Emotion Detection and Analysis Techniques Based on NLP
Siyu Yang · Applied and Computational Engineering · 2025
Emotion, as one of the key bridges connecting human society, serves as a central hub for human communication. With the continuous advancement of computer science, the field of artificial intelligence has developed many innovative branches and subfields to help computers understand human language, analyze the emotions and sentiments embedded within it, and make decisions and judgments. This technology has been applied across various domains, playing practical and significant roles, greatly benefiting human daily life and scientific exploration. Over the past two decades, natural language processing (NLP) has achieved remarkable progress, demonstrated extensive potential and contributed significantly to numerous areas. Emotions hold profound significance and impact on human life and social relationships. As an essential subfield of NLP, sentiment analysis and emotion detection have found broad applications in multiple domains. Despite the rapid development of sentiment analysis technologies, their applications still face many challenges. This paper explores the practical value and future prospects of sentiment analysis and emotion detection, reviews their currently employed methods and technological advancements, and focuses on analyzing existing issues while discussing their causes and potential solutions.