A Critical Discourse Analysis of Trump’ s tweets based on Van Dijk Model

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Kalantari Khandani Ezatollah; Frrokhi Barfe Mohammad Hasan; GHONCHEPOUR MOUSA

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Journal: ZABANPAZHUHI (Iranian Journal of Language Research) Year:2020 | Volume:12 | Issue:34 Page(s): 155-156

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Title

A Critical Discourse Analysis of Trump’ s tweets based on Van Dijk Model

Author(s)

Kalantari Khandani Ezatollah | Frrokhi Barfe Mohammad Hasan | GHONCHEPOUR MOUSA | Issue Writer Certificate

Keywords

TweetQ1

rhetorical analysisQ1

Van Dijk ModelQ1

TrumpQ1

critical discourse analysisQ1

Abstract

Twitter has changed the way information and data are circulated among a lot of users. Most of them are spreading through the societies, because certain thoughts and ideas are going to be imposed. Authorities have found this great powerful tool can successfully make common people make decisions as they wish to do. It seems that more than 500 million Tweets are sent daily from 320 million active users across the world and it increases everyday (Twitter. com). This unbelievable number of Tweets can create new groups and shape new ideologies among active users. A widespread stream of quickly communicated suppositions and thoughts might lead to uncontrollable event and supervise the life style of millions of people around the world. It might also interfere with political affairs and drastic changes happen due to intentional spread of thoughts putting policy makers in severe troubles. Amazingly, journalists make use of this tool as a monitoring system to find private and fascinating news about celebrities and famous sportsmen and women. They want to feed their media enough firsthand information to attract a lot of readers and users. They want to sell more, if they can have direct access to popular figures’ twitter page, their missions are completely done; that is why Tweeter is important to them. The present study aims to study and analyze some of the issues raised by critical discourse analytical approach to the study of speeches, e. g. Tweets. Since social networks have given a lot of opportunities to people put forward, acquire, express and reproduce their views, thoughts, ideologies and even their own daily routine activities largely by text or talk, a discourse analytical study of these language interactions seem to be necessary and most relevant. The more people become familiar with social media, the less they are vulnerable to be misled by indecent authorities. As present societies are now experiencing different ways for language interactions, the role and the influence of social networks, e. g. Twitter, are undeniable and need to be analyzed. The study of Tweets has made the linguists believe that twitting is a kind of social action and leads to processing social issues and if Tweet lexicons are chosen appropriately, they can have big effecton followers’ decisions and cause shapingideological groups. Houston and colleagues (2015) firmly believe that Tweets can form social actions and guide the societies towards certain directions. The discourse analysis of Tweets will reveal the type of interactions that twitter users have. It can also represent the way in which knowledge and power are produced. In other words, speech order, discourse and discourse analysis are to be seen as social productions that have changing and dynamic forces. They can have influences over social values and interactions, whether positive or negative (Ziahosseiny, 2012, p. 97). Of course, this kind of discourse analysis has to be certainly social-critical, because it has to find the roots of social problems (Ziahosseiny, 2012, p. 98). That is why we have made use of critical discourse analysis to clarify the ways by which realities are represented in social networks. Although, in this paper, the main attention has been given to the discourse analysis, its theoretical structure is based on different disciplines, especially on Van Dijk triangulation of discourse, cognition and society; they are necessary for analyzing sociolinguistics phenomena. Social sciences and philosophy have made the best use of this framework and they can critically explain social actions. These can also play an important role in reshaping the traditional approaches to social events as those approaches cannot fully and adequately elaborate on the sociocognitive nature and structures of ideologies and their discursive reproduction. In the present study, Trump’ s Tweets are analyzed based on the aforementioned considerations related to Van Dijk Model. To do that, 400 of Trump’ s Tweets from his twitter page, between January and March 2018, were studied. Then, based on linguistic signs and strategies put forward by Van Dijk (2003 & 2006), the Tweets were analyzed carefully. Those linguistic signs and strategies are: classification, polarization, generalization, distancing, implications, hyperbole, counterfactual, contrast, lexicalization, evidentiality, comparison, fallacy and euphemism. The findings show that Trump uses these strategies to create his own ideology. They also demonstrate that Trump makes use of hyperbole instead of logical reasoning. The data indirectly prove that Tweeter followers are constantly exposed to new ideologies; also, the dialogues have their own prompt influences on societies, make new social theories, play basic roles in people’ s life style and create new ideologies in groups.

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APA: Copy

Kalantari Khandani, Ezatollah, Frrokhi Barfe, Mohammad Hasan, & GHONCHEPOUR, MOUSA. (2020). A Critical Discourse Analysis of Trump’ s tweets based on Van Dijk Model. JOURNAL OF ZABANPAZHUHI, 12(34 ), 155-156. SID. https://sid.ir/paper/397594/en

Vancouver: Copy

Kalantari Khandani Ezatollah, Frrokhi Barfe Mohammad Hasan, GHONCHEPOUR MOUSA. A Critical Discourse Analysis of Trump’ s tweets based on Van Dijk Model. JOURNAL OF ZABANPAZHUHI[Internet]. 2020;12(34 ):155-156. Available from: https://sid.ir/paper/397594/en

IEEE: Copy

Ezatollah Kalantari Khandani, Mohammad Hasan Frrokhi Barfe, and MOUSA GHONCHEPOUR, “A Critical Discourse Analysis of Trump’ s tweets based on Van Dijk Model,” JOURNAL OF ZABANPAZHUHI, vol. 12, no. 34 , pp. 155–156, 2020, [Online]. Available: https://sid.ir/paper/397594/en

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