IDEAS home Printed from https://ideas.repec.org/a/sae/crmide/v8y2021i1p22-35.html
   My bibliography  Save this article

Methodological Problems of Using Arabic-Language Twitter as a Gauge for Arab Attitudes Toward Politics and Society

Author

Listed:
  • Mujtaba Ali Isani

Abstract

Public opinion research in the Middle Eastern context has seen a proliferation of data research that aims to track changes in the state of Arab attitudes. Yet, it remains unclear what is being measured and how representative the data is. This article aims to address this question by reviewing the extent to which and how the existing literature has addressed the issues of representativeness of Twitter communities and the validity of opinion measures derived from sentiment analysis in the Middle Eastern context. While some studies aim no further than to gauge the dynamics of Twitter debates, many others seek to generalize the larger public opinion trends. This raises questions about how representative Twitter users are of the general public, how asymmetric social media use is, and how participation routines vary. Furthermore, to what extent can sentiment analysis translate individual tweets into meaningful measures of expressed opinion, and how sensitive are means of aggregating opinions from sentiment analysis to variation in terms of tone and amount of text within and across individuals? Following a comprehensive review of existing research in the context of the Middle East, this article also aims to derive a clearer understanding of how collective Twitter opinion relates to public opinion and make some suggestions of ways to design sampling and coding procedures, as well as validation exercises to address measurement bias and error.

Suggested Citation

  • Mujtaba Ali Isani, 2021. "Methodological Problems of Using Arabic-Language Twitter as a Gauge for Arab Attitudes Toward Politics and Society," Contemporary Review of the Middle East, , vol. 8(1), pages 22-35, March.
    • Handle: RePEc:sae:crmide:v:8:y:2021:i:1:p:22-35
    DOI: 10.1177/2347798920976283
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/2347798920976283
    Download Restriction: no
    File URL: https://libkey.io/10.1177/2347798920976283?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Daniel J. Hopkins & Gary King, 2010. "A Method of Automated Nonparametric Content Analysis for Social Science," American Journal of Political Science, John Wiley & Sons, vol. 54(1), pages 229-247, January.
    2. Lucas, Christopher & Nielsen, Richard A. & Roberts, Margaret E. & Stewart, Brandon M. & Storer, Alex & Tingley, Dustin, 2015. "Computer-Assisted Text Analysis for Comparative Politics," Political Analysis, Cambridge University Press, vol. 23(2), pages 254-277, April.
    3. Alexandre Bovet & Hernán A. Makse, 2019. "Influence of fake news in Twitter during the 2016 US presidential election," Nature Communications, Nature, vol. 10(1), pages 1-14, December.
    4. Jean-Eric Aubert & Jean-Louis Reiffers, 2004. "Knowledge Economies in the Middle East and North Africa : Toward New Development Strategies," World Bank Publications - Books, The World Bank Group, number 15037.
    5. Joshua D. Kertzer & Thomas Zeitzoff, 2017. "A Bottom‐Up Theory of Public Opinion about Foreign Policy," American Journal of Political Science, John Wiley & Sons, vol. 61(3), pages 543-558, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Weifeng Zhong, 2016. "The candidates in their own words: A textual analysis of 2016 president primary debates," AEI Economic Perspectives, American Enterprise Institute, April.
    2. Sara Kahn-Nisser, 2019. "When the targets are members and donors: Analyzing inter-governmental organizations’ human rights shaming," The Review of International Organizations, Springer, vol. 14(3), pages 431-451, September.
    3. Sean D. Ehrlich & Christopher Gahagan, 2023. "The Multisided Threat to Free Trade: Protectionism and Fair Trade During Increasing Populism," Politics and Governance, Cogitatio Press, vol. 11(1), pages 223-236.
    4. Plouffe, Michael, 2024. "The Public and the Assembly: Foreign Public Opinion and Voting in the UNGA," OSF Preprints pu2yv_v1, Center for Open Science.
    5. Ciprian-Octavian Truică & Elena-Simona Apostol, 2022. "MisRoBÆRTa: Transformers versus Misinformation," Mathematics, MDPI, vol. 10(4), pages 1-25, February.
    6. Carlos Carrasco-Farré, 2022. "The fingerprints of misinformation: how deceptive content differs from reliable sources in terms of cognitive effort and appeal to emotions," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-18, December.
    7. Dehler-Holland, Joris & Schumacher, Kira & Fichtner, Wolf, 2021. "Topic Modeling Uncovers Shifts in Media Framing of the German Renewable Energy Act," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 2(1).
    8. Maschke, Andreas, 2024. "Talking exports: The representation of Germany's current account in newspaper media," MPIfG Discussion Paper 24/1, Max Planck Institute for the Study of Societies.
    9. Kübler, Raoul V. & Manke, Kai & Pauwels, Koen, 2025. "I like, I share, I vote: Mapping the dynamic system of political marketing," Journal of Business Research, Elsevier, vol. 186(C).
    10. Benjamin E. Bagozzi & Daniel Berliner & Zack W. Almquist, 2021. "When does open government shut? Predicting government responses to citizen information requests," Regulation & Governance, John Wiley & Sons, vol. 15(2), pages 280-297, April.
    11. Uğur Baloğlu, 2021. "Trolls, Pressure and Agenda: The discursive fight on Twitter in Turkey," Media and Communication, Cogitatio Press, vol. 9(4), pages 39-51.
    12. Mohamed M. Mostafa, 2023. "A one-hundred-year structural topic modeling analysis of the knowledge structure of international management research," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(4), pages 3905-3935, August.
    13. Sinziana-Maria Rindasu & Ioan Dan Topor & Liliana Ionescu-Feleaga, 2023. "The Evolution of Management Accountants' Digital Skills in Industry 4.0: A Qualitative Approach," Oblik i finansi, Institute of Accounting and Finance, issue 1, pages 38-48, March.
    14. Giovanni Di Franco & Michele Santurro, 2021. "Machine learning, artificial neural networks and social research," Quality & Quantity: International Journal of Methodology, Springer, vol. 55(3), pages 1007-1025, June.
    15. Prather, Lauren, 2024. "Ideology at the Water’s Edge: Explaining Variation in Public Support for Foreign Aid," World Development, Elsevier, vol. 176(C).
    16. Zhang, Han, 2021. "How Using Machine Learning Classification as a Variable in Regression Leads to Attenuation Bias and What to Do About It," SocArXiv 453jk, Center for Open Science.
    17. Nwaibeh, E.A. & Chikwendu, C.R., 2023. "A deterministic model of the spread of scam rumor and its numerical simulations," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 207(C), pages 111-129.
    18. Dongshu Liu & Li Shao, 2024. "Nationalist propaganda and support for war in an authoritarian context: Evidence from China," Journal of Peace Research, Peace Research Institute Oslo, vol. 61(6), pages 985-1001, November.
    19. Pauwels, Koen & Aksehirli, Zeynep & Lackman, Andrew, 2016. "Like the ad or the brand? Marketing stimulates different electronic word-of-mouth content to drive online and offline performance," International Journal of Research in Marketing, Elsevier, vol. 33(3), pages 639-655.
    20. Aritz Bilbao-Jayo & Aitor Almeida, 2018. "Automatic political discourse analysis with multi-scale convolutional neural networks and contextual data," International Journal of Distributed Sensor Networks, , vol. 14(11), pages 15501477188, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:crmide:v:8:y:2021:i:1:p:22-35. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.