Email: medvedev_yus@pfur.ru
ORCID iD: 0000-0003-1843-9110
SPIN-code: 7185-7796
ResearcherId: ACP-6391-2022

PhD in Historical Sciences, Associate Professor, Department of Foreign Languages, Faculty of Humanities and Social Sciences

6 Miklukho-Maklaya str., Moscow, Russian Federation, 117198

References

Supplementary files