Análise de Sentimentos Aplicada ao Marketing e Comportamento do Consumidor

Abstract Sentiment analysis, driven by advances in artificial intelligence (AI), natural language processing (NLP), and machine learning, has become a strategic tool for contemporary marketing. This article reviews the state of the art regarding the use of sentiment analysis to understand consumer behavior, monitor brand perception, and support real-time marketing decisions. Based on a critical review of recent literature, including conceptual studies, systematic reviews, and applied research, the paper discusses key methodologies, practical applications, ethical challenges, and emerging trends. It highlights how sentiment analysis, by processing large volumes of textual data from social media, online reviews, and digital interactions, enables the identification of emotional patterns, crisis anticipation, campaign personalization, and the strengthening of relationships between brands and consumers. The article also addresses use cases such as digital brand equity monitoring, AI-driven marketing automation, and the role of neural networks in opinion mining. Finally, it discusses the need for ethical and integrated approaches to ensure consumer privacy and trust, while suggesting future directions for research and practice. Keywords: Sentiment Analysis, Artificial Intelligence, Digital Marketing, Consumer Behavior