The Impact of Artificial Intelligence on Sentiment Analysis and Virtual Assistants

Sentiment analysis (SA), a critical technique for interpreting and classifying emotions in textual data, finds significant application in enhancing virtual assistants (VA), enabling them to understand and respond to user emotions effectively and contextually. This paper systematically reviews the evolutions of artificial intelligence (AI) and machine learning (ML) in transforming intelligent communication. Focusing on SA and VAs, this paper presents an in-depth analysis of the essential applications, advancements, and challenges in these fields. Our review covers the progression from early public opinion studies and primitive chatbots to today's state-of-the-art deep learning systems. Furthermore, we provide a comparative analysis of current methodologies, highlighting how integrated AI approaches can deliver more efficient, context-aware, and adaptive communication solutions. Our unique contribution lies in bridging the traditionally separate domains of SA and VAs, offering researchers a unified framework to develop more empathetic and adaptive assistants. The insights from this cross-domain analysis particularly advance applications in mental health support, personalized services, and accessible interfaces, pushing the boundaries of intelligent communication systems.