Abstract: Sentiment analysis, also known as opinion mining, is an important part of natural language processing (NLP) that automatically detects the polarity of a text and classifies it as positive, negative or neutral. With the rise of user-generated content on the Internet, opinion polls have become extremely popular in recent years. Consumers increasingly rely on user reviews and online chats to make purchasing decisions, making sentiment analysis an important tool for businesses and marketers. This paper provides a comprehensive overview of sentiment analysis techniques, methods and challenges. By exploring techniques such as sentiment classification, feature-based classification, and addressing negative processing, the paper provides an overview of the current state of sentiment analysis research. The study highlights the importance of sentiment analysis in various fields, including marketing, forecasting customer preferences and financial research, facilitating the extraction and interpretation of subjective information from raw data sources.
Keywords: Sentiment analysis, opinion mining, natural language processing (NLP), user-generated content, sentiment classification, marketing.
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DOI:
10.17148/IJARCCE.2024.13662
