Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

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

Version 1 : Received: 30 April 2021 / Approved: 5 May 2021 / Online: 5 May 2021 (12:28:53 CEST)

A peer-reviewed article of this Preprint also exists.

Balalaa, M.S.; Mabrouk, A.B.; Abdessalem, H. A Wavelet-Based Method for the Impact of Social Media on the Economic Situation: The Saudi Arabia 2030-Vision Case. Mathematics 2021, 9, 1117. Balalaa, M.S.; Mabrouk, A.B.; Abdessalem, H. A Wavelet-Based Method for the Impact of Social Media on the Economic Situation: The Saudi Arabia 2030-Vision Case. Mathematics 2021, 9, 1117.

Journal reference: Mathematics 2021, 9, 1117
DOI: 10.3390/math9101117

Abstract

In the present paper, we propose a wavelet method to study the impact of electronic media on economic situations. We precisely apply wavelet techniques versus classical methods to analyze economic indices in the market. The technique consists firstly in 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 tables subject finally to correspondence analysis before and after thresholding. As a case of study, we are empirically concerned with the 2030 KSA vision in electronic and social media. Effects of the electronic media texts about the trading 2030 Vision on the Saudi and global economy have 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 future GCC markets situation and thus may be a basis for investors’ decisions in such markets.

Subject Areas

Textual analysis; Media; Correspondence analysis; Wavelet thresholding; KSA-2030 Vision

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