Journal
Politeness Strategies Used by Trump and El-Sisi in Their Speeches at United Nations Assembly
English Education Journal · Vol. 13 No. 1 (2023) · pp. 12–19
- ISSN
- 2087-0108, 2502-4566
- Published
- 2023-03-15
- Publisher
- Universitas Negeri Semarang
- Language
- eng
Abstract
In this study, the researchers identified ways that politeness strategies are commonly employed in a speech. Specifically, this study aimed at exploring the politeness strategies used by Donald Trump and General El Sisi during their speech at the 75th session of the UN General Assembly. Both the similarities and the differences between Donald Trump’s and General Sisi's use of politeness strategies and sub-strategies in their speeches were investigated. A qualitative research approach was conducted, and the theory of politeness strategies by Brown and Levinson was applied as the analysis framework. The research data was collected from the 57 utterances in Trump's speech and 79 utterances in General Sisi's speech. The analysis results showed that both Trump and El-Sisi applied bald on record, positive, and negative politeness. Specifically, the politeness strategies found in Trump's speech were 10 utterances of bald on record, 53 utterances of positive politeness, 8 utterances of negative politeness, and two utterances of off-record strategy. On the contrary, General Sisi's speech mostly contained negative politeness strategies. It was found that there were 70 utterances of negative politeness, 11 utterances of positive politeness, and 1 utterance of off-record strategy. These various politeness strategies used by Donald Trump and General Sisi could not be separated from their respective social positions, social distances, and cultural backgrounds.
Collaboration network of the authors
40 authors · 123 co-authorship links · showing the 40 most connected
Hover or tap a name to highlight its co-authors. Double-click to open the author's page.
- Institut Teknologi Sepuluh Nopember
- Affiliation unknown
- Different organisations
- Same organisation
- Affiliation unknown
- Thicker line = more joint articles · bigger circle = more articles
Show as table
| Co-author | Organisation | Joint articles |
|---|---|---|
| Dwi Rukmini | Affiliation unknown | 9 |
| Abdurrachman Faridi | Affiliation unknown | 6 |
| Januarius Mujiyanto | Affiliation unknown | 5 |
| Warsono Warsono | Affiliation unknown | 5 |
| Rudi Hartono | Affiliation unknown | 5 |
| Widya Amalia | Affiliation unknown | 4 |
| Ahmad Sofwan | Affiliation unknown | 4 |
| Issy Yuliasri | Affiliation unknown | 4 |
| Sri Wuli Fitriati | Affiliation unknown | 3 |
| Sri Wuli Fitriati | Affiliation unknown | 3 |
| Katharina Rustipa | Affiliation unknown | 2 |
| Frimadhona Syafri | Affiliation unknown | 2 |
| Fahrur Rozi | Institut Teknologi Sepuluh Nopember | 2 |
| Djoko Sutopo | Affiliation unknown | 2 |
| SRI WAHYUNI | Affiliation unknown | 2 |
| Indah Nurhidayah | Affiliation unknown | 1 |
| Rahmiwati Rahmiwati | Affiliation unknown | 1 |
| Januarius Mujiiyanto | Affiliation unknown | 1 |
| Annisa Nur Atikah | Affiliation unknown | 1 |
| Prahda Alifa Fegasanti | Affiliation unknown | 1 |
| Fahmi Musthafa | Affiliation unknown | 1 |
| Urfatul Makhsunah | Affiliation unknown | 1 |
| Fahmi Arif Sangaji | Affiliation unknown | 1 |
| Yesi Novita Sari | Affiliation unknown | 1 |
| Syifa Fellashufa Fadillah | Affiliation unknown | 1 |
| Henrikus Joko Yulianto | Affiliation unknown | 1 |
| Regita Widya Murti | Affiliation unknown | 1 |
| Melawati Anggrayani | Affiliation unknown | 1 |
| Dini Setiana ningrum | Affiliation unknown | 1 |
| Ratna Widya Iswara | Affiliation unknown | 1 |
| Arif Arga Kusuma | Affiliation unknown | 1 |
| Abdurrahman Faridi | Affiliation unknown | 1 |
| Nur Laila Hafidhoh | Affiliation unknown | 1 |
| Dwi Undayasari | Affiliation unknown | 1 |
| IGede Arga Anggara | Affiliation unknown | 1 |
| sigit sulistiyanto | Affiliation unknown | 1 |
| Ratih Oktaviani | Affiliation unknown | 1 |
Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.