Image repair strategies in the CEO’s tweets regarding AirAsia’s QZ8501 crisis / Grace Lee Si Yunn

In light of the AirAsia QZ8501 crash in December 2014, Tony Fernandes as the Chief Executive Officer, took to Twitter to provide updates on the next course of actions taken by AirAsia as well as convey his thoughts and feelings. Attempts were made by Fernandes to repair his affected image and that o...

Full description

Saved in:
Bibliographic Details
Main Author: Grace Lee , Si Yunn
Format: Thesis
Published: 2019
Subjects:
Online Access:http://studentsrepo.um.edu.my/10638/2/Grace_Lee.pdf
http://studentsrepo.um.edu.my/10638/1/Grace_Lee_Si_Yunn_%E2%80%93_Dissertation.pdf
http://studentsrepo.um.edu.my/10638/
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.um.stud.10638
record_format eprints
spelling my.um.stud.106382020-01-18T03:11:24Z Image repair strategies in the CEO’s tweets regarding AirAsia’s QZ8501 crisis / Grace Lee Si Yunn Grace Lee , Si Yunn P Philology. Linguistics In light of the AirAsia QZ8501 crash in December 2014, Tony Fernandes as the Chief Executive Officer, took to Twitter to provide updates on the next course of actions taken by AirAsia as well as convey his thoughts and feelings. Attempts were made by Fernandes to repair his affected image and that of his company to reduce the risk of running losses and also to regain public trust. His effort was crucial as responses to the crisis would be a defining moment in the history of the corporation, determining whether the corporation makes it or breaks. The attempts to repair the sullied reputation are discussed with reference to Benoit’s (2015) image repair theory. It is revealed that Fernandes employed corrective action, bolstering, mortification, denial, and defeasibility. The tweets pertaining to the crisis obtained from Fernandes’s official Twitter account are used as the data and analysed to identify the most salient linguistic features present as well as explain how they realise the function of image repair. The features covered in this work are the personal pronouns ‘I’ and ‘we’ and their possessive determiners, the modal auxiliary ‘will’, the present tense, and the past tense. As manual analysis is conducted, a known limitation is that the interpretation and explanation of the data are subjective due to the influence of the researcher’s prior knowledge. As such, there is a possibility that the understanding and descriptions provided in this work might differ from those of the readers of this work. That this study does not investigate the effectiveness of strategies adopted enables it to be extended in that particular area in the future. 2019-06 Thesis NonPeerReviewed application/pdf http://studentsrepo.um.edu.my/10638/2/Grace_Lee.pdf application/pdf http://studentsrepo.um.edu.my/10638/1/Grace_Lee_Si_Yunn_%E2%80%93_Dissertation.pdf Grace Lee , Si Yunn (2019) Image repair strategies in the CEO’s tweets regarding AirAsia’s QZ8501 crisis / Grace Lee Si Yunn. Masters thesis, University of Malaya. http://studentsrepo.um.edu.my/10638/
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Student Repository
url_provider http://studentsrepo.um.edu.my/
topic P Philology. Linguistics
spellingShingle P Philology. Linguistics
Grace Lee , Si Yunn
Image repair strategies in the CEO’s tweets regarding AirAsia’s QZ8501 crisis / Grace Lee Si Yunn
description In light of the AirAsia QZ8501 crash in December 2014, Tony Fernandes as the Chief Executive Officer, took to Twitter to provide updates on the next course of actions taken by AirAsia as well as convey his thoughts and feelings. Attempts were made by Fernandes to repair his affected image and that of his company to reduce the risk of running losses and also to regain public trust. His effort was crucial as responses to the crisis would be a defining moment in the history of the corporation, determining whether the corporation makes it or breaks. The attempts to repair the sullied reputation are discussed with reference to Benoit’s (2015) image repair theory. It is revealed that Fernandes employed corrective action, bolstering, mortification, denial, and defeasibility. The tweets pertaining to the crisis obtained from Fernandes’s official Twitter account are used as the data and analysed to identify the most salient linguistic features present as well as explain how they realise the function of image repair. The features covered in this work are the personal pronouns ‘I’ and ‘we’ and their possessive determiners, the modal auxiliary ‘will’, the present tense, and the past tense. As manual analysis is conducted, a known limitation is that the interpretation and explanation of the data are subjective due to the influence of the researcher’s prior knowledge. As such, there is a possibility that the understanding and descriptions provided in this work might differ from those of the readers of this work. That this study does not investigate the effectiveness of strategies adopted enables it to be extended in that particular area in the future.
format Thesis
author Grace Lee , Si Yunn
author_facet Grace Lee , Si Yunn
author_sort Grace Lee , Si Yunn
title Image repair strategies in the CEO’s tweets regarding AirAsia’s QZ8501 crisis / Grace Lee Si Yunn
title_short Image repair strategies in the CEO’s tweets regarding AirAsia’s QZ8501 crisis / Grace Lee Si Yunn
title_full Image repair strategies in the CEO’s tweets regarding AirAsia’s QZ8501 crisis / Grace Lee Si Yunn
title_fullStr Image repair strategies in the CEO’s tweets regarding AirAsia’s QZ8501 crisis / Grace Lee Si Yunn
title_full_unstemmed Image repair strategies in the CEO’s tweets regarding AirAsia’s QZ8501 crisis / Grace Lee Si Yunn
title_sort image repair strategies in the ceo’s tweets regarding airasia’s qz8501 crisis / grace lee si yunn
publishDate 2019
url http://studentsrepo.um.edu.my/10638/2/Grace_Lee.pdf
http://studentsrepo.um.edu.my/10638/1/Grace_Lee_Si_Yunn_%E2%80%93_Dissertation.pdf
http://studentsrepo.um.edu.my/10638/
_version_ 1738506391906156544
score 13.209306