All for show? Does nationalistic rhetoric within speechmaking act as a tool to downplay socioeconomic inequality? An analysis of Nationalistic Rhetoric in the Speeches of Trump, Putin, and Xi Jinping

Executive Summary

This research report aims to decode common patterns of speech within three national address speeches. This was carried out using NVivo, a qualitative research tool that allows for effective analysis of textual sources. All of these speeches were chosen due to them offering insight into leaders looking forward to a new horizon of their governance, whether through a new year, or a new term. They also all occur at a time of key geopolitical significance, with the ongoings of the Russia-Ukraine conflict, (CFPA, 2025) key geopolitical moves by Trump (Aratani & Smith, 2025), and China’s moves to strengthen its domestic economy, in light of global instability (Desheng, 2025). 

Within this report, I aim to outline that despite all of these countries being in a time of growing domestic socioeconomic inequality, all three of these speeches push an underlying nationalist rhetoric. Promoting togetherness for political gain, despite all three countries being in a period of growing wealth disparity, causing inequality. This can be clearly seen when patterns of speech are analysed through Van dijk’s CDA framework (1993), with a specific focus on banal nationalism (Billig, 1993) and the repeated use of “we” to consolidate national sentiment (Chen, 2024 p.213) . Overall arguing that the togetherness and national sentiment within these speeches is a tool to garner political support and hide domestic socioeconomic inequality. 

CDA offers an excellent framework through which to perform qualitative analysis, due to its ability to highlight the “role of discourse in the reproduction of dominance and inequality” (Van Dijk, 1993 p. 253). This comes within the report through “a lexical analysis. This means simply looking at what kinds of words there are in a text” (Machin & Mayr, 2021 p. 20) . With the understanding of the basics of banal nationalism helping to underpin this, due to its approach of highlighting subtle and unconscious nationalistic framing within speech, whereby “nations are reproduced within a wider world of nations” (Billig, 1995 p. 15). Some context will also be provided through Korozhan’s speech analysis techniques, outlining each speech as follows. 

SPEAKER → SPEECH → OCCASION → AUDIENCE → EFFECT

(Korozhan, 2016 p. 241)

Methodology

This study uses a qualitative research design within an interpretivist focus, aiming to uncover how nationalist rhetoric may obscure socioeconomic inequality (Halperin & Heath, 2020). Van Dijk’s (1998) Critical Discourse Analysis framework was employed to analyse official speeches by Trump, Putin, and Xi Jinping, selected for their symbolic value and geopolitical influence. Analysis was conducted deductively using NVivo, supported by Van Dijk’s CDA framework and Billig’s (1995) theory of banal nationalism. Thematic analysis was focused on discursive strategies such as nationalistic storytelling and the national “we”. NVivo allowed the organisation of textual data and identification of recurring themes, namely through word frequency. This method allowed for interpretation of political speeches, highlighting the centrality of language in reproducing ideology and legitimising power (Van Dijk, 1998).

Speech 1 - President Xi Jinping's 2025 New Year message

Full Analysis: Xi Jinping's New Years Address

Speaker: Xi Jinping - Chinese President

Speech: New Years Address

Occasion: New Year - Looking back on the successes of the past year and looking towards the future of the nation at the end of the calendar year

Audience: Population of China and global world leaders

Effect: To embolden national spirit and bring into light the successes and goals of the nation to the world

Firstly, within this speech Xi Jinping's nationalistic framing is apparent from the start. Opening with the “journey” that the people of China have travelled in the past year together. Achieved through stories that the Chinese people can connect with, such as visits to local areas, as well as national olympic success. “I have visited many places across the country and seen how our people enjoy their enriching lives. I saw the big, red Huaniu apples in Tianshui, Gansu and the fishing boats in Aojiao Village, Fujian loaded with their catches” (Xinping, 2024). Reflecting a “common identity” through storytelling, a key nationalist political trope (Rumina, 1999). 

Furthermore, “Chinese New Year's Addresses frequently utilize high-value modal verbs and employ the inclusive pronoun "we" to consolidate “collective national sentiment” (Chen, 2024 p.213). A trend that is clearly seen when using a word frequency search within NVIVO software. “We” appears 213 times within this speech, as the second most prominent word, its inclusion is one which must be highlighted due to it being a deliberate choice of phrasing, one which appears in all three speeches analysed within this report. 

On top of deliberate language choices, this speech also has many trends aligning with the idea of banal nationalism. Namely through the Chinese flag being within the title image, as well as constant reinforcement of a shared national identity (Rumina, 1999). This shared identity is seen through the aforementioned examples, as well as in quotes such as “our motherland” and “China's bowls are now filled with more Chinese grain” (Xinping, 2024). This highlights the idea of an imagined “common identity” (Rumina, 1999), a tool of nationalistic speech and an idea that underpins banal nationalism, as it orchestrates the day-to-day acknowledgement of the nation. 

Despite this nationalistic connection between the people the speech clearly aims to manufacture, in reality this connection is not as prominent. Economic inequality in China is on the rise, with wages growing disproportionately, leaving the bottom 90% of earners left behind. “China has had a limited impact on inequality, resulting in a reduction of the top income decile of only 4% in China, relative to 25% in France and 19% in the U.S.” (Stanford, 2024). Despite much of this speech highlighting China's successes in response to an ever changing global market, the question that must be posed when CDA is applied is, how much of this “success” will trickle down to the average citizen financially and in subsequent freedoms? 

Figure 1 -  word frequency search of Xi Jinping's speech using NVIVO

Figure 2 -  image containing the Chinese flag

Speech 2 -  Donald Trump’s joint address to Congress

Full Analysis: Trump - Address to Congress

Speaker: Donald Trump - American President 

Speech: Joint Address to Congress

Occasion: First Congressional address of his new presidency 

Audience: Population of USA and global world leaders, as well as congressmen/women in the stands

Effect: To further his MAGA agenda, outlining his plans and successes so far

The second speech within this analysis, Donald Trump's congressional address offers further insight into many of the common tropes within nationalistic speechmaking. Once again with the inferred aim of creating a “national identity” (Rumina, 1999), with the goal of using this national pride to make people less aware of socioeconomic inequality, something that can be unpacked using CDA . 

Similar to Xi and Putin, this speech often utilizes emotional stories in order to prop up the national message. Examples of which are seen throughout, with the stories of “Payton McNabb”, successes of the first lady and the history of US successes. These anecdotes do not function solely as embellishment, but rather act as rhetorical scaffolding for an imagined “common identity” (Billig, 1995), masking internal divisions by evoking emotionally resonant narratives of shared history and values. A skill that Trump has mastered and mobilized, often for political gain, through the MAGA crowd (Johnson, 2024). 

As well as this, this speech continues the trend of the common, deliberate and tactical use of “we” within speech (Chen, 2024 p.213). Appearing 133 times within the address, more than any other word. Interestingly though, it is used in two ways. To speak to all american people directly e.g. “We suffered the worst inflation in 48 years”, as well as to speak to his political supporters directly, e.g. “ We won all seven swing states” (Trump, 2025), showing both nationalist grouping through use of a shared national experience and through shared nationalist “political ideology” (Rumina, 1999). 

Constant showings of banal nationalism permeate this text, most commonly through the use of shared national ideas (Billig, 1993), in this case “the American dream”, the idea that all hard working Americans can see success and have the life they want, i.e. equality of opportunity (Churchwell, 2021). This idea was chosen in particular, in order to highlight how it is used as a tool to hide socioeconomic inequality. Trump  often reiterated in this speech phrases such as “the American dream is surging bigger and better than ever before” (Trump, 2025). However, this seems to be untrue, many Americans lost out massively economically due to his tariffs effects on the markets (an element he said would do the opposite) (Aratani & Smith, 2025). On top of this, socioeconomic inequality remains a rising issue within the USA (Hernandez-Kent, 2024). With economic inequality on the rise, and Citizens United v. FEC ruling implying that spending money equates to free speech (FEC, 2010), does this pose the idea that some people are now more free than others? Overall, once again ending at the same question as before, for all Trump's talk of it, how much of this “success” will trickle down to the average citizen? 

Figure 3 - word frequency search of Trump's speech using NVIVO

Speech 3 - Vladimir Putin’s new year's address

Full Analysis: Putin - New years address

Speaker: Vladimir Putin - Russian President

Speech: New Years Address

Occasion: New Year - Looking back on the successes of the past year and looking towards the future of the nation at the end of the calendar year

Audience: Population of Russia and global world leaders

Effect: To embolden national spirit and bring into light the successes and goals of the nation 

The third and final focal point of analysis, Putin’s new year's speech, once again follows many of the same styles outlined within this research. Despite being the shortest of the three, there is still a clear example of nationalistic storytelling, in this context related to Russian military successes during WW2. This story aims to bring people together within the nation in order to support Russia’s current military conflict within Ukraine (CFPA, 2025). Being very relevant when analysed along the CDA framework, as there are continuous instances of language choices being deliberately used in order to reflect the nation as “one people”, a nationalistic trope well established by this point. Critical when doing CDA, due to this togetherness not reflecting the true nature of discourse and power within Russia, as seen through socioeconomic figures. 

Within this speech, banal nationalism once again comes into play, with its form being the way in which the nation is spoken of. The repeated use of phrases such as “our nation”, “our unity” and “our motherland” (Putin, 2024) shows the fostering of an unconscious national connection. Likely being repeated so much due to the need for wartime support from the people, although compared to the oligarchs holding most the wealth (Artemchuk. 2025), they are unimportant, and therefore being sold this “national spirit” and connection to foster troop numbers and national support for the war. 

Finally, NVIVO was once again used to highlight consistent use of the word “we”. Showing up as the most common word and making up over 6% of the speech, it can be seen that just as with the other speeches, it is acting here as a tool to consolidate collective national sentiment. However, despite this sentiment, Russia is the most economically unequal country within this analysis, with “Nearly half of pre-tax national income (going) to Russia's top 10 %” (European Parliament, 2018). This shows a huge level of inequality, so much so that there is no talk of economic “success” within this speech that was present in the others. But rather a noticeable lack of mention, with the entire focus being on this “national spirit”. 

Figure 4 -  word frequency search of Putin’s speech using NVIVO

Conclusions

Overall, this research has used critical discourse analysis (Van Dijk, 1993), combined with banal nationalist theory (Billig, 1995) in order to highlight common rhetorical trends within these speeches. This method has proven that there are clear speech trends between these three leaders. Coming in the form of:

• The nationalist “we”

• Nationalistic storytelling

• Unconscious examples of nationalistic rhetoric and imagery

These trends can be seen through comparison of the most commonly used words across all three, with words such as “people” ,“country” and “we” being among the most common, all with nationalistic connotations. 

Figure 5 -  word cloud of common words across all speeches

In regards to a shared relationship between discourse and power (Van Dijk, 1993 p. 253). These speeches all differ slightly in their approach to hiding socioeconomic inequality. However, whether through Xi’s talk of “Coordinated development across regions”, Trump's “MAGA” ideals, or Putin’s lack of mention of economics. What is clear is that all three countries have rising wealth disparity, which this report aims to have argued is hidden within these speeches by nationalistic rhetoric and framing. With the collective “common identity”, a rhetorical tool aimed at hiding these divides. 

Figure 6 -  Graph highlighting income growth disparity in US, China and Russia

Reflections

This report was one which took a lot of thought and time. I found using NVIVO challenging but helpful, allowing me to group the “we”’s made it very effective, as well as word clouds which were good at illustrating my point. In terms of the speeches, I found they all had interesting trends and that this report could have gone a number of ways. When speaking to classmates, it was interesting to hear ideas that hadn’t crossed my mind. Analysis and breakdown of the speeches was a sizable undertaking (especially Trump’s), however I enjoyed connecting to the different frameworks for speech analysis, although this did cause some initial confusion. Overall, while this was one of my more difficult assignments of the year, I found it pleasant and I'm glad to have completed it to the best of my ability. 

Final Word Count: 2198

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