Enhancing Media Convergence with Artificial Intelligence to Stabilize Financial Markets

Authors

  • Haozhong Xue New York University
  • Yanyi Zhong Pepperdine University
  • Jingwen He Washington University in St. Louis

DOI:

https://doi.org/10.70393/616a6e73.323531

ARK:

https://n2t.net/ark:/40704/AJNS.v2n1a01

Disciplines:

Computer Science

Subjects:

Artificial Intelligence

References:

32

Keywords:

Artificial Intelligence (AI), Media Convergence, AIGC (AI-Generated Content), Sentiment Analysis and Fake News Detection

Abstract

This study explores the application of artificial intelligence (AI) technology in media convergence, focusing on how AI is driving deep integration of media and financial markets through big data analytics, AIGC (AI-generated content), and intelligent communication technologies. Ai-driven sentiment analysis and fake news detection tools effectively solve the problem of information asymmetry and the spread of false news in the financial market and promote market stability and transparency. Through personalized recommendations and intelligent communication, AI provides users with a more accurate content experience and improves user engagement and satisfaction. In addition, the rapid development of AIGC and big data ecology has promoted the intellectualization of information dissemination and public opinion analysis, providing more forward-looking support for financial market decision-making.

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Author Biographies

Haozhong Xue, New York University

Tandon School of Engineering, New York University, New York, USA, 11101, hx2341@nyu.edu.

Yanyi Zhong, Pepperdine University

Graziadio Business School, Pepperdine University, Malibu, USA, 90263, yanyi.zhong@alumnimail.pepperdine.edu.

Jingwen He, Washington University in St. Louis

Samfox School of Architecture, Washington University in St. Louis, California, USA, 94608, jingwenhe@wustl.edu.

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Published

2025-01-14

How to Cite

Xue, H., Zhong, Y., & He, J. (2025). Enhancing Media Convergence with Artificial Intelligence to Stabilize Financial Markets. Academic Journal of Natural Science , 2(1), 1–6. https://doi.org/10.70393/616a6e73.323531

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