Visualization acceptance among the data journalists in the United Arab Emirates: A structural equation modeling-based study

Faycal Farhi 1 * , Riadh Jeljeli 1, Abdelouahab Boukhenoufa 2, Mohamed Mallek 3, Kafia Lassouane 4
More Detail
1 Al Ain University, College of Communication and Media, Al Ain, UNITED ARAB EMIRATES
2 Sultan Qaboos University, Mascate, OMAN
3 University of Khorfakkan, College of Arts Sciences and Information Technology, Department of Communication, Sharjah, UNITED ARAB EMIRATES
4 King Khaled University, Faculty of Humanities, Media and Communication Department, KINGDOM OF SAUDI ARABIA
* Corresponding Author
Online Journal of Communication and Media Technologies, Volume 14, Issue 4, Article No: e202447. https://doi.org/10.30935/ojcmt/14986
OPEN ACCESS   233 Views   105 Downloads   Published online: 20 Aug 2024
Download Full Text (PDF)

ABSTRACT

New trends and practices in journalism and news-making contribute to data journalism’s increasing adoption and use. This study highlights and examines data journalism as a significant practice among journalists in the United Arab Emirates. Theoretically supported by social cognitive theory, data from 309 journals is analyzed using structural equation modelling. The results show a strong preference among Emirati journalists for using data journalism professionally. These journalists encode data using various visualization approaches to improve data availability and transparency for readers. Also, they prioritize assuring easy and understandable data decoding among audiences, potentially promoting critical thinking. Thus, the study concludes that Emirati journalists are assertive about adopting and using data journalism approaches to enhance their skills and provide transparent data to readers. Also, data journalism’s preference reflects technology’s integration into traditional journalism, transforming communication into a two-way process. Finally, the research discusses the study implications, limitations, and recommendations accordingly.

CITATION

Farhi, F., Jeljeli, R., Boukhenoufa, A., Mallek, M., & Lassouane, K. (2024). Visualization acceptance among the data journalists in the United Arab Emirates: A structural equation modeling-based study. Online Journal of Communication and Media Technologies, 14(4), e202447. https://doi.org/10.30935/ojcmt/14986

REFERENCES

  • Abbott, M. L., & McKinney, J. (2013). Understanding and applying research design. John Wiley & Sons.
  • Acharya, A. S., Prakash, A., Saxena, P., & Nigam, A. (2013). Sampling: Why and how of it? Indian Journal of Medical Specialties, 15(3). https://doi.org/10.7713/ijms.2013.0032
  • Afsar, M., & Kumari, S. (2020). Empowerment of women journalists through technology in rural areas of India. In Proceedings of the 3rd International Conference on Advanced Research in Social Sciences & Humanities (pp. 34–43).
  • Ali, Z. S. (2023). Media and non-media sources for disaster risk reduction. Online Journal of Communication and Media Technologies, 13(3), Article e202322. https://doi.org/10.30935/ojcmt/13095
  • Anderson, B., & Borges-Rey, E. (2019). Encoding the UX: User interface as a site of encounter between data journalists and their constructed audiences. Digital Journalism, 7(9), 1253–1269. https://doi.org/10.1080/21670811.2019.1607520
  • Appelgren, E. (2018). An illusion of interactivity. Journalism Practice, 12(3), 308–325. https://doi.org/10.1080/17512786.2017.1299032
  • Appelgren, E., & Lindén, C.-G. (2020). Data journalism as a service: Digital native data journalism expertise and product development. Media and Communication, 8(2), 62–72. https://doi.org/10.17645/mac.v8i2.2757
  • Auväärt, L. (2022). Fighting COVID-19 with data: An analysis of data journalism projects submitted to sigma awards 2021. Central European Journal of Communication, 15(3), 37–395. https://doi.org/10.51480/1899-5101.15.3(32).3
  • Bagozzi, R. P., & Yi, Y. (2012). Specification, evaluation, and interpretation of structural equation models. Journal of the Academy of Marketing Science, 40(1), 8–34. https://doi.org/10.1007/s11747-011-0278-x
  • Bebawi, S. (2020). Data journalism and investigative reporting in the Arab world: From emotive to evidence-based journalism. In B. Mutsvairo, S. Bebawi, & E. Borges-Rey (Eds.), Data journalism in the global south. Palgrave studies in journalism and the global south (pp. 193–204). Palgrave Macmillan. https://doi.org/10.1007/978-3-030-25177-2_11
  • Beiler, M., Irmer, F., & Breda, A. (2020). Data journalism at German newspapers and public broadcasters: A quantitative survey of structures, contents and perceptions. Journalism Studies, 21(11), 1571–1589. https://doi.org/10.1080/1461670X.2020.1772855
  • Binns, A. (2017). Fair game? Journalists’ experiences of online abuse. Journal of Applied Journalism & Media Studies, 6(2), 183–206. https://doi.org/10.1386/ajms.6.2.183_1
  • Bolarinwa, O. A. (2015). Principles and methods of validity and reliability testing of questionnaires used in social and health science researches. Nigerian Postgraduate Medical Journal, 22(4), 195–201. https://doi.org/10.4103/1117-1936.173959
  • Borges-Rey, E. (2016). Unravelling data journalism. Journalism Practice, 10(7), 833–843. https://doi.org/10.1080/17512786.2016.1159921
  • Borges-Rey, E. (2020). Towards an epistemology of data journalism in the devolved nations of the United Kingdom: Changes and continuities in materiality, performativity and reflexivity. Journalism, 21(7), 915–932. https://doi.org/10.1177/1464884917693864
  • Boyles, J. L., & Meyer, E. (2018). Letting the data speak. Digital Journalism, 4(7), 944–954. https://doi.org/10.1080/21670811.2016.1166063
  • Bradshaw, P. (2017). Data journalism. In P. Bradshaw (Ed.), The online journalism handbook. Routledge. https://doi.org/10.4324/9781315761428-10
  • Broussard, R. (2020). “Stick to sports” is gone: A field theory analysis of sports journalists’ coverage of socio-political issues. Journalism Studies, 21(12), 1627–1643. https://doi.org/10.1080/1461670X.2020.1785323
  • Chen, M., Cao, Y., & Liang, Y. (2021). Determinants of open government data usage: Integrating trust theory and social cognitive theory. Government Information Quarterly, 40(4), Article 101857. https://doi.org/10.1016/j.giq.2023.101857
  • Chettah, M., & Farhi, F. (2023). The future of the journalism profession from the perspective of professionals following the COVID-19 pandemic. Academic Journal of Interdisciplinary Studies, 12(3), Article 179. https://doi.org/10.36941/ajis-2023-0070
  • Chwialkowski, K., Strathmann, H., & Gretton, A. (2018). A kernel test of goodness of fit. arXiv. https://doi.org/10.48550/arXiv.1602.02964
  • Codina, L. (2021). The binomial of interaction and visualization in digital news media: Consolidation, standardization and future challenges. El Profesional de la Informacion, 30(4), 1–15.
  • Conner, M., & Norman, P. (2015). Predicting and changing health behaviour: Research and practice with social cognition models. McGraw-Hill Education.
  • Cushion, S., Lewis, J., & Callaghan, R. (2017). Data journalism, impartiality and statistical claims. Journalism Practice, 11(10), 1198–1215. https://doi.org/10.1080/17512786.2016.1256789
  • Darwish, E. B. (2020). The effectiveness of using social media in government communication in UAE. https://zuscholars.zu.ac.ae/workingpapers/10/
  • de-Lima-Santos, M.-F., & Mesquita, L. (2021). The strategic value of data journalism. In R. Salaverría, & M.-F. de-Lima-Santos (Eds.), Journalism, data and technology in Latin America (pp. 97–136). Springer. https://doi.org/10.1007/978-3-030-65860-1_4
  • Engebretsen, M., Kennedy, H., & Weber, W. (2018). Data visualization in Scandinavian newsrooms: Emerging trends in journalistic visualization practices. Nordicom Review, 39(2), 3–18. https://doi.org/10.2478/nor-2018-0007
  • Fahmy, N., & Attia, M. A. M. (2021). A field study of Arab data journalism practices in the digital era. Journalism Practice, 15(2), 170–191. https://doi.org/10.1080/17512786.2019.1709532
  • Farhi, F., & Mohamed, M. M. A. (2023). Media dealing with international crises: An analytical study of international channels through social networking pages: “Al-Hurra” American channel and “France24” Arabic channels examples. Studies in Media and Communication, 11(6), 261–270. https://doi.org/10.11114/smc.v11i6.6004
  • Farhi, F., Jelieli, R., Aburezeq, I., Zamoum, K., Al-Shami, S. A., & Hacini, I. (2023). Determinants behind continuous intention to use data journalism among Emirati journalists. In Proceedings of the 2023 International Conference on Multimedia Computing, Networking and Applications (pp. 48–54). IEEE. https://doi.org/10.1109/MCNA59361.2023.10185779
  • Ferrer-Conill, R., & Tandoc, E. C. (2018). The audience-oriented editor: Making sense of the audience in the newsroom. Digital Journalism, 6(4), 436–453. https://doi.org/10.1080/21670811.2018.1440972
  • Friedman-Romell, B. H. (1995). Breaking the code: Toward a reception theory of theatrical cross-dressing in eighteenth-century London. Theatre Journal, 47(4), 459–479. https://doi.org/10.2307/3208987
  • Fu, Y., & Stasko, J. (2023). More than data stories: Broadening the role of visualization in contemporary journalism. IEEE Transactions on Visualization and Computer Graphics, 30(8), 5240–5259. https://doi.org/10.1109/TVCG.2023.3287585
  • Gehrke, M. (2020). Transparency as a key element of data journalism: Perceptions of Brazilian professionals. In Proceedings of the Computation + Journalism Symposium.
  • Heravi, B. R. (2019). 3Ws of data journalism education. Journalism Practice, 13(3), 349–366. https://doi.org/10.1080/17512786.2018.1463167
  • Ishmuradova, I. I., Chistyakov, A. A., Klebanov, L. R., Sliusar, V. V., Sliusar, M. V., Devyatkin, G. S., & Drobysheva, N. N. (2024). A decadal review of the role of communication-mobile technologies in promoting digital inclusion: Digital divide. Online Journal of Communication and Media Technologies, 14(3), Article e202438. https://doi.org/10.30935/ojcmt/14709
  • Kabha, R. (2019). Comparison study between the UAE, the UK, and India in dealing with WhatsApp fake news. Journal of Content, Community and Communication, 10(9), 176–186. https://doi.org/10.31620/JCCC.12.19/18
  • Kalatzi, O., Bratsas, C., & Veglis, A. (2018). The principles, features and techniques of data journalism. Studies in Media and Communication, 6(2), 36–44. https://doi.org/10.11114/smc.v6i2.3208
  • Khatun, N. (2021). Applications of normality test in statistical analysis. Open Journal of Statistics, 11(01), 113–122. https://doi.org/10.4236/ojs.2021.111006
  • Lewis, N. P., & Nashmi, E. A. (2019). Data journalism in the Arab Region: Role conflict exposed. Digital Journalism, 7(9), 1200–1214. https://doi.org/10.1080/21670811.2019.1617041
  • Lewis, N. P., McAdams, M., & Stalph, F. (2020). Data journalism. Journalism & Mass Communication Educator, 75(1), 16–21. https://doi.org/10.1177/1077695820904971
  • Lu, S. (2020). Taming the news feed on Facebook: Understanding consumptive news feed curation through a social cognitive perspective. Digital Journalism, 8(9), 1163–1180. https://doi.org/10.1080/21670811.2020.1837639
  • Mello, S. C. B. D., & Collins, M. (2001). Convergent and discriminant validity of the perceived risk scale in business-to-business context using the multitrait-multimethod approach. Revista de Administração Contemporânea, 5(3), 167–186. https://doi.org/10.1590/S1415-65552001000300009
  • Munoriyarwa, A. (2022). Data journalism uptake in South Africa’s mainstream quotidian business news reporting practices. Journalism, 23(5), 1097–1113. https://doi.org/10.1177/1464884920951386
  • Mutsvairo, B. (2019). Challenges facing development of data journalism in non-Western societies. Digital Journalism, 7(9), 1289–1294. https://doi.org/10.1080/21670811.2019.1691927
  • Palomo, B., Teruel, L., & Blanco-Castilla, E. (2019). Data journalism projects based on user-generated content. How La Nacion data transforms active audience into Staff. Digital Journalism, 7(9), 1270–1288. https://doi.org/10.1080/21670811.2019.1626257
  • Piepho, H. (2019). A coefficient of determination (R2) for generalized linear mixed models. Biometrical Journal, 61(4), 860–872. https://doi.org/10.1002/bimj.201800270
  • Porlezza, C., & Splendore, S. (2019). From open journalism to closed data: Data journalism in Italy. Digital Journalism, 7(9), 1230–1252. https://doi.org/10.1080/21670811.2019.1657778
  • Schunk, D. H. (2001). Social cognitive theory and self-regulated learning. In Self-regulated learning and academic achievement. Routledge.
  • Simons, M., Tiffen, R., Hendrie, D., Carson, A., Sullivan, H., Muller, D., & McNair, B. (2017). Understanding the civic impact of journalism: A realistic evaluation perspective. Journalism Studies, 18(11), 1400–1414. https://doi.org/10.1080/1461670X.2015.1129284
  • Snoussi, T. (2019). ‘ICT faculties’ usage in the UAE private universities: A case study. Global Media Journal, 17(33), 1–8.
  • Stalph, F. (2018). Classifying data journalism. Journalism Practice, 12(10), 1332–1350. https://doi.org/10.1080/17512786.2017.1386583
  • Stalph, F., Thurman, N., & Thäsler-Kordonouri, S. (2024). Exploring audience perceptions of, and preferences for, data-driven ‘quantitative’ journalism. Journalism, 25(7), 1460–1480. https://doi.org/10.1177/14648849231179606
  • Tahat, K., Mansoori, A., Tahat, D., Qablan, A., & Haddad, I. (2024). Analyzing the newspapers’ coverage of sustainable development goals in UAE. Online Journal of Communication and Media Technologies, 14(3), Article e202439. https://doi.org/10.30935/ojcmt/14710
  • Thakkar, J. J. (2020). Structural equation modelling: Application for research and practice (with AMOS and R). Springer. https://doi.org/10.1007/978-981-15-3793-6
  • Thorsen, E. (2019). Surveillance of journalists/encryption issues. In The international encyclopedia of journalism studies (pp. 1–7). Wiley. https://doi.org/10.1002/9781118841570.iejs0272
  • Treadwell, G., Ross, T., Lee, A., & Lowenstein, J. K. (2016). A numbers game: Two case studies in teaching data journalism. Journalism & Mass Communication Educator, 71(3), 297–308. https://doi.org/10.1177/1077695816665215
  • Túñez-López, J. M., Toural-Bran, C., & Frazão-Nogueira, A. G. (2020). From data journalism to robotic journalism: The automation of news processing. In J. Vázquez-Herrero, S. Direito-Rebollal, A. Silva-Rodríguez, & X. López-García (Eds.), Journalistic metamorphosis: Media transformation in the digital age (pp. 17–28). Springer. https://doi.org/10.1007/978-3-030-36315-4_2
  • Voorhees, C. M. (2016). Discriminant validity testing in marketing: An analysis, causes for concern, and proposed remedies. Journal of the Academy of Marketing Science, 44, 119–134. https://doi.org/10.1007/s11747-015-0455-4
  • Warnes, S. (2018). What’s visual “encoding” in data viz, and why is it important?’ Medium. https://medium.com/@sophiewarnes/whats-visual-encoding-in-data-viz-and-why-is-it-important-7406bc88b4b4
  • Weber, W., Engebretsen, M., & Kennedy, H. (2018). Data stories. Rethinking journalistic storytelling in the context of data journalism. Studies in Communication Sciences, 18(1), 191–206. https://doi.org/10.24434/j.scoms.2018.01.013
  • Westlund, O., & Hermida, A. (2021). Data journalism and misinformation. In H. Tumber, & S. Waisbord (Eds.), The Routledge companion to media disinformation and populism. Routledge. https://doi.org/10.4324/9781003004431-16
  • Willnat, L., Weaver, D. H., & Wilhoit, G. C. (2019). The American journalist in the digital age: How journalists and the public think about journalism in the United States. Journalism Studies, 20(3), 423–441. https://doi.org/10.1080/1461670X.2017.1387071
  • Young, M. L. (2017). What makes for great data journalism?: A content analysis of data journalism awards finalists 2012-2015. Journalism Practice, 12(1), 115–135. https://doi.org/10.1080/17512786.2016.1270171
  • Zhang, S., & Feng, J. (2019). A step forward? Journalism Studies, 20(9), 1281–1300. https://doi.org/10.1080/1461670X.2018.1513814