The Gaza War: Text Analysis

Authors

  • Namkil Kang

    College of Liberal Arts, Far East University, Chungbuk, Republic of Korea

DOI:

https://doi.org/10.30564/fls.v6i6.7638
Received: 29 October 2024 | Revised: 11 November 2024 | Accepted: 11 November 2024 | Published Online: 9 December 2024

Abstract

The objective of this paper is to conduct a text analysis of 40 BBC News broadcasts from the year 2024. Notably, the term "Gaza" appears with the highest frequency, totaling 335 tokens, and occupies a significant proportion of the coverage. This prominence is further illustrated by its substantial representation in a word cloud, suggesting its status as a pivotal topic. Additionally, the term "Israel" ranks second in prominence, indicating its relevance, though slightly less so than Gaza. Other noteworthy keywords include "homes," "base," "campaign," "attack," "conditions," "group," "leader," and "ceasefire," all of which contribute to the narrative surrounding the conflict. The data reveals that "Gaza" has a 10.5% likelihood of being identified as a main topic, while "Israel" has an 8.4% likelihood. Moreover, the similarity index indicates that the terms "Gaza" and "BBC" share the highest degree of similarity, followed closely by "Hamas" and "Gaza." These findings underscore the importance of language in shaping public perception and discourse surrounding complex geopolitical issues. In conclusion, BBC News does not take a stance in favor of either Israel or Hamas; rather, it maintains a neutral position. This impartiality is effectively illustrated through various analytical methods, including term frequency analysis, word cloud analysis, network analysis, topic analysis, and similarity analysis.

Keywords:

Big Data; Topic; Similarity; Term Frequency; Network; Word Cloud; Cluster

References

[1] Gee, J.P., 2014. An Introduction to Discourse Analysis: Theory and Method. Routledge: New York, USA. pp. 1-250.

[2] Biber, D., Conrad, S., Reppen, R., 1998. Corpus Linguistics: Investigating Language Structure and Use. Cambridge University Press: Cambridge, UK. pp. 1-400.

[3] Halliday, M.A.K., Matthiessen, C., 2014. An Introduction to Functional Grammar. Routledge: London, UK. pp. 1-500.

[4] Swales, J.M., Feak, C.B., 2004. Academic Writing for Graduate Students: Essential Tasks and Skills. University of Michigan Press: Ann Arbor, USA. pp. 1-300.

[5] Van Dijk, T.A., 1997. Discourse as Structure and Process. Sage Publications: Thousand Oaks, USA. pp. 1-400.

[6] Sampson, G., 2001. Empirical Linguistics. Continuum: London, UK. pp. 1-250.

[7] Baker, P., 2006. Using Corpora in Discourse Analysis. London: Continuum: London, UK. pp. 1-250.

[8] McEnery, T., Wilson, A., 2001. Corpus Linguistics: An Introduction. Edinburgh: Edinburgh University Press: Edinburgh, UK. pp. 1-350.

[9] Tognini-Bonelli, E., 2001. Corpus Linguistics at Work. John Benjamins Publishing: Amsterdam, Netherlands. pp. 1-250.

[10] Sinclair, J., 1991. Corpus, Concordance, Collocation. Oxford: Oxford University Press: Oxford, UK. pp. 1-200.

[11] Gries, S. T., 2009. Quantitative Approaches in Usage-based Linguistics. In: Handbook of Cognitive Linguistics. New York: Routledge: New York, USA. pp. 178-195.

[12] McEnery, T., 2011. Corpus Linguistics: Method, theory and practice. Palgrave Macmillian: London, UK. pp. 1-300.

[13] Baker, P., McEnery, T., 2005. A Corpus-Based Study of Euphemism and Dysphemism. Journal of Pragmatics. 37(6), 955-967.

[14] Lott, D., 2009. The Use of Corpora in the Teaching of English for Academic Purposes. English for Specific Purposes. 28(2), 119-130.

[15] Charles, M., 2011. A Corpus-Based Study of Academic Writing. Journal of English for Academic Purposes. 10(3), 213-226.

[16] McCallum, A., 2005. MALLET: A Machine Learning for Language Toolkit. Available from: http://mallet.cs.umass.edu (cited 2 December 2, 2024).

[17] Taboada, M., Grieve, J., 2004. Analyzing Sentiment in Text. Computational Linguistics. 30(3), 259-270.

[18] Evison, J., Turner, K., 2014. Using Corpora for Text Analysis in Research. Language Resources and Evaluation, 48(1). 69-85.

[19] Rayson, P., Garside, R., 2000. Comparing Corpora Using Frequency Profiling. Proceedings of the Workshop on Linguistic Data Consortium; May 30-June 1, 2000; Philadelphia, USA. pp. 1-15.

[20] Baroni, M., Bernardini, S., 2006. Bootstrapping the WordNet with a Corpus-Based Approach. Proceedings of the International Conference on Language Resources and Evaluation; May 22-28, 2006; Genoa, Italy. pp. 1-10.

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How to Cite

Kang, N. (2024). The Gaza War: Text Analysis. Forum for Linguistic Studies, 6(6), 589–604. https://doi.org/10.30564/fls.v6i6.7638

Issue

Vol. 6 , Iss. 6 (December 2024)

Article Type

Article

License

Copyright © 2024 Moussa Diagne Faye, Vini Yves Bernadin Loyara, Amadou Keita, Mamadou Diop, Angelbert Chabi Biaou, Mahamadou Koita, Hamma Yacouba

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This is an open access article under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) License.