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<p>This review is a critical analysis of 29 peer-reviewed articles that investigate the application of Artificial Intelligence (AI) and Natural Language Processing (NLP) innovations to transform financial decision-making using social media data. A systematic review and subsequent study selection was in connection with PRISMA scheme using relevancy to sentiment analysis, predictive modeling, fraud detection, and sustainability in financial ecosystems to select studies between 2021 and 2025. Using unstructured social media data, AI and NLP can greatly improve sentiment analysis, risk forecasting, and personalized financial services. Nevertheless, there are still fears of algorithmic secrecy, data bias, ethical responsibility, and privacy theft. The literature demands explainable AI (XAI), models that are fair, and solid governance structures that can guarantee transparency and trust. The review is a synthesis of developing evidence regarding the potential of AI-NLP to incorporate social media signals into finance to provide insights into sustainable, transparent, and ethical financial innovation.</p>

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A systematic review of Artificial Intelligence and Natural Language Processing applications in social media-based financial ecosystems

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月27日

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  • Sajeel Ahmed,
  • Abira Zaki,
  • Nashat Almasria,
  • Hassan Hamad Hasan Aldboush,
  • Muhammad Raghib Zafar

摘要

This review is a critical analysis of 29 peer-reviewed articles that investigate the application of Artificial Intelligence (AI) and Natural Language Processing (NLP) innovations to transform financial decision-making using social media data. A systematic review and subsequent study selection was in connection with PRISMA scheme using relevancy to sentiment analysis, predictive modeling, fraud detection, and sustainability in financial ecosystems to select studies between 2021 and 2025. Using unstructured social media data, AI and NLP can greatly improve sentiment analysis, risk forecasting, and personalized financial services. Nevertheless, there are still fears of algorithmic secrecy, data bias, ethical responsibility, and privacy theft. The literature demands explainable AI (XAI), models that are fair, and solid governance structures that can guarantee transparency and trust. The review is a synthesis of developing evidence regarding the potential of AI-NLP to incorporate social media signals into finance to provide insights into sustainable, transparent, and ethical financial innovation.