Handling stakeholders’ Cognitive and Metacognitive Interaction Behaviour in Social Media as a Novel Unstructured Data Source: Contribution of Machine Learning

This research explores the evolving dynamics of stakeholder interactions in the context of higher education institutions (HEIs), particularly in the face of transformative changes triggered by the COVID-19 pandemic. The strategies of response to emergencies and crises shape the international reputation of HEIs. Crisis and its consequences can be managed through communication and controlled by data analytics. It delves into the shift from traditional university governance structures to stakeholder-driven models and emphasizes the critical role of crisis management. The focus then turns to the inadequacy of educational institutions in adapting to 21st-century learning, exacerbated by the governance challenges posed by the pandemic. The overarching research question guides the exploration of how organizations can leverage digital technology, particularly ML, to shape positive stakeholder interactions. The literature review examines the transformation of stakeholder interactions, unveiling the role of both cognition and metacognition in shaping perceptions and behaviours presenting a novel data source for understanding organizational dynamics. The study proposes that stakeholders with advanced metacognitive abilities exhibit intelligent behaviour instead of actual behaviour, impacting corporate reputation perception. The research methodology outlines the challenges of handling vast, unstructured datasets and employs a multi-layer stacking ensemble technique, combining various base models, to predict stakeholders’ sentiments and behaviours. The study contributes to the understanding of the complex interplay between organizations and stakeholders in the digital age, offering insights into leveraging technological advancements for positive stakeholders’ interactions.