Out-grouping and ambient affiliation in Donald Trump’s tweets about Iran: Exploring the role of negative evaluation in enacting solidarity
Abstract
This paper explores communing affiliation and out-grouping in a corpus of Trump’s tweets about Iran. Communing is
a form of ‘ambient affiliation’ (Zappavigna 2011Zappavigna, Michele 2011 “Ambient
Affiliation: A Linguistic Perspective on Twitter.” New Media &
Society 13, no. 5: 788–806. ) which offers a way of understanding
how Trump attempts to build alignments with his audience without necessarily directly engaging with them, since he tends
to ignore replies to his tweets. The paper focuses on three affiliation strategies: convoking (mustering community),
promoting (garnering attention), and finessing (dialogistic positioning). It draws on Martin and White’s (2005)Martin, J. R., and P. R. R. White 2005 The
Language of Evaluation: Appraisal in
English. Basingstoke: Palgrave/Macmillan.
Appraisal framework to consider how these affiliation strategies are used to
foster communing around ideation-attitude couplings, typically couplings associating Iran with negative judgement or
appreciation. Promoting affiliation was found to be the most prominent affiliation strategy used by Trump to
garner attention through his rhetorical tendency toward hyperbole.
Keywords:
Publication history
Table of contents
1.Introduction
This paper explores how US President Donald Trump uses negative evaluative language about Iran as a strategy for creating alignments
with his ambient audience on Twitter. It focuses on the kind of ‘ambient affiliation’ (Zappavigna
2011Zappavigna, Michele 2011 “Ambient
Affiliation: A Linguistic Perspective on Twitter.” New Media &
Society 13, no. 5: 788–806. ) he adopts in his personal Twitter account, @realDonaldTrump, to outgroup Iran and its government as a way of
communing with his supporters. Iran has a unique geopolitical status in the Middle East region and is surrounded by a number of mainly
Arab countries which are US allies (Hokayem 2014Hokayem, Emile 2014 “Iran,
the Gulf States and the Syrian Civil
War.” Survival 56 (6): 59–86.
). It is one of the only countries in the
area to officially oppose US policies regarding the Middle East, resulting in ongoing tension between the two nations. Following the
nuclear negotiation in 2015, the two countries came close to a mutual dialogue and a possible truce in meetings between the US
Secretary of State and Iran’s Foreign Minister. However, even before his presidency, Trump expressed his disdain for these nuclear
talks in tweets characterising it as a “bad deal”. Once elected president, he withdrew from the Iran nuclear agreement and has since
exerted pressure on Iran, often publicly via Twitter, to comply with US demands (Kroenig
2018Kroenig, Matthew 2018 “The
Return to the Pressure Track: The Trump Administration and the Iran Nuclear Deal.” Diplomacy
&
Statecraft 29 (1): 94–104.
). The “impulsivity” (Ott 2017Ott, Brian
L. 2017 “The Age of Twitter: Donald J.
Trump and the Politics of Debasement.” Critical Studies in Media
Communication 34 (1): 59–68.
, 61) of Trump’s combative and inflammatory
Twitter discourse has been referred to as “gut-feeling” tweeting (Enli 2017Enli, Gunn 2017 “Twitter
as Arena for the Authentic Outsider: Exploring the Social Media Campaigns of Trump and Clinton in the 2016 US Presidential
Election.” European Journal of
Communication 32 (1): 50–61.
, 55) about what
are sensitive topics for the US and its allies.
While there have been many studies of politicians’ use of Twitter across a range of countries from Switzerland to South
Korea (c. f. Rauchfleisch and Metag 2016Rauchfleisch, Adrian, and Julia Metag 2016 “The
Special Case of Switzerland: Swiss Politicians on Twitter.” New Media &
Society 18 (10): 2413–2431. ; Grant et al.
2010Grant, Will
J., Brenda Moon, and Janie
Busby Grant 2010 “Digital
Dialogue? Australian Politicians’ Use of the Social Network Tool Twitter.” Australian Journal
of Political
Science 45 (4): 579–604.
; Frame and Brachotte 2015Frame, Alex, and Gilles Brachotte 2015 “Le
tweet stratégique: Use of Twitter as a PR Tool by French Politicians.” Public Relations
Review 41 (2): 278–287.
; Yoon and
Park 2014Yoon, Ho
Young, and Han
Woo Park 2014 “Strategies
Affecting Twitter-Based Networking Pattern of South Korean Politicians: Social Network Analysis and Exponential Random Graph
Model.” Quality &
Quantity 48 (1): 409–423.
; Coesemans and De Cock 2017Coesemans, Roel, and Barbara
De Cock 2017 “Self-reference
by Politicians on Twitter: Strategies to Adapt to 140 Characters.” Journal of
Pragmatics 116: 37–50.
), Trump has displayed a consistently
unconventional rhetorical style that diverges from the approach of many other politicians (Sclafani 2017Sclafani, Jennifer 2017 Talking
Donald Trump: A Sociolinguistic Study of Style, Metadiscourse, and Political
Identity. Lodnon: Routledge.
). His “amateurish yet authentic” (Enli 2017Enli, Gunn 2017 “Twitter
as Arena for the Authentic Outsider: Exploring the Social Media Campaigns of Trump and Clinton in the 2016 US Presidential
Election.” European Journal of
Communication 32 (1): 50–61.
, 54) tone has
heightened scholarly interest in his tweets (Ott 2017Ott, Brian
L. 2017 “The Age of Twitter: Donald J.
Trump and the Politics of Debasement.” Critical Studies in Media
Communication 34 (1): 59–68.
; Ross and Rivers 2018Ross, Andrew
S., and Damian
J. Rivers 2018 “Discursive
Deflection: Accusation of “Fake News” and the Spread of Mis-and Disinformation in the Tweets of President
Trump.” Social Media+
Society 4 (2):
; Ross and Caldwell 2020Ross, Andrew
S., and David Caldwell 2020 “ ‘Going
Negative’: An APPRAISAL Analysis of the Rhetoric of Donald Trump on Twitter.” Language &
Communication 70: 13–27.
; Pain and Chen 2019Pain, Paromita, and Gina
Masullo Chen 2019 “The
President is in: Public Opinion and the Presidential Use of Twitter.” Social Media+
Society 5 (2):
; Krugman 2016Krugman, Paul 2016 “Donald
Trump’s “Big Liar” Technique.” The New York Times.
; Kreis 2017Kreis, Ramona 2017 “The
“Tweet Politics” of President Trump.” Journal of Language and
Politics 16 (4): 607–618.
; Hoffman 2018Hoffmann, Christian
R. 2018 “Crooked Hillary and Dumb
Trump.” Internet
Pragmatics 1 (1): 55–87.
). This style has continued from his
election campaign into his presidency and he has favoured use of his personal Twitter account, @realDonaldTrump, rather than the
formal @POTUS account used by other presidents. Trump tweets very frequently compared to past presidents (e.g. 37 and 38 times on 3
and 4 March 2020 respectively), leading him to be labelled the “Tweeter in Chief” by media (see for example Anderson 2017Anderson, Bryan 2017 “Tweeter-In-Chief:
A Content Analysis of President Trump’s Tweeting Habits.” Elon Journal of Undergraduate
Research in
Communications 8 (2): 36–47.
).
1.1Trump’s negativity on Twitter
Scholarly studies in media and communication have shown that there is a correlation between heavy Twitter use and
negatively-charged emotional language aimed at garnering the attention of online audiences (Stieglitz and Dang-Yuan 2013Stieglitz, Stefan, and Linh Dang-Xuan 2013 “Emotions
and Information Diffusion in Social Media – Sentiment of Microblogs and Sharing
Behavior.” Journal of Management Information
Systems 29 (4): 217–248. ; Ott 2017Ott, Brian
L. 2017 “The Age of Twitter: Donald J.
Trump and the Politics of Debasement.” Critical Studies in Media
Communication 34 (1): 59–68.
). ‘Negativity’ is regularly observed
in political discourse where it tends to focus on the alleged faults and weaknesses of opposition candidates (Dolezal et al. 2017Dolezal, Martin, Laurenz Ennser-Jedenastik, and Wolfgang
C. Müller 2017 “Who
Will Attack the Competitors? How Political Parties Resolve Strategic and Collective Action Dilemmas in Negative
Campaigning.” Party
Politics 23 (6) 666–679.
), or on negative emotions and opinions toward people and events
(Ott 2017Ott, Brian
L. 2017 “The Age of Twitter: Donald J.
Trump and the Politics of Debasement.” Critical Studies in Media
Communication 34 (1): 59–68.
). This study explores the linguistic realisation of such negativity by
considering how it is realised in negative evaluative language using the Appraisal framework, a social semiotic model of
evaluation (Martin and White 2005Martin, J. R., and P. R. R. White 2005 The
Language of Evaluation: Appraisal in
English. Basingstoke: Palgrave/Macmillan.
; Hunston 2000Hunston, Susan 2000 “Evaluation
and the Planes of Discourse: Status and Value in Persuasive
Texts.” In Evaluation in Text: Authorial Stance and the Construction
of Discourse, edited by Hunston, Susan and Geoff Thomson: 176–207. London: Oxford
University Press.
). Twitter seems to privilege negative
communication which can breed “dark, degrading, de-humanizing discourse” (Ott 2017Ott, Brian
L. 2017 “The Age of Twitter: Donald J.
Trump and the Politics of Debasement.” Critical Studies in Media
Communication 34 (1): 59–68.
,
62). There have been several studies focusing on the negativity of Trump’s tweeting practice (c.f., Ross and Caldwell 2020Ross, Andrew
S., and David Caldwell 2020 “ ‘Going
Negative’: An APPRAISAL Analysis of the Rhetoric of Donald Trump on Twitter.” Language &
Communication 70: 13–27.
; Ceron and d’Adda 2016Ceron, Andrea, and Giovanna d’Adda 2016 “E-campaigning
on Twitter: The Effectiveness of Distributive Promises and Negative Campaign in the 2013 Italian
Election.” New Media &
Society 18 (9): 1935–1955.
). Lee & Quealy (2016)Lee, Jasmine
C., and Kevin Quealy 2016 “The
282 People, Places and Things Donald Trump has Insulted on Twitter: A Complete List.” The New
York Times 25.
have noted the unprecedented degree of personal attacks and
insults that characterised Trump’s election campaign. After analysing 66,463 tweets from the primary season leading up to the 2016
election, Conway-Silva et al. (2018)Conway-Silva, Bethany
A., Christine
R. Filer, Kate Kenski, and Eric Tsetsi 2018 “Reassessing
Twitter’s Agenda-Building Power: An Analysis of Intermedia Agenda-Setting Effects During the 2016 Presidential Primary
Season.” Social Science Computer
Review 36 (4): 469–483.
also concluded that Trump produced more lying accusations than any other
candidate. Krugman (2016)Krugman, Paul 2016 “Donald
Trump’s “Big Liar” Technique.” The New York Times.
labelled Trump’s online behaviour as the ‘big liar’
technique, arguing that the accuracy and truthfulness of most of Trump’s tweets have become irrelevant to their discursive power
and influence. Also pervasive in Trump’s discourse is repeated derogatory labelling of mainstream media as “fake news”. This is a
rhetorical strategy aimed at spreading misinformation by delegitimising news outlets (e.g. CNN and the New York Times) while
indicating allegiance to outlets that support Trump’s agenda (e.g. Fox News) (Ross and River
2018Ross, Andrew
S., and Damian
J. Rivers 2018 “Discursive
Deflection: Accusation of “Fake News” and the Spread of Mis-and Disinformation in the Tweets of President
Trump.” Social Media+
Society 4 (2):
).
This paper explores Trump’s negativity on Twitter using the Appraisal framework (Martin and White 2005Martin, J. R., and P. R. R. White 2005 The
Language of Evaluation: Appraisal in
English. Basingstoke: Palgrave/Macmillan. ), to understand how patterns of evaluation are targeted at certain groups and are involved in
creating alignments with the ambient audience. While there has been a limited concentration of work applying Appraisal to Trump’s
tweets, there is less work considering his political discourse from the perspective of affiliation (although see Zappavigna (2018) 2018 Searchable
Talk: Hashtags and Social Media
Metadiscourse. London: Bloomsbury
Publishing.
). Ross and Caldwell (2020Ross, Andrew
S., and David Caldwell 2020 “ ‘Going
Negative’: An APPRAISAL Analysis of the Rhetoric of Donald Trump on Twitter.” Language &
Communication 70: 13–27.
,
14) analysed a corpus of Trump’s tweets around the time of his political campaign and subsequent victory, using Appraisal to reveal
his tendency to “go negative” in attempts to delegitimise his political opponent, Hillary Clinton. Another study drawing on
Appraisal found that Trump made use of negative evaluation and judgement much more frequently than Clinton (Hoffman 2018Hoffmann, Christian
R. 2018 “Crooked Hillary and Dumb
Trump.” Internet
Pragmatics 1 (1): 55–87.
). Other work has noted that Trump tends to communicate informally, directly,
and provocatively, in his attempts to appeal to supporters by constructing an image of a “homeland” threatened by dangerous
“others” (Kreis 2017Kreis, Ramona 2017 “The
“Tweet Politics” of President Trump.” Journal of Language and
Politics 16 (4): 607–618.
). He tends to use personal pronouns such as I,
we, and membership terms such as nation and people to construe an ingroup of
nationalistic Americans. Outsiders are referred to with pronouns such as them and they, for
example in tweets about ‘Muslim bans’. Kreis concluded that this may contribute to the normalisation of
right-wing populist discourses.
The present study will consider the kinds of affiliation strategies adopted by Trump that may contribute to this kind
of in/out grouping as Trump attempts to create a community of shared values that excludes outsiders. It builds on previous work on
social bonding via ‘ambient affiliation’ in social media discourse (Zappavigna 2014 2014 Coffeetweets:
Bonding Around the Bean on Twitter. In The Language of Social
Media, edited by Seargeant, Philip and Caroline Tagg: 139–160. London: Palgrave
Macmillan. ,
2018 2018 Searchable
Talk: Hashtags and Social Media
Metadiscourse. London: Bloomsbury
Publishing.
; Zappavigna and Martin 2018Zappavigna, Michele, and James
R. Martin 2018 “#
Communing Affiliation: Social Tagging as a Resource for Aligning Around Values in Social
Media.” Discourse, Context &
Media 22: 4–12.
) to
demonstrate the ways in which negatively appraising an ‘other’ can be used to foster social alignments that have serious and
negative implications for particular social groups.
1.2Background on Iran-US relations
There is a long history of hostility between the United States and Iran, dating back to 1953 when the United States
and the UK were behind a coup d’état which led to the toppling of the Iranian Prime Minister, Mohammad Mosadegh (Pollack 2004Pollack, Kenneth 2004 The
Persian Puzzle: Deciphering the Twenty-five-Year Conflict Between the United States and
Iran. New York: Random
House.). While the two countries have never been officially at war, they have not
had any diplomatic ties since November 1979 and the American hostage crisis. In the hostage crisis standoff, some Iranian
university students, angry at US support of the dethroning of the Shah of Iran, stormed the US embassy and took 60 US citizens
hostage, with the permission of the Supreme Leader of the time, Ayatollah Khomeini. This led to an international crisis with US
President Carter cutting all diplomatic ties between the two countries and imposing sanctions against Iran (Blakemore, 2020Blakemore, Erin 8 January 2020 “U.S.-Iran
Tensions: From Political Coup to Hostage Crisis to Drone Strikes.” https://www.history.com/news/iran-nuclear-deal-sanctions-facts-hostage-crisis. Accessed 9 January 2020. https://www.history.com/news/iran-nuclear-deal-sanctions-facts-hostage-crisis). The closest step to any official arbitration was the 2015 nuclear negotiations during
which former US Secretary of State, John Kerry, and Iran’s Minister of Foreign Affairs, Mr Javad Zarif met on a few occasions.
Together with leaders of China, France, Russia, the UK, and Germany, they signed a Joint Comprehensive Plan of Action (JCPOA) in
order for Iran to suspend its nuclear activity in exchange for sanction relief from the US and other European countries. However,
in May 2018, Trump unilaterally withdrew from the agreement and vowed harsh penalties for companies trading with Iran. Following
this decision, tensions between the two countries escalated and led to instability in the Middle East region.
The US has always criticised Iran for its financial and military support of militia-based groups, as it considers them a source of volatility and insecurity in the region. The two countries were on the brink of a full-scale war in early 2020 when the Pentagon confirmed the killing of a high status Iranian General, Qasem Suleimani, Commander of Quds Force, in Baghdad airport. Iran fired more than a dozen missiles toward US military bases in Baghdad, in response. A more tempered rhetoric and the possibility of mutual dialogue between the two countries has largely been annihilated, and the two countries continue to blame each other for all instability in the region. Iranian Supreme Leader, Ayatollah Khamenei, has ruled out the possibility of any dialogue between the US and Iran after the killing of General Suleimani. This is indicative of the high level of hostility between the US and Iran at the present time, an extremely dangerous context for the kind of negatively-charged discourse produced by Trump about Iran that we will explore in this paper.
1.3The structure of this article
This paper begins by introducing the Appraisal framework (Martin and White
2005Martin, J. R., and P. R. R. White 2005 The
Language of Evaluation: Appraisal in
English. Basingstoke: Palgrave/Macmillan. ), a framework for analysing the patterning of evaluative language developed within Systemic Functional
Linguistics. It then details the model of ambient affiliation (dialogic and communing affiliation), explaining how this model
arose out of Knight’s (2010)Knight, Naomi 2010 “Laughing
Our Bonds off: Conversational Humor in Relation to Afiliation” PhD
Thesis, University of Sydney, Sydney,
Australia. work on conversational exchanges. Affiliation considers
how social alignments arise out of attitudinal stances targeted at things and experiences, referred to as ideation-attitude
couplings. The paper then details the corpus of Trump’s tweets about Iran and explores the specific affiliation strategies
deployed by Trump to align or de-align from certain stances and voices, and to generate solidarity or dissonance with respect to
certain groups
2.Theoretical framework: Appraisal, and dialogic and communing affiliation
2.1The Appraisal framework
Martin and White’s (2005)Martin, J. R., and P. R. R. White 2005 The
Language of Evaluation: Appraisal in
English. Basingstoke: Palgrave/Macmillan. Appraisal framework offers an account of
evaluative language aimed at describing three systems of meaning, attitude, Engagement, and
Graduation,11.All appraisal terms and sub-types are written in small caps. that are used in this paper to explore the attitudinal positions in
the corpus of Trump’s tweets. attitude is a system for mapping how feelings and opinions are construed in texts and is
comprised of three regions of meaning: affect (expressing emotions e.g. love, hate, fear),
judgement (assessment of human behaviour based on social and ethical norms e.g. competent, stupid)
and appreciation (valuing of things and events e.g. beautiful). Attitudes can also be
graded. The graduation system models the up-scaling and down-scaling of an evaluation in terms of intensity and amount
(force) or prototypicality and preciseness (focus) (Martin and White
2005Martin, J. R., and P. R. R. White 2005 The
Language of Evaluation: Appraisal in
English. Basingstoke: Palgrave/Macmillan.
, 135–160). Another dimension of Appraisal is the engagement
22.The main distinction in engagement is between utterances which engage with dialogic alternatives
(heterogloss) and those which do not (monogloss). monoglossic statements do not acknowledge any
other positions while heteroglossic statements whether entertain other propositions and viewpoints (dialogically
expansive) or challenge/reject alternative viewpoints (dialogically contractive). system,
influenced by Bakhtin’s (1981)Bakhtin, Mikhail
M. 1981 “The Dialogic Imagination: Four
Essays, ed.” Michael Holquist, trans. Caryl Emerson and Michael Holquist (Austin: University of
Texas Press,
1981) 84 (8): 80–2.
notion of “dialogism”, which deals with intersubjective
positioning and whether a proposition includes or excludes other voices and alternative viewpoints (Martin and White 2005Martin, J. R., and P. R. R. White 2005 The
Language of Evaluation: Appraisal in
English. Basingstoke: Palgrave/Macmillan.
, 92–134). If a proposition entertains other value positions and voices, then it is
“dialogically-expansive” but if it actively challenges or constrains the scope of other alternative positions, the proposition is
“dialogically-contractive” (Martin and White 2005Martin, J. R., and P. R. R. White 2005 The
Language of Evaluation: Appraisal in
English. Basingstoke: Palgrave/Macmillan.
, 102). Figure 1 below shows the Appraisal framework with examples from Trump’s tweets about Iran to illustrate the
most delicate choice in each system, with Appraisal features shown in bold font.
Appraisal also accounts for whether or not the evaluative meaning is realised in the text through explicit evaluative
language, that is, whether it is inscribed, or through less direct means, that is, whether it is invoked.
Appraisal distinguishes between three systems of implied evaluation: provoke, flag and afford (Hood 2010Hood, Susan 2010 Appraising
Research: Evaluation in Academic
Writing. London: Springer. ). For example, attitude may be provoked via lexical metaphors or flagged via
graduation resources. Finally, attitude may be ‘afforded’ via ideation; for instance when something can be said to have shared
significance. An example is the Whitehouse which is generally a shared positive symbol in American culture, although which it may have positive or negative connotations
depending on the ideological position of the author/speaker relative to the political party currently in government.
2.2Dialogic affiliation
The Appraisal framework provides insight into attitudinal meaning and how social values are constructed in texts. However, sociality is more complex than simply
expressing feelings or opinions: “[we] don’t after all simply affiliate with feelings; we affiliate with feelings about people,
places and things, and the activities they participate in, however abstract or concrete” (Martin 2008Martin, James
R. 2008 “Innocence: Realisation,
Instantiation and Individuation in a Botswanan Town.” Questioning
linguistics: 27–54., 58). Thus, the key unit of analysis for exploring affiliation is the ideation-attitude coupling; how
feelings or opinions are associated with experience in texts, or in other words, how ideational and interpersonal meanings are
related in discourse to form a value that is available to be negotiated. Knight’s (2010Knight, Naomi 2010 “Laughing
Our Bonds off: Conversational Humor in Relation to Afiliation” PhD
Thesis, University of Sydney, Sydney,
Australia., 2013Knight, Naomi
K. 2013 “Evaluating Experience in Funny
Ways: How Friends Bond Through Conversational Hum.” Text &
Talk 33 (4–5): 553–574.
) work on the role of ideation-attitude coupling in the negotiation
of bonds in conversational exchanges forms the basis of the social semiotic approach to affiliation adopted in this paper. This
work suggested that in dialogic exchanges, interactants tend to rally around, condemn, or defer social bonds
An example of an ideation-attitude coupling is shown below in a tweet where Trump criticises Hillary Clinton via negative judgement (incompetent), creating a disdainful tone as a disqualification strategy:
3 August 2016: Our incompetent Secretary of State, Hillary Clinton , was the one who started to give 400 million dollars in cash to Iran.33.The annotation convention for the analysis of couplings is underlined italics for ideation and bold for appraisal.
[ideation: Secretary of State, Hillary Clinton / attitude: negative judgement ]
This tweet features a coupling of Secretary of State, Hillary Clinton and negative
judgement, which is notated, following the convention adopted by Zappavigna and Martin
(2018)Zappavigna, Michele, and James
R. Martin 2018 “#
Communing Affiliation: Social Tagging as a Resource for Aligning Around Values in Social
Media.” Discourse, Context &
Media 22: 4–12. , with ideation shown in
underlined italics
and attitude in bold.
The square brackets and / are used to suggest the fusion of attitude with ideation, forming a value that is open to potential
response by other tweeters. This coupling offers to the ambient audience ‘bad Hillary’ as a potential bond which they can choose
to embrace, challenge or laugh off, depending on their political orientation or some other variable in the context. In this example
inscribed (explicit) negative attitude has been coupled with Hillary Clinton. However, one might argue that
providing the title of “Secretary of State” in this context also invokes negative judgement of capacity
targeted at Clinton, in the sense that Trump seems to use the title sarcastically or with a degree of disdain. In our data
analysis we have focused on inscribed couplings since these have clear realisations through the system of attitude and
have only considered invoked attitude where it is very clear from evidence present in the co-text. Most tweets contain
attitudinal meanings that are invoked via various strategies, however justifying their annotation usually requires abducing
contextual parameters that are not always available in ambient context such as Twitter (see Section 2.1 for the types of invoked attitude that are considered in Appraisal).
This tweet about Clinton does not directly address anyone as part of an explicit conversational exchange. Instead,
like many tweets, it has a potential “imagined audience” (see Marwick and boyd 2011Marwick, Alice
E., and Danah Boyd 2011 “I
Tweet Honestly, I Tweet Passionately: Twitter Users, Context Collapse, and the Imagined
Audience.” New Media &
Society 13 (1): 114–133. ;
Litt and Hargittai 2016Litt, Eden, and Eszter Hargittai 2016 “The
Imagined Audience on Social Network Sites.” Social Media+
Society 2 (1): 1–16.
) that may choose to engage with the tweet or simply read
it. This audience might include Trump’s followers or general Twitter users who search for material, browse hashtags or keywords,
or are directed to the tweet from a news site, amongst many other possibilities. The tweet received 9.1 thousand replies such as
the following examples which both table couplings that are critical of Trump’s stance on Clinton:
User 1: And this is why u will not be president. Did you do one ounce of research before you put out this tweet! Trump 32%
[ideation: Trump (you) / attitude: invoked negative judgement ]
User 2: What a stupid lie . That money has been held in escrow since 1979.
[ideation: Trump’s verbiage / attitude: negative appreciation ]
The replies above both de-align with the coupling in Trump’s tweet by challenging it with competing couplings targeting negative judgement appreciation at Trump and his verbiage. The unfolding thread of replies that criticise Trump with couplings of this kind can be interpreted as mass rallying around a ‘bad Trump’ bond, tabled as a challenge to the ‘bad Hillary’ bond that Trump asserted in his original tweet.
2.3Communing affiliation
While Twitter discourse can involve direct interaction between users, interpretable as rallying around, rejecting or
deferring social bonds using Knight’s dialogic affiliation framework, often a tweet will receive no reply. Such tweets can
nevertheless be seen to be offering potential bonds to the ambient audience (Zappavigna and
Martin 2018Zappavigna, Michele, and James
R. Martin 2018 “#
Communing Affiliation: Social Tagging as a Resource for Aligning Around Values in Social
Media.” Discourse, Context &
Media 22: 4–12. ). This is particularly the case with Trump’s tweets, where there is usually a cascade of replies but rarely
any exchange between Trump and any subsequent replies. In order to account for ambient social bonding in the absence of direct
interaction, Zappavigna and Martin (2018)Zappavigna, Michele, and James
R. Martin 2018 “#
Communing Affiliation: Social Tagging as a Resource for Aligning Around Values in Social
Media.” Discourse, Context &
Media 22: 4–12.
and Zappavigna (2021) 2021 “Ambient
Affiliation in Comments on YouTube Videos: Communing Around Values About
ASMR.” 外国语 44, no. 1: 21–40.
developed the system of communing affiliation. Communing affiliation (Figure 2) involves three strategies whereby an ideation-attitude coupling tabled in a post is made more
bondable:
convoking:44.Communing affiliation strategies are shown in small caps throughout; convoking, finessing and promoting. mustering community around a bond
finessing: dialogic positioning amongst other potential bonds
promoting: enhancing discursive visibility of a bond
These strategies are concerned with how an orientation towards a bond is established in a text; that is, how a particular ideation-attitude coupling is directed to a community, how it is set against other potential couplings offered by other potential voices in the social stream, and how it is made visible or more prominent in the social stream. Since Trump largely ignores replies to his tweets, communing affiliation offers a means of understanding the kinds of strategies he is using to build potential alignments with his audience without necessarily directly engaging with them.
Convoking is a system of meaning-making considering the resources through which a text ‘calls together’ a community or group to bond around a coupling. convocation encompasses choices in systems such as address (e.g. vocatives) which can be used to marshal a persona or group to align around a value. It can also include naming resources which can be used to designate the community to whom a value is relevant. For example, the following tweet attempts to convoke the audience, marshalled as ‘we’ around the coupling [ideation: Iran Deal / attitude: negative appreciation ] tabled at the beginning of the post:
The Iran Deal is defective at its core. If we do nothing, we know what will happen. In just a short time, the world’s leading state sponsor of terror will be on the cusp of acquiring the world’s most dangerous weapons…. https://t.co/58qwBLzxIH
Finessing a coupling refers to the modulation of a coupling with reference to other stances and voices which
may be present. This occurs through either embellishing a coupling via discursive resources such as dialogic expansion or
distilling it via resources such as dialogic contraction. For example, embellishing would open the bond to
various other possibilities offered by a range of voices with differing perspectives (e.g. I guess, I think, it seems,
maybe). In contrast distilling would limit this range, often to only one choice, for instance through
propositions that assert bald facts with monoglossic language. The relevant system of meaning at stake is the Appraisal system of
Engagement (Martin and White 2005Martin, J. R., and P. R. R. White 2005 The
Language of Evaluation: Appraisal in
English. Basingstoke: Palgrave/Macmillan. ) which accounts for the extent to which
a proposition entertains alternative viewpoints and stances, and is either dialogically expansive or dialogically contractive in
accommodating or rejecting other viewpoints. For example, the following tweet
distils
the coupling [ideation: paying billions to Iran / attitude: negative judgement
] through resources of contraction and
modality that close down other potential perspectives on this coupling:
We are stupidly paying Iran billions of dollars that we should not be paying. Why isn’t this part of the nuclear negotiations? Really dumb!
Finally, promoting a coupling refers to interpersonally emphasising the coupling in order to attract
attention in the social stream. It performs a similar function to upscaling or intensifying attitude through the system
of graduation (Martin and White 2005Martin, J. R., and P. R. R. White 2005 The
Language of Evaluation: Appraisal in
English. Basingstoke: Palgrave/Macmillan. ). This choice is very frequent in Trump’s
tweets as he used ALL CAPS and exclamation marks very frequently in his tweeting practice (see Ross and Caldwell 2020Ross, Andrew
S., and David Caldwell 2020 “ ‘Going
Negative’: An APPRAISAL Analysis of the Rhetoric of Donald Trump on Twitter.” Language &
Communication 70: 13–27.
; Wignell et al 2019Wignell, Peter, Kay O’Halloran, and Sabine Tan 2019 “Semiotic
Space Invasion: The Case of Donald Trump’s US Presidential
Campaign.” Semiotica 2019 (226): 185–208.
). For example, the following
tweet
fosters
a series of couplings negatively judging the Iranian president through
this type of typographic choice together with upscaled graduation (shown in blue and underlined):
To Iranian President Rouhani: NEVER, EVER THREATEN THE UNITED STATES AGAIN OR YOU WILL SUFFER CONSEQUENCES THE LIKES OF WHICH FEW THROUGHOUT HISTORY HAVE EVER SUFFERED BEFORE. WE ARE NO LONGER A COUNTRY THAT WILL STAND FOR YOUR DEMENTED WORDS OF VIOLENCE & DEATH. BE CAUTIOUS!
The ALL CAPS font and the upscaled graduation both emphasise the expressed attitude both through intensifiers as well as infused emphasis via Appraisal resources themselves (e.g. the choice of ‘threaten’ rather than less evaluatively loaded lexis such as ‘pressure’). Fostering typically draws upon graduation resources for upscaling or downscaling attitude (force), whereas the alternative choice, modulate, draws upon graduation resources relating to adjusting prototypicality or preciseness (focus, e.g. a true hero). As the system network in Figure 2 shows with the brace (representing an ‘and’ relation), the three choices of convoking, finessing, and promoting are simultaneous rather than mutually exclusive, and may occur together within the same post.
3.Method
The dataset explored in this paper is a specialised corpus of tweets by Trump, collected using the website http://www.trumptwitterarchive.com to include any tweet containing the word ‘Iran’, either in the body of the post or in hashtags. It spanned the period since Trump began tweeting in 2009 until the time of writing in January 2020, totalling 371 tweets. 124 of these tweets were posted during the time he was president (since 20 January 2017). Thus Trump tweeted more about Iran while he was not in the Oval Office. Most of his tweets before his presidency (about two thirds of them) were criticism of the Iran Nuclear Deal.
Detailed analysis of attitude-ideation couplings was undertaken on the entire dataset, as well as analysis of the communing
affiliation strategies (convoking, finessing, promoting) in each tweet, using Zappavigna’s (2018 2018 Searchable
Talk: Hashtags and Social Media
Metadiscourse. London: Bloomsbury
Publishing., 2021 2021 “Ambient
Affiliation in Comments on YouTube Videos: Communing Around Values About
ASMR.” 外国语 44, no. 1: 21–40.
) framework (see Section 2.3). Analysis of these strategies is aimed at understanding how Trump uses linguistic strategies to
boost the interpersonal impact of the ideation-attitude couplings that occur in his tweets, augmenting their potential bondability (in
the absence of paralinguistic resources often available in spoken discourse such gesture). The linguistic analysis was conducted using
UAM Corpus Tool (O’Donnel 2008O’Donnell, M. 2008 “UAM
Corpus Tool. Available to download from: http://www.corpustool.com.”), a tool supporting manual and semi-automatic annotation of
textual corpora. UAM Corpus Tool allows the user to annotate texts and corpora using coding schemas which are manually defined by the
user and which specify the linguistic features to be annotated. Since UAM Corpus Tool is geared toward use by Systemic Functional
Linguists, these schemas can be entered as system networks (such as Figure 1 and Figure 2) with features either being selected together (an ‘and’ relationship represented as a
brace) or selected as a choice between features (an ‘or’ relationship represented as square brackets). Each type of annotation is
applied in a separate annotation layer as shown by the layers of boxes in Figure 3 where the
darker box represents an ideation layer and the lighter boxes are Appraisal layers (each layer of boxes underneath the primary text
represents an additional layer of delicacy in the system network). UAM Corpus Tool has a built-in Appraisal layer which was used for
the coupling analysis in conjunction with a manually defined ideation layer. One of the advantages of this type of linguistic
annotation software is that it allows overlapping annotation segments (e.g. ‘Propriety’ and ‘Number’ overlap in the example in Figure 3) due to the layered annotation method. In addition, the interface allows the user to
select segments of text quickly by highlighting a section which makes the annotation of different sized units fast and manageable
which is important when working with large corpora. The annotations can be exported as XML and a range of other formats which means
that they can be processed in other software such as statistical packages. In addition, the software integrates some simple automated
analyses such as the Stanford Parser for part of speech tagging, and it also includes some search capabilities and simple
concordancing options.
In order to present the analyses in a legible way, the following annotation convention was used, adapting the convention for
annotating couplings in Zappavigna and Martin (2018)Zappavigna, Michele, and James
R. Martin 2018 “#
Communing Affiliation: Social Tagging as a Resource for Aligning Around Values in Social
Media.” Discourse, Context &
Media 22: 4–12. :
[ideation: <<>> / attitude: <<>>] x communing affiliation strategy ↘ <<>>
This annotation aims to show how the ideation-attitude coupling (with the / symbol representing how attitude and ideation fuse together to form a value) is inflected (shown with an x) by the communing affiliation strategy applied. The ↘ symbol is used to indicate the instantiation of a particular affiliation strategy in the text. An example of such annotation is shown for promoting affiliation realised by graduation in the following tweet:
10 November 2019: If Iran is able to turn over to the U.S. kidnapped former FBI Agent Robert A. Levinson, who has been missing in Iran for 12 years, it would be a very positive A step A. At the same time, upon information & belief, Iran is, & has been, enriching uranium. B THAT WOULD BE A VERY BAD B STEPB !
A [ideation: step / attitude: positive appreciation ] x Promote: foster ↘ graduation: force: very
B [ideation: step / attitude: negative appreciation ] x Promote: foster ↘ graduation: force: VERY
Text 7 promotes the ideation-attitude coupling by upscaling the attitude through lexical and typographic intensification. More examples and detailed analyses will be provided in the next section.
4.Construing negative attitude about Iran
The analysis of ideation-attitude couplings in Trump’s tweets shows his tendency to direct negative attitude toward Iran. Of the 371 tweets explored, 212 tweets negatively appraised Iran, the Iranian government, and Iran’s nuclear deal, including more than 100 tweets construing negative judgement and appreciation of Iran. For example, consider the prosody of negative judgement and appreciation in the following concordance lines:
Iran has long been secretly “enriching,” in total violation…
… Iran’s very ignorant and insulting statement , put out today, only shows that they do not understand reality…
Iran leadership doesn’t understand the words “nice” or “compassion,” they never have.
Iran made a very big mistake!
The Trump Administration has succeeded in dramatically raising the costs to Iran for its sinister behaviour…
Example (Text 8) is the following tweet about Iran’s nuclear deal with the US, a topic which Trump has consistently tweeted about (81 tweets since 2012) with negative attitude:
July 10, 2019: Iran A has long been secretly "enriching," in total violationA of the terrible B 150 billion-dollar deal made by John Kerry and the Obama Administration B. Remember, that deal was to expire in a short number of years. Sanctions will soon be increased, substantially!
This tweet contains the following couplings:
A [ideation: Iran / attitude: negative judgement ]
B [ideation: 150 billion-dollar deal... / attitude: negative appreciation ]
Iran is evaluated with negative judgement of propriety , embedding an additional coupling of Iran’s nuclear deal with negative appreciation (terrible) within this coupling.
It should be acknowledged that there were a few limited couplings of Iran with positive attitude in the corpus (15 tweets with positive appreciation or judgement), mainly where the reference was to the Iranian people and only a handful relating to the Iranian government, for example:
25 June 2019: The A wonderful A Iranian people are sufferingBC and for no reason at all C. D Their leadership spends D all of its money on Terror, and little on anything else.
A [ideation: Iranian people / attitude: positive appreciation ]
B [ideation: Iranian people / attitude: negative affect ]
C [ideation: suffering / attitude: negative appreciation ]
D [ideation: their leadership / attitude: negative judgement ]
25 September 2018: Despite requests, I have no plans to meet Iranian President Hassan Rouhani. Maybe some day in the future. I am sure he is an absolutely lovely man.
[ideation: he ( Iranian President, Hassan Rouhani ) / attitude: positive appreciation ]
In the Texts 13 and 14 above, there are couplings of positive attitude with Iranian people and Iranian president, Hassan Rouhani, as well as negative attitude with Iranian government/leadership. In the first tweet, the Iranian people are coupled with both positive appreciation (wonderful) and negative affect (suffering) which also invokes negative judgement of the Iranian government since their suffering is “for no reason at all”. This culminates in explicit negative judgement of the Iranian leadership at the end of the tweet. In this way, Trump has made a distinction between the Iranian people and the Iranian government and has appraised the former positively but the latter negatively. The second tweet, however, is of a different nature and couples positive appreciation with Iranian president, Hassan Rouhani. There were only 4 tweets of this kind where Trump directly positively assesses the Iranian government/authorities and most often this appears as a backdrop for invoking some form of self-praise (e.g. in the above, the idea that he has received multiple requests for meetings).
Trump’s tweets about Iran also feature a recurrent coupling of negative attitude with Obama/Obama’s administration
(135 tweets). This is in accord with previous research identifying Obama as a recurrent attitudinal target (see Ross and Caldwell 2020Ross, Andrew
S., and David Caldwell 2020 “ ‘Going
Negative’: An APPRAISAL Analysis of the Rhetoric of Donald Trump on Twitter.” Language &
Communication 70: 13–27. ; Kreis 2017Kreis, Ramona 2017 “The
“Tweet Politics” of President Trump.” Journal of Language and
Politics 16 (4): 607–618.
). An example is the
following:
April 6, 2015: Obama Totally Out-negotiated by Iran, Taliban, Virtually every country in the world.
[ideation: Obama / attitude: negative judgement ]
Further examples coupling Obama and other Democrats with negative attitude are shown in the following concordance lines:
…Under the terrible Obama plan , they would have been on their way to Nuclear in a short number of years…
… Obama is a disgrace & an embarrassment”
Exclusive–Donald Trump: Obama ‘Totally Out-Negotiated’ by Iran, Taliban, ‘Virtually Every Country in the World’ – http://t.co/FrtuGriGUo”
… Obama has no idea what he is doing – incompetent!
Obama seems so fawning and desperate to make a deal with Iran that lots of bad results can occur.
Our incompetent Secretary of State, Hilary Clinton , was the one who started talks to give 400 million dollars, in cash, to Iran. Scandal!
Iran looks like it is toying with John Kerry on nuclear talks- he is begging for a deal to save face. Negotiation is just not his thing!
Schumer and Democrats are big fans of being weak and passive with Iran. They have no clue…
The high frequency (143 tweets) of this type of coupling in tweets about Iran shows Trump’s preoccupation with attacking the
rival party and the previous US administration, no matter the topic and focus of his tweets (see Ross and Caldwell 2020Ross, Andrew
S., and David Caldwell 2020 “ ‘Going
Negative’: An APPRAISAL Analysis of the Rhetoric of Donald Trump on Twitter.” Language &
Communication 70: 13–27. ).
5.Communing affiliation strategies employed by Trump
This section explores how the kinds of ideation-attitude couplings that we have surveyed in Section 4 are involved in the communing affiliation strategies (i.e. convocation, finessing, and promoting) that Trump adopts. In terms of his overall tendency, promoting was the most common strategy (Table 1). 40% of the couplings in his tweets were promoted by fostering (85%) or modulating (15%). He used convoking with 23% of his couplings to muster his base of support. 60% of these targeted a person, authority, or country via marshalling. Trump also finessed the couplings in 33% of his tweets, embellishing a coupling in relation to other possible perspectives in 30% of these, and closing down the possibility of alternative couplings by distilling in 70%.
Affiliation strategy | Frequency | ||
---|---|---|---|
convocation | 23% | marshal | 60% |
designate | 40% | ||
Finessing | 33% | embellish | 30% |
distill | 70% | ||
Promoting | 40% | foster | 85% |
modulate | 15% |
5.1Convoking as a strategy for mustering Trump’s base
Trump employs convocation as an affiliation strategy in 23% of his tweets to align his base of supporters around particular values. He usually musters his supporters through attacking outsiders, which in addition to the Iranian government, include Democrats, Obama and politicians or other figures who have publicly criticised him. For example, in the tweet below, by appealing to nationalist sentiments via the #MAGA (Make America Great Again) hashtag, Trump marshals his supporters against Bob Coker, a US senator who supported the Iran nuclear deal:
Dec 23, 2018: A Bob Corker was responsible for giving us the Bhorrible BIran Nuclear Deal , which I ended, yet C he C badmouths D me for D wanting to bring our young people safely back home. Bob wanted to run and asked for my endorsement. I said NO and the game was over. #MAGA E I ELOVE TENNESSEE!
A [ideation: Bob Corker / attitude: negative judgement ] x Convoke: marshal ↘ #MAGA
B [ideation: Iran deal / attitude: negative appreciation ] x Convoke: marshal ↘ #MAGA I LOVE TENNESSEE
C [ideation: he / attitude: invoked negative judgement ] X Convoke: marshal ↘ #MAGA
D [ideation: me, Trump / attitude: positive affect ] X Convoke: marshal ↘ #MAGA
E [ideation: I / attitude: positive affect ] x Promote: foster ↘ graduation: force: all caps
In this tweet, text 24, there are several couplings negatively assessing Bob Corker and the Iran nuclear deal. Trump
marshals his ambient supporters around these couplings by the use of #MAGA which convokes his supporters via
their identification as Americans who desire their country to be restored to an imagined historical period of apparent
magnificence. This has been a common strategy to emphasise that “our country” should be protected against the “evil”, because “We”
(or ‘us’ depending on the grammatical context) are threatened by “them” (see Wodak
2015Wodak, Ruth 2015 “Critical
Discourse Analysis, Discourse-Historical Approach.” In The
International Encyclopedia of Language and Social Interaction, edited by Tracy, Karen: 1–14. New
York: John Wiley and Sons. , 66; Kreis 2017Kreis, Ramona 2017 “The
“Tweet Politics” of President Trump.” Journal of Language and
Politics 16 (4): 607–618.
, 613). In addition, the small caps font promotes
this bond, and is a typographic strategy Trump regularly uses to garner attention. The tweet positions Trump as part of a
nationalistic ingroup (‘us’), as a patriot who cares about the country and its soldiers serving overseas, while
Bob Corker is presented as an outsider who does not hold this value. This distinction aims to appeal to Trump’s supporters who
share nationalistic bonds about the value of military service. This ‘Us/We’ versus ‘Them’ distinction has been noted in many other
studies of political discourse (see for example Sarkhoh and Khosravinik, 2020Sarkhoh, Nadia, and Majid KhosraviNik 2020 “Social
Media Discourses of Arabism and the Negotiation of Self in the Middle East.” World
Englishes 39 (4): 609–622.
; Khosravinik and Zia, 2014KhosraviNik, Majid, and Mahrou Zia 2014 “Persian
Nationalism, Identity and Anti-Arab Sentiments in Iranian Facebook Discourses: Critical Discourse Analysis and Social Media
Communication.” Journal of Language and
Politics 13 (4): 755–780.
for a distinction between Us and Them in Arab versus Persian
discourse on social media).
There were a small number of tweets (15) where Trump attempts to muster his audience around positive judgement of Iran, however this mainly occurred as part of a rhetorical strategy to suggest his own positive capacity. For example, the following tweet implies Trump’s skill as a negotiator in the first sentence and then tables two couplings positively appraising Iran:
Dec 7, 2019 12:32: 30 PM Taken during the Obama Administration (despite $ 150 Billion gift), returned during the Trump Administration. Thank A you to Iran A on a very fairB negotiation B. See, we can make a deal together C!
A [ideation: Iran / attitude: invoked positive judgement ] x Convoke: marshal ↘ you
B [ideation: negotiation / attitude: positive appreciation ] x Convoke: marshal ↘ you
C [ideation: we / attitude: invoked positive judgement ] x Convoke: marshal ↘ addressing [See, we]
This tweet, Text 25, embedded the following post by The Associated Press which provides context regarding the "deal":
Iran’s foreign minister says a detained Princeton graduate student will be exchange for an Iranian scientist held by the U.S. The trade involves graduate student Xiyue Wang and scientist Massoud Soleimani. http://apne.ws/lEAvUQH
In this tweet, marshalling is used to construct a ‘we’ that includes Trump and Iran. It is difficult to untangle the logic in this kind of rhetoric, beyond the opportunity it provides Trump for boasting, as less than a month later, he ordered the killing of the Iranian General Suleimani in an Iraq airport, leading to an escalation in tensions.
5.2Finessing as a strategy for closing down the “outgroups”
finessing a coupling involves dialogic positioning through expansive and contractive resources that
acknowledge “other communities of values” (Han 2015Han, J. 2015 “#
Feminism is Not a Dirty Word’: Axiology, Ambient Affiliation and Dialogism in Discourses Surrounding Feminism in
Microblogging.” Honours Thesis, University of
Sydney, Sydney, Australia., 78). This includes tweets
acknowledging other voices which embellish (i.e. expand) or distill (i.e. contract) a coupling in terms of other
potential stances or perspectives (Zappavigna 2018 2018 Searchable
Talk: Hashtags and Social Media
Metadiscourse. London: Bloomsbury
Publishing.). In Trump’s tweets, 70% of the
couplings were distilled, meaning that there is less potential for dialogic alternatives. For example, the tweet below
couples Trump and invoked positive judgement. This coupling is finessed through closing down the dialogic space
and alternative viewpoints. The tweet begins by allowing
room for the alternative perspective that Trump “called off the strike against Iran” but this proposition is
immediately suppressed by “never”, distilling the coupling:
22 June 2019: IA never called the strike against Iran back A , as people are incorrectly B reporting B , I just stopped it from going forward at this time.
A [ideation: I [Trump ] / attitude: invoked positive judgement ] x Finessing: distill ↘ engagement: contract: disclaim: deny: never
B [ideation: reporting / attitude: negative veracity ]
The tweet invokes positive judgement of Trump in his capacity to prevent the strike “from going forward at this time”, suggesting that he might give the order again later. Trump later indicated that he had cancelled the attack shortly before it was to begin as he was told that 150 people might be killed (Chappell 2019Chappell, Bill. June 21 2019 “Trump Says He Called Off Strike On Iran Because He Didn’t See It As ‘Proportionate’.” Accessed 20 February 2020. https://www.npr.org/2019/06/21/734683701/trump-reportedly-orders-strike-on-iran-then-calls-off-attack-plan). Another example of finessing a coupling is seen in the tweet below:
30 July 2019: Just remember, the IraniansA B never won a warA , but never lost a negotiation B!
A: [ideation: Iranians / attitude: invoked negative judgement of Iran] x Finessing: distill ↘ engagement: contract: disclaim: deny: never
B: [ideation: Obama’s negotiation team [John Kerry ] / attitude: negative judgement of Obama’s team] x Finessing: distill ↘ engagement: contract: disclaim: deny: never
In this tweet “never” distills the coupling by closing the dialogic space with respect to other alternative couplings. It forms part of a prosody of tweets that construes two outgroups: Iranians and Obama’s negotiation team led by John Kerry. The positive invoked judgement of Iran in “never lost a negotiation” seems to operate only in the service of belittling Obama’s negotiation team, with the parallelism of ‘never’, an attempt at humorous ridicule.
Another common way of distilling a coupling in Trump’s tweets was through rhetorical questions, which occurred in about 40 tweets. In most cases Trump first proposes a question but subsequently provides or implies the answer to the question himself, meaning that alternative positions are suppressed. He uses this strategy to portray others negatively or close down an outgroup. In the tweet below, for example, Trump couples Barack Obama with negative judgement of capacity:
13 December 2011: who handed Iraq over to Iran yesterday? Barack Obama. We have gotten nothing from the Iraqis…
[ideation: Barack Obama / attitude: invoked negative judgement ] x Finessing: distill ↘ engagement: contract: proclaim: concur: rhetorical question
This tweet was posted a few days after President Obama ordered the withdrawal of all US forces from Iraq by the end of 2011. In this post “handed Iraq over to Iran” is a reference to the likelihood that Iran will take over if US forces leave Iraq. The rhetorical question is used to distill the coupling of Obama with invoked negative judgement of capacity (in terms of his inability to handle the withdrawal of forces strategically so that a country like Iran does not take over). While the question, together with invoked negative judgement of Obama, opens up the possibility of alternative dialogistic positions, by providing an answer (and revealing the question to in fact be rhetorical), Trump closes down the dialogic space. This distills the negative stance about Obama that Trump is attempting to propagate amongst his audience.
There are also some tweets (30% using finess) where the coupling is embellished through resources of heteroglossic expansion, entertaining other possible interpretations and alternative voices. For example, in the tweet below, there are two couplings in Trump’s statements. In the first, the Iranian government (i.e. they) is coupled with negative invoked judgement stemming from Rouhani’s statement, presented as one possible interpretation among others. In the second, the coupling of “threats” with negative invoked appreciation is embellished via the use of modality of possibility (can):
3 July 2019: Iran was just issued a new warning. Rouhani says A that they A will Enrich Uranium “to any amount we want” A if there is no new Nuclear Deal. Be careful with the threats, Iran. They B can B come back to bite you like nobody has been bitten before! B
A: [ideation : they [Iran ] / attitude: negative invoked judgement ] x Finessing: embellish ↘ engagement: expand: attribute: acknowledge: Rouhani says
B: [ideation: they [threats ] / attitude: negative invoked appreciation ] x Finessing: embellish ↘ engagement: expand: entertain: can
The embellishing of the couplings in these tweets contributes to the overall negativity and the social sanctioning of the Iranian government as an outgroup.
5.3Promoting as a strategy for garnering attention and emphasising values
Promoting is a common strategy in Trump’s tweets (occurring with 40% of the couplings) and is used to
interpersonally emphasise a coupling, in accord with Trump’s tendency toward hyperbole. It is mainly used to emphasise his
arguments, point of view, and subjective opinions. fostering a coupling is the most common choice (84%) through use of
all caps, exclamation marks, repetition of letters, and other various resources for the quantification and intensification of force (see
Martin and White 2005Martin, J. R., and P. R. R. White 2005 The
Language of Evaluation: Appraisal in
English. Basingstoke: Palgrave/Macmillan. , 154; Ross and Caldwell
2020Ross, Andrew
S., and David Caldwell 2020 “ ‘Going
Negative’: An APPRAISAL Analysis of the Rhetoric of Donald Trump on Twitter.” Language &
Communication 70: 13–27.
; Wignell et al 2019Wignell, Peter, Kay O’Halloran, and Sabine Tan 2019 “Semiotic
Space Invasion: The Case of Donald Trump’s US Presidential
Campaign.” Semiotica 2019 (226): 185–208.
). The couplings in the tweets are usually
fostered through the use of upscaled graduation resources, applied for both emphasis and garnering
attention. For example, the tweet below, Text 31, couples negative invoked judgment with President Obama’s giving money
to Iran. This coupling has been promoted by the use of all caps in the lexical item, “CASH” and the exclamation mark.
There is also another coupling of Iran’s deal with negative appreciation:
21 June 2019: President Obama made a desperate A and terrible A deal A with Iran – Gave them 150 Billion Dollars plus I.8 Billion DollarsB in CASH ! B …
A [ideation: deal / attitude: negative appreciation ]
B [ideation: President Obama … / attitude: negative invoked judgement ] x Promote: foster ↘ graduation: force: CASH!
The fostering of these couplings emphasises the incompetence of Obama as an outgrouping move. This kind of outgrouping strategy is also seen in posts such as the following warning the Iranian administration about how to behave:
23 July 2018: To Iranian President Rouhani: NEVER EVER THREATEN THE UNITED STATES AGAIN OR YOU WILL SUFFER CONSEQUENCES OF THE LIKES OF WHICH FEW THROUGHOUT HISTORY HAVE EVERT SUFFERRED BEFORE. WE ARE NO LONGER A COUNTRY THAT WILL STAND FOR YOUR DEMENTED WORDS OF VIOELNCE & DEATH. BE CATIOUS.
[ideation: Trump / attitude: positive invoked judgement ] x Promote: foster ↘ graduation: force: all caps
This tweet, as a whole, couples Trump with invoked positive judgement, fostered through use of all caps which also has the rhetorical effect of emphasising the threatening dimension of the statement.
While fostering through upscaling of force graduations was the most frequent choice, there are a few tweets (15% of promoted) where the coupling is modulated through choices in graduation that adjust prototypicality through focus. One example is the tweet below which couples a “statement” from media with negative appreciation. This coupling is promoted by modulating via focus to in terms of typicality:
21 May 2019: The Fake News put out a typically false statement , without any knowledge that the United States was trying to set up a negotiation with Iran.
[ideation: statement / attitude: negative appreciation ] x Promote: modulating ↘ graduation: focus: typically
This modulation outgroups the media as a source which usually lies and gives “false
statement(s)”. This is part of an overarching rhetorical strategy employed by Trump to position the media as
‘fake news’ (see Kreis 2017Kreis, Ramona 2017 “The
“Tweet Politics” of President Trump.” Journal of Language and
Politics 16 (4): 607–618. ).
6.Conclusion
This study used the system of communing affiliation to understand how Trump’s tweets about Iran forge different kinds of interpersonal alignments with the potential ambient audience. It considered the way his tweets position and critique different groups, and the strategies used to manifest different values. Recurrent couplings of Iran, the Iranian government, and Iran’s nuclear deal with negative attitude (mainly judgement and appreciation) were identified, as well as the role these couplings played in different communing affiliation strategies. Promoting was found to be the most common strategy and was used in Trump’s tweets to garner attention and as part of his overall tendency toward hyperbole. The other two affiliation strategies (convoking and finessing) were mainly used to muster ingroups or close down outgroups.
While each system of communing affiliation (convoke, finesse, promote) has been discussed separately in this paper, they are in fact simultaneous systems, and can all be wielded in a single tweet and with reference to the same coupling, for instance:
3 July 2019: Iran was just issued a new warning. Rouhani says A that they A will Enrich Uranium “to any amount we want” A if there is no new Nuclear Deal. Be careful with the threats, Iran. They B canB come back to bite you like nobody has been bitten before! B
A: [ideation: they / attitude: positive invoked judgment] x finess ↘ engagement: embelish: Rouhani says
B: [ideation: they / attitude: negative invoked attitude ] x convoke: designate: Iran x finess: embellish ↘ engagement: expand: entertain: can x promote: foster: !
This tweet concurrently marshals Trump’s supporters against Iran, at the same time as finessing the coupling through embellishing it by raising the possibility that Iran’s threats might backfire. The coupling is also promoted via the exclamation mark and Trump’s characteristic hyperbole (like nobody has been bitten before!). Further research might explore the extent to which these communing affiliation patterns are characteristic of his treatment of other groups that he tends to negatively assess such as women and ethnic minorities, and also whether other politicians are emulating his combative affiliation strategies.