International Journal of English Linguistics; Vol. 10, No. 2; 2020
ISSN 1923-869X E-ISSN 1923-8703
Published by Canadian Center of Science and Education
26
A Typical Politician vs. a Lunatic Businessman: Different Language
Styles of Hillary Clinton and Donald Trump
Yuqing Zhao
1
, Ting Wu
1
& Huiyu Zhang
1
1
Department of Linguistics and Translation, Zhejiang University, Hangzhou, China
Correspondence: Huiyu Zhang, Department of Linguistics and Translation, School of International Studies,
Zhejiang University, Hangzhou, 310058, China. E-mail: z[email protected]u.cn
Received: November 23, 2019 Accepted: December 28, 2019 Online Published: January 18, 2020
doi:10.5539/ijel.v10n2p26 URL: https://doi.org/10.5539/ijel.v10n2p26
Abstract
The victory of Donald Trump over Hillary Clinton in the 2016 US election shocked the media and the public
around the world. In an attempt to understand the linguistic differences between Clinton and Trump that might
explain the unexpected result, both quantitative and qualitative methods were used in the research to analyze
their particular language features in the speeches and different strategies employed in their debates. The
quantitative result showed that Trump’s language was not as rich as Clinton’s. And in terms of the qualitative
analysis, it was found that Clinton tended to use the pronoun you more than Trump and that both of them were
inclined to make frequent use of we in their campaign speeches. As for debate strategies, Trump, compared with
Clinton, was more likely to interrupt and repeat for the purpose of showing power and leaving the audience a
stronger impression. The research offers insights into Trump’s and Clinton’s linguistic features and debate
strategies that might account for Trump’s victory in the election.
Keywords: Donald Trump, Hillary Clinton, linguistic features, political discourse, quantitative and qualitative
analysis
1. Introduction
Almost three years into Trump’s presidency, the world has witnessed many of his surprising moves, including
dropping out of the Trans-Pacific Partnership Agreement (TPP) on trade and the Paris Agreement on climate
change, issuing a ban on immigrants from some Muslim countries, and implementing increasing trade tariffs on
other countries. His surprising policies can be a very long list. What Trump has done in the past years is a
reflection of the fact that he started to abandon America’s old tradition of being a global sheriff. Instead, he
started to increasingly focus on the interests of America. “Making America Great Again” was exactly the slogan
that Trump used during the 2016 US election, helping him win the support of a large number of voters. The
approaching 2020 United States presidential election again reminds us of the unexpected victory of Donald
Trump in the 2016 US election. In the meantime, as a seasoned politician, Hillary Clinton, the other presidential
candidate in the 2016 election, was expected to win by most of the media and the public around the world. The
election result, however, was just the opposite, rendering people confused and making them wonder about the
reasons behind the unforeseen outcome.
In the wake of it, a range of perspectives have been provided to account for the stunning victory of Trump. Some
scholars have connected his success to racial and sexual factors (Major, Blodorn, & Major Blascovich, 2018;
Lajevardi & Abrajano, 2019; Bock, Byrd-Craven, & Burkley, 2017; Bracic, Israel-Trummel, & Shortle, 2019;
Philpot, 2018). For instance, white voters’ concerns about their racial identity, anti–Muslim sentiment in the US,
sexist attitudes towards women, and the racial factor in the gender gap (Major, Blodorn, & Major Blascovich,
2018; Lajevardi & Abrajano, 2019; Bock, Byrd-Craven, & Burkley, 2017; Bracic, Israel-Trummel, & Shortle,
2019; Philpot, 2018) all contributed to Trump’s victory. Additionally, other factors such as economic
dissatisfaction, social problems, religious beliefs, and voters’ trust have been believed to serve as predictors for
supporting Trump as well (Monnat & Brown, 2017; Franco, 2016; Whitehead, Perry, & Baker, 2018;
Shockley-Zalabak, Morreale, & Stavrositu, 2019). These studies mostly explore the issue from a sociological or
psychological perspective, analyzing external factors that are related to economy, society, and most importantly,
the potential voters. The internal factors of the two presidential candidates, however, have not been thoroughly
examined.
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Hence, this paper focuses on the two candidates to analyze some potential reasons. Since a huge amount of
speeches and debates are involved in presidential campaigns, language is a key element during the election
period. Many researchers have actually identified that language is a powerful weapon for the success of many
politicians (Tenorio, 2002; Ricks, 2018; Ernst, Esser, Blassnig, & Engesser, 2019). In view of that, the research
aims to compare the two candidates’ language styles to dig out the secret of Trump’s incredible victory over
Clinton. By looking into different language features of the two candidates and how they employed language
during the election period, it is expected that, from a linguistic view, some possible explanations for Trump’s
victory can be found. In this research, both quantitative and qualitative methods are used to examine the
similarities and differences in the speech language and the debate performance of Clinton and Trump. With the
help of statistics and the theory of critical discourse analysis (henceforth CDA), “the subjective nature of the
qualitative analysis” (Abbas, 2019, p. 505), to some extent, is expected to be overcome.
Overall, this study attempts to address the following two questions:
1) What are the linguistic features in Clinton’s and Trump’s speeches, and what strategies were used in their
debates?
2) How could the linguistic features in Clinton’s and Trump’s speeches, and their debate strategies affect the
election outcome?
2. Literature Review
2.1 Campaign Language and Debate Strategies
When it comes to individual factors of the two candidates, their language has been a topic of interest for many
scholars. For example, Savoy (2018) examined the style and rhetoric of Clinton and Trump in terms of both oral
and written forms. His work pinpointed a bigger difference shown in the two forms for Trump and a fact that
Trump tended to be more direct than Clinton. A similar finding was provided by Edward, Hutahaean, Kurniawan,
and Hamuddin (2018). They examined the relationship between language and power by investigating speech acts
of Clinton and Trump during the 2016 presidential debate. The results identified that Trump seemed to be more
directive while Clinton was more indirect. Language of the two candidates also revealed gender differences. In
Grebelsky-Lichtman’s and Katz’s (2019) research, both verbal and nonverbal languages were analyzed, which
revealed that Clinton and Trump presented themselves as in line with their gender features and that nonverbal
language was under a bigger influence of gender.
Besides language, abundant studies have also focused on debate strategies of the presidential candidates.
Specifically speaking, Jacobsen (2019) analyzed interruptions during the first 2016 US presidential debate, and
provided an explanation as to why Trump was viewed as the one that interrupted frequently. Quam and
Ryshina-Pankova (2016) reviewed patterns of interaction with voters in the campaign speeches of three
candidates, namely, Trump, Clinton and Sanders. By employing the Engagement framework, it was shown that
Trump differed from the other two more mainstream politicians in terms of strategy use. By analyzing Clinton’s
and Trump’s speech themes and discourse strategies, Liu and Lei (2018) found that Clinton was more likely to
appeal to reason while Trump attempted to appeal to negative sentiments during 2016 election campaigns. The
above studies have offered insights into the two candidates’ language features and strategies, but only a few of
them conducted their research from a linguistic perspective (e.g., Liu & Lei, 2018; Savoy, 2018).
2.2 Speeches and Debates as Political Discourse
Numerous studies have concentrated on the analysis of political discourse such as political speeches and political
debates. In terms of research subjects, many researchers laid emphasis on the speeches of political leaders
(Sharififar & Rahimi, 2015; Borriello, 2017; Carreon & Svetanant, 2017; Alemi, Latifi, & Nematzadeh, 2018).
As for research content, gender issues in political settings (Vasvári, 2013; Dicu, 2018; Petlyuchenko &
Charnyakova, 2019), strategies and tactics such as silence to realize political goals (Alagözlü & Sahin, 2011;
Ponomarenko, Vasilkova, Volskaya, Kasperova, & Nikolaeva, 2018; Alemi, Latifi, & Nematzadeh, 2018), and
techniques like irony, metaphors, and the use of hyperboles, acclaims, attacks and defenses in political speeches
and debates (Benoit & Sheafer, 2006; Nuolijärvi & Tiittula, 2011; Linkeviciute, 2019; Abbas, 2019) are among
the themes of interest for many scholars. After the 2016 election, the whole world had its eyes on the new
president of the United States. Extensive literature has investigated Trump’s speeches, debates, and his tweets on
social media. For example, the element of populism was found in Trump’s discourse (Chilton, 2017;
Montgomery, 2017; Demata, 2017). Moreover, Trump’s controversial comments on racism, immigration and
Islamophobia have also been topics of interest (Terrill, 2017; Demata, 2017; Waikar, 2018). Apart from that,
many scholars have directed their attention beyond Trump, providing an overview of Trump’s uniqueness from
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other US politicians in the 2016 election. Among them, Wang and Liu (2018) looked into changes of stylistic
features of Donald Trump over time and his differences from other politicians. Other comparative studies were
also conducted. For instance, Aswad (2019) demonstrated that Trump tended to use more hyperbolic crisis
rhetoric while Clinton was more likely to employ egalitarian rhetoric. By analyzing speeches of Trump, Clinton
and Sanders, Schoor (2017) asserted that these three US politicians presented different political styles in terms of
ideology. Trump possessed a populist style, Sanders a populist-pluralist style while Clinton an elitist-pluralist
style.
Nevertheless, these studies mostly investigated the overall features of the candidates’ language without a focal
point on some specific details. In an attempt to further narrow down their language features, this research
attempts to focus on pronouns in campaign speeches to illustrate linguistic similarities and differences of Clinton
and Trump with the combination of quantitative and qualitative analysis.
2.3 Critical Discourse Analysis (CDA)
Additionally, among the above studies, many of them utilize linguistic theories and measures as their main
research method, of which CDA is a frequently used one (e.g., Sharififar & Rahimi, 2015; Carreon & Svetanant,
2017; Wang & Liu, 2018). CDA entails applying “discourse analytic techniques” “to interrogate social
phenomena” with the combination of “a critical perspective” (Ainsworth & Hardy, 2004, p. 236). As a kind of
discourse analysis, it is used to analyze the text so that the underlying assumptions and ideologies can be drawn
from the text. Considered as a common way to comprehend and explain the world (Kelsey, 2003), discourse can,
to some extent, reflect the reality of the world. Besides, one of the goals of CDA is to make hidden messages
explicit by a detailed analysis of small linguistic features (Hardy, 2008) or the overall structure of a discourse.
CDA is also designed for detecting links “between language and other elements” (Fairclough, 2001, p. 230) in
our life. Thus, the application of CDA in the analysis of discourse can shed light on the real world, allowing
people to see what is hidden beneath the superficial expressions of words and phrases. Furthermore, albeit CDA
has been used as a common theory in textual analysis, it has also received some criticism during its development.
Some critics have accused it of choosing merely a limited quantity of discourses (Sriwimon & Zilli, 2017) and of
“the imminent risk of ‘cherry picking’” (Törnberg & Törnberg, 2016, p. 134), which means that a single text is
selected to demonstrate the author’s opinion. Thus, the above disapproval raises doubts about the
representativeness of the target texts and the problem of overgeneralization. Nevertheless, solutions can be found
to minimize its disadvantages, that is, the utilization of quantitative analysis.
3. Methods
3.1 Data
Our corpus is a self-constructed one with speech and debate transcripts of Hillary Clinton and Donald Trump,
which are downloaded from online sources. The specific information is listed in the Appendix.
In all, 20 speech transcripts are collected—10 of them are Clinton’s campaign speeches and another 10 are
Trump’s. Additionally, three transcripts for the TV debates between Clinton and Trump are also included. The
distribution of the corpus is shown in Table 1.
Table 1. The distribution of the transcripts
Clinton Trump
Presidential debates 3 3
Campaign speeches 10 10
Total 13 13
3.2 Data Processing and Analysis
Both quantitative and qualitative methods were applied in the research. For quantitative measures, two tools
were used to process the data collected. One was QUITA (Quantitative Index Text Analyzer) and the other was
AntConc 3.4.4w (Windows) 2014. QUITA is mainly used for calculating quantitative indexes that are related to
frequency and distribution (Liu, 2017, p. 133), and AntConc is a corpus analysis toolkit for concordance and text
analysis. Before using the two tools, the debating contents of Clinton and Trump were separated into two
different files and the contents of irrelevant speakers were excluded. By employing the software QUITA,
vocabulary richness can be calculated and this index is represented by the value of R
1
. By applying AntConc,
keyword lists for the 20 speeches of the two 2016 presidential candidates (10 for each) and their debates (3 files
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for each) were generated respectively. First, we imported a target corpus, Trump’s speech transcripts for example,
into the software. Second, we used the “Keyword List” in the “Tool Preferences” to generate the keyword lists of
the corpus. We used the “BNC-Wordlist”, “BNC-Written Wordlist” and “BNC-Spoken Wordlist” as our
reference corpus. Last, a table of the keyword list was generated. The same steps were taken to process the other
three target corpora, namely, Hillary’s speech transcripts, Trump’s debate transcripts, and Hillary’s debate
transcripts. For qualitative methods, the theory of CDA is employed. According to van Dijk (2015, p. 478), CDA
has particularly concentrated on political discourses in that it takes a special interest “in the critical study of
power abuse”. Political discourse can refer to a variety of oral or written discourses that are different in kinds,
including “a speech, debate, political interview, policy document” (Wilson, 2015, p. 775), etc. As speech and
debate transcripts, the data collected for the research are one type of the political discourses that CDA deals with.
By analyzing the keywords, the collocations, and their links to other factors in society, the research intends to
figure out the hidden messages in the speeches and debates of Donald Trump and Hillary Clinton. With the
combination of quantitative and qualitative methods, both a broad picture and the details can be illustrated in the
research.
4. Results and Discussion
4.1 A General View
Through the analysis by QUITA, the result can be seen in Table 2.
Table 2. Quantitative results for the texts
Text Types Tokens TTR H-point R
1
Clinton’s speeches 3983 38735 0.102827 80.5 0.549713
Trump’s speeches 3908 38919 0.100414 76.5 0.561811
Clinton’s debates 2285 18403 0.124165 54.6667 0.566876
Trump’s debates 2001 23190 0.086287 65 0.531156
4.1.1 TTR
TTR is the type-token ratio. The distinction between a “type” and its “tokens” is “an ontological one between a
general sort of thing and its particular concrete instances (to put it in an intuitive and preliminary way)” (Wetzel,
2018). Every text has its own TTR. From the values of TTR of these texts here, it displays that Trump’s TTR is
lower than Clinton’s both in campaign speeches and debates. As a result, a general conclusion can be reached
that Trump’s language is not as rich as Clinton’s.
4.1.2 H-Point
The h-point originated from the number “h index”, which was proposed by Hirsch (2005). It is “defined as the
number h of papers with citation counts higher or equal to h” (Popescu, 2007, p 555). Hirsch first used this index
“as a particularly simple and useful way to characterize the scientific output of a researcher” (2005, p. 16569).
He argued that “h was preferable to other single-number criteria commonly used to evaluate scientific output of a
researcher” (Hirsch, 2005, p. 16569). Under this circumstance, Popescu and his study brought “empirical
arguments for the transfer of the h-index concept from scientometrics to linguistics” (2007, p. 556). He switched
“the problem from paper citation ranking to word frequency ranking” (Popescu, 2007, p. 556). Accordingly, the
“h-index for words” represents the “word distribution width” and is “defined as the number h of unique words
with counts higher or equal to h” (Popescu, 2007, p. 557) instead of citations. In this study, the h-point in the
above table is a threshold determined by the rank-frequency distribution of the texts.
When r = f(r), the value of r is the h-point (r represents the rank, and f(r) represents the frequency of the words
in that rank). The frequency of the words which are before the h-point is higher than their ranks. On the contrary,
the frequency of the words which are after the h-point is lower than their ranks. If the h-point cannot be found
directly from the rank-frequency distribution table, it will be calculated with the following formula (Liu, 2017):
h =
(
)
(
)
(
)
(
)
(1)
(assuming the h-point is between r
1
and r
2
, and r
2
＞r
1
)
Accordingly, in this study, the rank-frequency table of Clinton’s speeches is shown in Table 3.
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Table 3. Part of the frequency list of Clinton’s speeches
Rank Word Frequency %
… … … …
79 believe 82 0.212
80 how 81 0.209
81 like 80 0.207
82 Americans 80 0.207
83 let 79 0.204
84 jobs 78 0.201
… … … …
Therefore, the h-point of Clinton’s speeches should be calculated as follows:
h =
∗∗
= 80.5
The words before the h-point are more likely to be function words which may have a higher frequency, and the
words after the h-point are more likely to be content words (Liu, 2017). As a result, the value of the h-point will
reflect the richness of the text. The richness of texts is also shown in Table 2 in the form of R
1
.
4.1.3 R
1
R
1
means the vocabulary richness of the texts which can particularly reflect one’s language style. The value of R
1
is related to the h-point. The formula is shown as follows:
R
1
= 1- F(h)
F(h) = F(h) -
So, R
1
= 1- [F(h) -
] (2)
Through the formula above, for instance, R
1
of Trump’s debates can be calculated as follows:
R
1
= 1- [
∑
(
ℎ
)
-
∗
]≈0.531
By that analogy, the rest of the values of R
1
can be calculated. By comparing the values of R
1
in texts of these
two candidates in Table 2, it is surprising to see that R
1
of Trump is higher than that of Clinton in campaign
speeches. In debates, however, R
1
of Trump is lower than that of Clinton. Since one’s impromptu speech, to
some extent, can reflect one’s mind better for the lack of full preparation, this study prefers to use the value of R
1
in debates to illustrate their vocabulary richness.
From the analysis all above, it can be concluded that Trump’s vocabulary richness is lower than Clinton’s from a
general perspective.
4.2 Pronouns in the Speeches
As far as pronouns are concerned, Clinton used the pronoun you more often than Trump in her election speeches.
The word you appeared altogether 528 times in her speeches and ranked 13 in the keyword list. According to
Pennebaker, “pronouns reflect where people are paying attention” (2011, p. 100). Therefore, speakers who use
you “are looking at or thinking about their audience” (2011, p. 100), which means that they want to make a
connection with the audience. Thus, the pronoun you is used to appeal to the audience. In the case of election
speeches, the frequent use of you makes the public feel that their interests are being considered by a potential
country leader who has the power to make a difference to their life. In Clinton’s speeches, she was likely to
create unfair pictures of ordinary people living a hard life against the rich making huge profits to indicate that
America needed change. The following is an example of you being used in the way that it can connect and
appeal to the audience—the voters.
Example 1
Yo u worked extra shifts, took second jobs, postponed home repairs… you figured out how to make it work.
……
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Yo u see corporations making record profits, with CEOs making record pay, but your paychecks have barely
budged.
While many of you are working multiple jobs to make ends meet, you see the top 25 hedge fund managers
making more than all of America’s kindergarten teachers combined. And, often paying a lower tax rate.
(Hillary Clinton’s Campaign Launch Speech, Note 1)
By letting the audience imagine the huge gap between ordinary hardworking citizens and the rich who possess a
large fortune, Clinton underlined the unfair tax system in the country. Naturally, she offered herself as the right
person to do the job—to change America and to make it a better place and a fairer country for more ordinary
people to live in. In this way, the audience might be infected by her, agree with her, and in the end vote for her,
which exactly suited Clinton’s purpose of her speeches.
Another interpretation of you is that it implies the speaker’s relatively higher social status. As is stated by James
W. Pennebaker, “the pronouns I, we, and you are by far the words that consistently reveal status” and that “the
person who uses more second-person pronouns like you and your is likely to be the person higher in status”
(2011, p. 100). As a democrat, Hillary Clinton represents the elite in the United States, which explains her use of
you in a different way. Apart from applying you to shorten the distance between her and the audience as
mentioned above, she also applied you in a way that the pronoun showed her superiority and relatively higher
social status—no matter she used it in this way consciously or unconsciously. Here is an example as such.
Example 2
And you’re lucky I didn’t try singing that, too, I’ll tell you!
……
And I want you to remember this, because to me, this is absolutely the most-compelling argument why we
should do this.
(Hillary Clinton’s Campaign Launch Speech, Note 1)
In the example above, the pronoun you was used as a symbol of giving orders. It indicated that Hillary Clinton
seemed to “order” the audience to do what she wanted them to. Besides, throughout the speeches, she kept
reminding the audience that she was once the First Lady, a Senator and the Secretary of State. Altogether, “First
Lady”, “Senator” and “Sectary of State” which refer to Clinton herself have a word frequency of 3, 10 and 12
respectively in the ten speeches selected. By mentioning her time in office, indeed, she wanted to make sure that
the audience knew about her hard work and her contributions to the country. Nevertheless, it also suggested that
she had more power than the audience. With dissatisfaction with the current state bureaucracy among
working-class American voters (Lamont, Park, & Ayala-Hurtado, 2017), anti-elitism became increasingly
popular. As a result, being a member among the elite was no longer an advantage for Clinton. Tired of the
unchanged American society under the control of the elite, ordinary people and working-class citizens in
America asked for a change—a change for a better future for themselves instead of the elite. The elite had
enjoyed too much superiority and priority. It was time that the ordinary American citizens’ voice be heard. As a
consequence, Donald Trump, who displayed himself nothing like a traditional politician from the elite group,
stimulated the passionate participation of the silent majority in the election in the way of defying the
Establishment in American politics (Parmar, 2017). By catering for the sentiment of the ordinary voters, Trump
managed to win the support, the will, and eventually, the votes of a large number of working-class American
people. As is shown above, two different ways of applying you in the election speeches led to two opposite
results. One helped Clinton draw the audience to her side, making them believe that she would run the country
with their interests in mind. The other, however, widened the distance between Clinton and her audience, doing
no good to her campaign, which instead contributed to the popularity of Trump to some extent.
In addition to their difference in the use of the pronoun you, a similarity between the two candidates can be
found in terms of the pronoun we. They both used we on a frequent basis in their speeches. The word we both
ranked the second in the keyword lists of Clinton’s and Trump’s speeches with a word frequency of 750 and 722
respectively. As in the case of the pronoun you, the frequent use of the word we indicates a higher status of the
speaker as well (Kacewicz, Pennebaker, Davis, Jeon, & Graesser, 2014). As politicians, Clinton and Trump have
more resources and power than the ordinary people in the United States. Therefore, it can be said that they are in
a higher position in the social hierarchy. Nevertheless, the phenomenon of a higher frequency in the use of the
pronoun we reflects “the fact that high-status individuals are more collectively oriented or other-oriented”
(Kacewicz et al., 2014, p. 137). It means that their attention is more focused on others, which makes sense in that
politicians like Clinton and Trump needed to rely on the people of the country voting for them in the election.
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Therefore, it is typical of politicians to be inclined to talk about protecting the interests of as many groups of
people as possible in their speeches.
The pronoun we actually refers to at least five different meanings: “the you-and-I we”, “the
my-friends-and-not-you we”, “the we-as-you we”, “the we-as-I we” and “the every-like-minded-person-on-earth
we” (Note 2)
(Pennebaker, 2011, p. 101). Among the five meanings, politicians tend to use the last one, which “is
the vaguest of all” (Pennebaker, 2011, p. 101). When looking at the left side of the word we, it can be seen that
several words—“America/American(s)”, “country/countries”, “future”, “job(s)”, “people” and
“together”—appeared frequently (word frequency ≥ 3) both in the speeches of Clinton and Trump (See Table 4).
Table 4. Word frequency for collocations of we
Clinton’s speeches Trump’s speeches
Collocations of we Word frequency (≥3)
America/American(s) 9 5
country/countries 5 9
future 6 6
job(s) 4 6
people 3 6
together 9 9
The above figures show that both Clinton and Trump attempted to narrow the distance between the audience and
them by addressing speeches that were about creating a better “future” for the “country” and for the “American”
“people”. Since employment is the foundation of people’s livelihood, Clinton and Trump also laid much
emphasis on “jobs” in their speeches. For a special purpose of appealing to the audience and to raise their
confidence about the future of the country, the two politicians underlined the importance of all the people doing
their part “together” to make America great again. In order to realize this goal, the first step, naturally, was to
vote for them. They created beautiful dreams with sweet fruit in their speeches, making promises to meet the
needs and to protect the interests of the people. In this way, the high spirits in their speeches became infectious,
persuading the audience to vote for them. Based on this, the purpose of the election campaign could be achieved.
In all, by taking advantage of the pronoun we, both Clinton and Trump attempted to draw the audience—the
potential voters—to their own side so that they could earn more votes in the election.
4.3 Debate Strategies
4.3.1 Interrupting for Power
Language is functional, and accordingly, people will use it to achieve both personal and political ends. To some
extent, language is always related to political activities. Partington (2002) argued that language is not merely a
tool for politicians to achieve some goals, but it can go further that politics is language.
The issue of impoliteness has drawn much attention in previous studies of discourse in political debates.
Jaworski and Galasinski (2000) found that a debate which aimed at power would contribute to a positive
self-presentation and an inevitable negative depiction of the other. As a result, there must be a relationship
between impoliteness and power. In the political debates selected for the research, impoliteness did exist in the
form of frequent interruptions.
Interruption happens frequently in daily life. It can be defined as an action that somebody breaks others’ turn to
speak in order to take over the conversation. West and Zimmerman also defined it as a deep “intrusion into the
internal structure of a speaker’s utterance” (1977, p. 523). Previous studies have indicated that language can be
manipulated to demonstrate power. In this study, the competitive relationship between the two presidential
candidates (at that time) left them with no choice but to manipulate their language to attack each other for the
aim of supporting their own opinions and showing their superiority in the presidential debates.
By using the software Antconc, the statistics about the interrupting words can be seen in Table 5 below.
Table 5. Frequency of “Excuse me”
Clinton Trump
Frequency of the interrupting phrase “Excuse me” 0 14
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As is seen, “Excuse me” occurred 14 times in Trump’s debates, which means an apparent interruption in the
conversation during the debates. Nevertheless, Clinton never used this phrase in their debates, which was a
significant difference from Trump. In the final debate, for instance, the host reminded Trump many times that his
time was up, and that he should stop talking. Nonetheless, it made no difference.
Example 3
WALLACE: Sir, your two minutes are up.
WALLACE: Sir… (interrupted by Trump)
WALLACE: Time, Mr. Trump.
WALLACE: Wait, but…
WALLACE: Mr. Trump… (more than one time)
WALLACE: Well, let me – wait, wait, sir, let me…
WALLACE: Sir, if I may finish my question… Time.
WALLACE: Well, no, sir, because we’re running out of time…
Sacks, Schegloff, and Jefferson argued that “the organization of taking turns to speak is fundamental to
conversation” (1974, p. 696). For a host, a good way to guarantee “the smooth flow of conversation” (Nor, 2012,
p. 130) in a show is to control the discourse by appropriately using discourse markers for speaking turns. While
it should be noted that Wallace used many of these markers to remind Trump of the timing in the debates,
unfortunately, it did not work for Trump. In contrast, there was barely any turn-taking marker used by Wallace
for Clinton. Some previous experimental studies have pinpointed that “the occurrence of interruptions is
clustered in a few conversations for the same-sex pairs, while almost uniformly distributed across cross-sex pairs”
(Zimmerman & West, 1996, p. 225). In their experiment, a class of female speakers’ rights to speak seemed to be
“casually infringed upon by males” (Zimmerman & West, 1996, p. 225). And thus, it was concluded that the
distribution of turns to speak in conversation might reflect the differences between males and females in the
economic system, which indicated the existence of male-dominance in society (Zimmerman & West, 1996). This
kind of male-dominance is also demonstrated through males interrupting females in conversation to gain control
under the underlying male-dominance mind. As is seen, Trump’s frequent interruptions were exactly in accord
with the above descriptions.
Besides continuing to speak directly regardless of the host’s reminding, Trump also “politely” interrupted.
Example 4
TRUMP: Excuse me. My turn. You were very much involved in every aspect of this country. Very much.
And you do have experience. I say the one thing you have over me is experience, but it’s bad experience,
because what you’ve done has turned out badly.
TRUMP: Excuse me. She just went about 25 seconds over her time. Could I just respond to this, please?
From the above example, it can be seen that there was a different time standard for Trump. For one thing, it
seemed to be fatal for him to bear others’ taking up his time. For another thing, he freely prolonged his own
speeches and did not feel guilty for his interruption.
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34
4.3.2 Strategy of Repetition
Table 6. Keyword list of the debates
Clinton Trump
Rank Freq Keyness Word Rank Freq Keyness Word
1 85 789.578 donald 1 469 930.456 we
2 568 760.386 i 2 679 854.439 i
3 368 723.46 we 3 540 735.249 you
4 139 334.543 our 4 41 718.582 obama
5 497 310.92 that 5 213 688.132 re
6 24 257.79 trump 6 52 634.024 hillary
7 106 255.134 think 7 177 604.213 going
8 93 226.749 ve 8 43 518.405 isis
9 77 200.254 want 9 118 420.746 country
10 67 197.671 country 10 366 403.352 have
11 11 191.066 obama 11 26 381.624 mosul
12 53 189.845 president 12 256 345.619 t
13 10 183.844 putin 13 47 343.593 clinton
14 100 179.527 because 14 154 336.147 our
15 76 175.455 going 15 316 334.966 they
16 107 165.138 people 16 104 283.015 look
17 15 157.65 isis 17 142 282.967 because
18 37 153.314 jobs 18 153 279.211 very
19 48 141.346 lot 19 268 271.789 she
20 210 140.545 have 20 15 268.815 putin
21 111 136.655 do 21 495 237.309 it
22 131 134.698 what 22 12 215.052 obamacare
23 93 127.868 well 23 137 214.774 people
24 117 120.479 about 24 34 209.616 percent
25 9 110.434 undocumented 25 395 193.148 s
26 221 106.219 you 26 29 186.143 tremendous
27 73 105.055 know 27 17 177.928 trillion
28 28 96.098 america 28 31 176.555 disaster
29 62 92.988 re 29 89 174.875 ve
30 15 91.87 wealthy 30 34 169.862 russia
As is seen in Table 6 above, generally speaking, the frequency of each keyword of Clinton was lower than that of
Trump. It means that Trump was more likely to repeat his words for the purpose of emphasis or a lack of
vocabulary.
In addition to the keywords of the specific topic that the host gave to them, their differences on wording can also
be seen. For instance, the keyness of “tremendous” in Trump’s debates is 186.143, and he used the word 29 times
to express the meaning of greatness. On the contrary, Clinton was more likely to use different words to express
the same meaning. Although Clinton’s strategy made her look more “well-educated”, Trump’s strategy of
repetition actually made his speech more impressive. Though Trump might not use the strategy on purpose, it
still exerted a powerful effect on highlighting messages he wanted to convey to the audience.
5. Conclusion
Combining quantitative analysis with the qualitative method of CDA, this study aims to compare language
features of the two 2016 US election candidates—Donald Trump and Hillary Clinton—from a general
perspective as well as in detail. Statistics and figures illustrate the overall results while details in their transcripts
of speeches and debates demonstrate their specific differences in the choice of words and strategies.
From a general view, it can be concluded that Clinton’s vocabulary is richer than Trump’s in that Clinton’s value
of R
1
in debates is higher than that of Trump. In the meantime, under a detailed observation, this study offers
some insights into these two candidates’ language styles. In campaign speeches, Clinton used the pronoun you
much more often than Trump. On one hand, the use of you narrowed the distance between Clinton and her
audience. On the other hand, it also implied Clinton’s higher social status and her attempts of widening the gap
between the audience and her. Donald Trump, however, by demonstrating himself nothing like a traditional
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35
politician, won himself the support of a large number of voters. Besides the difference, Clinton and Trump both
used the pronoun we on a regular basis, showing to the audience that they had the people’s interests in mind.
Therefore, the distance between the speakers and the audience was shortened, helping Clinton and Trump in
getting more votes from the audience. In the debates, Trump’s repetitive use of the same words and his frequent
interruptions showed his desire for power under the influence of a male-dominance mind. Nevertheless, his
strategy of repetition actually made his speech in the debates more impressive.
At the same time, there are some limitations about this study. First, the corpus of this study is not large enough to
generate more convincing results. Secondly, the results of quantitative analysis, to some extent, may not be well
explained. In addition, more statistical software could have been used to achieve a more thorough and reliable
result. Beyond that, some factors, such as ghostwriters for speech writing and the ability of improvisation, have
not been taken into account in the study.
Acknowledgments
This study is supported by the National Natural Science Foundation of China (Project Nos. 71872165;
71402163), the Social Science and Humanities Research Foundation of Chinese Ministry of Education (Project
No. 18YJC630241), and the Research Foundation of China’s Language Commission (Project No. YB135–95).
All views expressed are those of the authors and not of the sponsoring organizations.
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Notes
Note 1. The examples are extracted from Hillary Clinton’s Campaign Launch Speech on June 13, 2015.
Note 2. A more detailed explanation for the five meanings of the pronoun we can be seen in Chapter 7 of James
W. Pennebaker’s book The Secret Life of Pronouns.
Appendix A
List of the Sampled Speeches and Debates
Table A1. Clinton’s campaign speeches and debates
Rank Words Date Theme URL
Campaign speeches
1 4747 13 June, 2015 Hillary Clinton’s
campaign launch speech
http://time.com/3920332/transcript-full-text-hillary-clinton-campa
ign-launch/
2 1702 27 February,
2016
Hillary Clinton’s South
Carolina speech
https://www.dailykos.com/stories/2016/2/27/1492599/%13Hillary
%13Clinton%13s%13South%13Carolina%13speech%13Transcri
pt
3 1314 1 March, 2016 Hillary Clinton’s Super
Tuesday victory speech
http://time.com/4244178/super-tuesday-hillary-clinton-victory-sp
eech-transcript-full-text/
4 4250 2 June, 2016 Hillary Clinton’s speech
on Donald Trump and
national security
http://time.com/4355797/hillary-clinton-donald-trump-foreign-pol
icy-speech-transcript/
5 5596 28 July, 2016 Hillary Clinton’s
acceptance speech
https://www.bloomberg.com/news/features/2016-07-29/hillary-cli
nton-s-acceptance-speech-annotated
6 5895 11 August,
2016
Hillary Clinton’s
economic speech
https://www.newsweek.com/hillary-clinton-full-transcript-econo
mic-speech-48960257
7 2937 25 August,
2016
Hillary Clinton’s speech
on the alt-right
https://www.huffingtonpost.com/entry/hillary-clinton-speech-text
_us_57bf4575e4b02673444f2307
8 6150 6 September,
2016
Hillary Clinton’s stump
speech
https://www.npr.org/2016/09/15/493924325/inside-hillary-clinton
s-stump-speech-annotated
9 4834 10 October,
2016
Hillary Clinton’s speech
at Ohio State
https://www.dispatch.com/content/stories/local/2016/10/11/hillar
y-clintons-speech-at-ohio-state.html
10 1098 9 November,
2016
Hillary Clinton’s
concession speech
https://www.telegraph.co.uk/news/2016/11/09/hillary-clintons-sp
eech-in-full/
Debates
1 4782 27 September,
2016
First debate https://www.boston.com/news/politics/2016/09/28/read-the-full-tr
anscript-of-the-presidential-debate-here
2 6347 10 October,
2016
Second debate https://www.nytimes.com/2016/10/10/us/politics/transcript-secon
d-debate.html
3 7116 19 October,
2016
Final debate https://www.washingtonpost.com/news/the-fix/wp/2016/10/19/th
e-final-trump-clinton-debate-transcript-annotated/?noredirect=on
&utm_term=.f94e1b27714c
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39
Table A2. Trump’s campaign speeches and debates
Rank Words Date Theme URL
Campaign speeches
1 2342 21 March, 2016 Full text of Donald Trump’s
speech to AIPAC
https://www.timesofisrael.com/donald-trumps-full-speech
-to-aipac/
2 3496 27 April, 2016 Donald Trump’s foreign
policy speech
http://www.thefiscaltimes.com/2016/04/28/Transcript-Do
nald-Trump-s-Foreign-Policy-Speech-April-27-2016
3 6339 16 June, 2016 Donald Trump’s presidential
announcement speech
http://time.com/3923128/donald%13trump%13announce
ment%13speech/
4 5143 21 July, 2016 Full transcript of Donald
Trump’s acceptance speech
at the RNC
https://www.vox.com/2016/7/21/12253426/donald-trump-
acceptance-speech-transcript-republican-nomination-trans
cript
5 3549 8 August, 2016 Donald Trump’s economic
speech
https://www.washingtonpost.com/news/the-fix/wp/2016/0
8/08/donald-trumps-economic-speech-annotated/
6 2886 16 August,
2016
READ: Full transcript of
Donald Trump law &
order speech
https://heavy.com/news/2016/08/read-full-transcript-donal
d-trump-transcript-law-and-order-speech-west-bend-wisc
onsin
7 3531 18 August,
2016
Donald Trump’s best speech
of the 2016 campaign,
annotated
https://www.washingtonpost.com/news/the-fix/wp/2016/0
8/19/donald-trumps-best-speech-of-the-2016-campaign-an
notated/?utm_term=.3902f4958668
8 6849 31 August,
2016
Transcript: Donald Trump’s
full immigration speech,
annotated
https://www.latimes.com/politics/la-na-pol-donald-trump-
immigration-speech-transcript-20160831-snap-htmlstory.
html
9 2363 7 September,
2016
Donald Trump’s speech on
national security in
Philadelphia
https://thehill.com/blogs/pundits-blog/campaign/294817-t
ranscript-of-donald-trumps-speech-on-national-security-in
10 1616 9 November,
2016
Donald Trump’s victory
speech
https://www.cnn.com/2016/11/09/politics/donald-trump-v
ictory-speech/index.html
Debates
1 8504 27 September,
2016
First debate https://www.boston.com/news/politics/2016/09/28/read-th
e-full-transcript-of-the-presidential-debate-here
2 7315 10 October,
2016
Second debate https://www.nytimes.com/2016/10/10/us/politics/transcrip
t-second-debate.html
3 6499 19 October,
2016
Final debate https://www.washingtonpost.com/news/the-fix/wp/2016/1
0/19/the-final-trump-clinton-debate-transcript-annotated/?
noredirect=on&utm_term=.f94e1b27714c
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