Digital Media Information Risk and Foreign Direct Investment in GCC Markets: A Wavelet-Denoising and Correspondence-Analysis Approach with Evidence from Saudi Arabia

Digital media has become a central information channel for investors and policymakers, yet the information it provides on foreign direct investment (FDI) is often noisy, uncertain, and fragmented. This study examines the role and impact of digital media on FDI in the Gulf Cooperation Council (GCC) region using a GCC-wide media corpus with Saudi Arabia as the anchor case. Using digital media articles published between 2018 and 2024, we construct a words-by-year contingency table and apply a wavelet-denoising procedure before correspondence analysis. A Daubechies Db12 wavelet at decomposition level 3 is used to separate signal from noise, after which factorial correspondence analysis is performed on the denoised contingency matrix. The results show that wavelet denoising substantially improves the interpretability of the factorial structure: the first two axes explain 97.34% of the total inertia, compared with approximately 70% explained by three axes in the raw data. The denoised analysis reveals distinct temporal patterns, including the initial opening of GCC markets to non-petroleum FDI in 2018, disruption during the COVID-19 pandemic period in 2019–2020, and recovery and expansion in 2021–2024 in sectors such as digital media, finance, tourism, technology, and energy. These findings highlight the value of wavelet-based textual analysis for extracting reliable information from digital media and for supporting FDI risk assessment, market monitoring, and financial decision-making in GCC markets.