Analyzing Tweets of Global Political Figures: Appraising Public Response to the Imran Khan’s Incident of November 2022

Authors

  • Humera Faraz Air University, Islamabad
  • Kiran Almas Air University, Islamabad
  • Kainat Noor Air University, Islamabad

Keywords:

 Appraisal analysis  Twitter  Social media  Opinion,  Attitude markers  Imran Khan

Abstract

Social media platforms are used by people to interact with one another, express their emotions, and participate in public discourse. For individuals who want to interpret public opinion from tweets, it is
crucial to evaluate social media sites. This article is an analysis of the tweets of a Pakistani political figure, the ex-prime minister. Taking the elements of appraisal
theory (Martin, et al., 2005) into account, this research aims to explore the evaluative language used by the office holders of several countries around the globe. Tweets in the media reflect the ideology of the political parties through reference to the murder attempt on
Imran Khan. Appraisal theories claim emotions are produced when certain appraisals are performed (Arnold, 1960a). A process of evaluation and subsequent emotion is frequently brought on by the
occurrence of an event since the perceptual system is built to recognize change (Ornstein, 1991). The findings
offer evidence of the maximum use of negative affect, an element of the attitude part of the theory used for this
research, because they deal with the personal emotions with regard to the incident such as Appalled," “feeling
ill," "unaccepted," "shocked," "tragic," "horrifying," "condemned," "terrible,” etc.

References

References

Alamsyah, A., Rahmah, W., & Irawan, H. (2015). Sentiment analysis based on appraisal theory for marketing intelligence in Indonesia's mobile phone market.

Journal of Theoretical and Applied Information Technology, 82(2), 335.

Arnold, M. B. (1960). Emotion and personality. Columbia University Press.

Asghar, M. Z., Khan, A., Khan, F., & Kundi, F. M. (2018). RIFT: a rule induction

framework for Twitter sentiment analysis. Arabian Journal for Science and

Engineering, 43(2), 857-877.

Bae, Y., & Lee, H. (2011, September). A sentiment analysis of audiences on twitter: who is the positive or negative audience of popular twitterers? In International

Conference on Hybrid Information Technology (pp. 732-739). Springer, Berlin,

Heidelberg.

Barbosa, L., & Feng, J. (2010, August). Robust sentiment detection on twitter from biased and noisy data. In Coling 2010: Posters (pp. 36-44).

Bartlett, T., & O'Grady, G. (Eds.). (2017). The Routledge handbook of systemic functional linguistics. Taylor & Francis.

Baykal, N. (2016). Değerleme Kuramı Açısından Türkler ve Türkçe. Uluslararası Türkçe Eğitimi ve Öğretimi Dergisi. 1(1), 111-130.

Bhatia, R., Garg, P., & Johari, R. (2018, April). Corpus based twitter sentiment analysis. In Proceedings of 3rd International Conference on Internet of Things and Connected Technologies (ICIoTCT) (pp. 26-27).

Bloom, K. (2011). Sentiment analysis based on appraisal theory and functional local

grammars. Illinois Institute of Technology.

Chingwere, M. (2014). An appraisal of the three political principals' speeches on the

occasion of the signing of the Global Political Agreement of 15 September 2008.

Faraz, H., & Asgher, J. (2021). A Trojan Hores, a Game Changer, a Silver Bullet and What Not! A Study of Metaphors in the Discourses of China-Pakistan Economic

Corrodor (CPEC). International Review of Sociial Sciences, 9(1), 386-399.

Halliday, M. A. K. (1994). An Introduction to Functional Grammar. London: Edward Arnold.

Jullian, M. P. (2011). Appraising through someone else's words: the evaluative power of quotations in news reports. Discourse & Society, 22, 766-780.

Kaur, R., & Kautish, S. (2022). Multimodal sentiment analysis: A survey and comparison. Research Anthology on Implementing Sentiment Analysis Across Multiple Disciplines, 1846-1870.

Khoo, C. S. G., Nourbakhsh, A., & Na, J. C. (2012). Sentiment analysis of online news

text: A case study of appraisal theory. Online Information Review.

Korenek, P., & Šimko, M. (2014). Sentiment analysis on microblog utilizing appraisal

theory. World Wide Web, 17(4), 847-86

Martin, J. R., & White, P. R. R. (2005). The language of evaluation: Appraisal in English. Palgrave Macmillan press.

Montoyo, A., Martínez-Barco, P., & Balahur, A. (2012). Subjectivity and sentiment

analysis: An overview of the current state of the area and envisaged developments. Decision Support Systems, 53(4), 675-679.

Oktar, L. (2002). Gazete Söyleminde İdeolojik Yapılar. 1990 Sonrası LaikAntilaik

Çatışmasında Farklı Söylemler: Disiplinlerarası Bir Yaklaşım içinde. (ss. 37-52). (Haz.) Semiramis Yağcıoğlu. İzmir: Dokuz Eylül Yayınları.

Ornstein, R., & Ehrlich, P. R. (1991). New world new mind. Anchorage Reading Service. Poecze, F., Ebster, C., & Strauss, C. (2018). Social media metrics and sentiment analysis to evaluate the effectiveness of social media posts. Procedia Computer Science, 130, 660-666.

Qiao, F., & Jiang, K. (2021). Attitudes towards global warming on Twitter: A

Hedonometer-Appraisal analysis. Journal of Global Information Management

(JGIM), 30(7), 1-20.

Roseman, I. J., & Smith, C. A. (2001). Appraisal theory. Appraisal processes in emotion: Theory, methods, research, 3-19

Ross, A. S., & Caldwell, D. (2020). ‘Going negative’: An appraisal analysis of the rhetoric of Donald Trump on Twitter. Language & communication, 70, 13-27.

Saeed, S., Zahra, T., & Fayyaz, A. A. (2021). Sentiment analysis of Imran Khan's tweets.

Pakistan Journal of Psychological Research, 36(3), 473-494.

Syed, A. Z. (2015, November). Applying sentiment and emotion analysis on brand tweets for digital marketing. In 2015 IEEE Jordan Conference on Applied Electrical

Engineering and Computing Technologies (AEECT) (pp. 1-6). IEEE.

Tribune, the express. News desk (2022, November). Social media reacts to targeted attack on Imran Khan

Tribune, the express. News desk (2022, November). World leaders denounce assassination attempt on Imran Khan

Urda, J., & Loch, C.H. (2013). Social preferences and emotions as regulators of behavior in processes. Journal of Operations Management, 31, 6-23.

Whitelaw, C., Garg, N., & Argamon, S. (2005, October). Using appraisal groups for

sentiment analysis. In Proceedings of the 14th ACM international conference on

Information and knowledge management (pp. 625-631).

Yildirim, A., & Simsek, H. (2006). Research Methods in Social Sciences. Ankara:

Seckin Yayincilik.

Zappavigna, M. (2011). Ambient affiliation: A linguistic perspective on Twitter. New

media & society, 13(5), 788-806

Published

2024-03-16

How to Cite

Humera Faraz, Kiran Almas, & Kainat Noor. (2024). Analyzing Tweets of Global Political Figures: Appraising Public Response to the Imran Khan’s Incident of November 2022. Erevna: Journal of Linguistics and Literature, 7(2), 41-55. Retrieved from https://journals.au.edu.pk/ojserevna/index.php/erevna/article/view/310