Article citationsMore>>

Cheng, Y., Sun, J. and Zhang, Y. (2019) A Taxonomy of Machine Learning Techniques for Crisis Communication Research. International Journal of Strategic Communication, 13, 421-438.

has been cited by the following article:

• TITLE: Leveraging Predictive Analytics for Strategic Corporate Communications: Enhancing Stakeholder Engagement and Crisis Management

  AUTHORS: Natalie Nkembuh

  KEYWORDS: Predictive Analytics, Corporate Communications, Stakeholder Engagement, Crisis Management, Machine Learning, Data-Driven Strategy, Ethical AI, Digital Transformation, Reputation Management, Strategic Communication

  JOURNAL NAME: Journal of Computer and Communications, Vol.12 No.10, October 18, 2024

  ABSTRACT: This study explores the integration of predictive analytics in strategic corporate communications, with a specific focus on stakeholder engagement and crisis management. Our mixed-methods approach, which combines a comprehensive literature review with case studies of five multinational corporations, allows us to investigate the applications, challenges, and ethical implications of leveraging predictive models in communication strategies. While our findings reveal significant potential for enhancing personalized content delivery, real-time sentiment analysis, and proactive crisis management, we stress the need for careful consideration of challenges such as data privacy concerns and algorithmic bias. This emphasis on ethical implementation is crucial in navigating the complex landscape of predictive analytics in corporate communications. To address these issues, we propose a framework that prioritizes ethical considerations. Furthermore, we identify key areas for future research, thereby contributing to the evolving field of data-driven communication management.