Evaluation of Policy Making in Russell Group Universities Employing AI-driven NLP Method
Year: 2024
Type: article
Abstract: This study explores how Russell Group universities can evaluate their policymaking and strategic decisions by employing AI-driven Natural Language Processing (NLP) methods. Through a large-scale case study based on social media data during the COVID-19 pandemic, the research assesses how university policies-particularly those related to governance, crisis management, and higher education-impact institutional reputation and stakeholder engagement. By leveraging computational social science and machine learning algorithms to detect patterns in public sentiment and stakeholder behavior, the study demonstrates how AI can enhance policy and decision-making within the higher education sector. Additionally, the study sheds light on AI’s role in promoting transparency, accountability, and effective reputation management, positioning the Russell Group as a key player in shaping the future of global academia.
Author: Homa Molavi
Institution: University of Manchester
Language: English
Subfield: Communication
Field: Social Sciences
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4412385250