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A Wavelet-Based Method for the Impact of Social Media on the Economic Situation: The Saudi Arabia 2030-Vision Case

Author

Listed:
  • Majed S. Balalaa

    (Deanship of Public Relations and Media, University of Tabuk, Tabuk 47512, Saudi Arabia)

  • Anouar Ben Mabrouk

    (Department of Mathematics, Faculty of Science, University of Tabuk, Tabuk 47512, Saudi Arabia
    Department of Mathematics, Higher Institute of Applied Mathematics and Computer Science, University of Kairouan, Kairouan 3100, Tunisia
    Laboratory of Algebra, Number Theory and Nonlinear Analysis, LR18ES15, Department of Mathematics, Faculty of Sciences, University of Monastir, Monastir 5019, Tunisia)

  • Habiba Abdessalem

    (Department of Quantitative Methods, Faculty of Economic Sciences and Management, University of Sousse, Sousse 4023, Tunisia)

Abstract

In the present paper, a wavelet method is proposed to study the impact of electronic media on economic situation. More precisely, wavelet techniques are applied versus classical methods to analyze economic indices in the market. The technique consists firstly of filtering the data from unprecise circumstances (noise) to construct next a wavelet denoised contingency table. Next, a thresholding procedure is applied to such a table to extract the essential information porters. The resulting table subject finally to correspondence analysis before and after thresholding. As a case of study, the KSA 2030-vision is considered in the empirical part based on electronic and social media. Effects of the electronic media texts about the trading 2030 vision on the Saudi and global economy has been studied. Recall that the Saudi market is the most important representative market in the GCC continent. It has both regional and worldwide influence on economies and besides, it is characterized by many political, economic and financial movements such as the worldwide economic NEOM project. The findings provided in the present paper may be applied to predict the future situation of markets in GCC region and may constitute therefore a guide for investors to decide about investing or not in these markets.

Suggested Citation

  • Majed S. Balalaa & Anouar Ben Mabrouk & Habiba Abdessalem, 2021. "A Wavelet-Based Method for the Impact of Social Media on the Economic Situation: The Saudi Arabia 2030-Vision Case," Mathematics, MDPI, vol. 9(10), pages 1-21, May.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:10:p:1117-:d:554763
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    References listed on IDEAS

    as
    1. Ines Kahloul & Anouar Ben Mabrouk & Slah-Eddine Hallara, 2010. "Wavelet-Based Prediction for Governance, Diversification and Value Creation Variables," Papers 1011.5020, arXiv.org.
    2. Christoph Schleicher, 2002. "An Introduction to Wavelets for Economists," Staff Working Papers 02-3, Bank of Canada.
    3. Conlon, T. & Crane, M. & Ruskin, H.J., 2008. "Wavelet multiscale analysis for Hedge Funds: Scaling and strategies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(21), pages 5197-5204.
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    5. Carlo Cattani, 2010. "Fractals and Hidden Symmetries in DNA," Mathematical Problems in Engineering, Hindawi, vol. 2010, pages 1-31, June.
    6. Anouar BenMabrouk & Olfa Zaafrane, 2013. "Wavelet fuzzy hybrid model for physico-financial signals," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(7), pages 1453-1463, July.
    7. Habiba Abdessalem & Saloua Benammou, 2018. "A wavelet technique for the study of economic socio-political situations in a textual analysis framework," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 45(3), pages 586-597, August.
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