A Review of Trends and Challenges in Adopting AI Models through Cross-Lingual Transfer Learning via Sentiment Analysis

This study presents a comprehensive examination of the most recent developments and challenges related to implementing artificial intelligence models for sentiment analysis using cross-lingual transfer learning techniques. This paper aims to provide an overview of the historical context and theoretical foundations of sentiment analysis, cross-lingual transfer learning, and the significance of Artificial Intelligence (AI) models. It will also discuss the latest advancements and cutting-edge methodologies in these domains. In addition, we engage in examine research methods, establishing assessment criteria, identifying developing trends, and the identification of persistent issues. Furthermore, we explore the implications of cross-lingual sentiment analysis across many fields.