Sentiment analysis, also known as opinion mining, is a subfield of Natural Language Processing (NLP) that focuses on identifying and extracting subjective information from text. It is widely used to determine emotions, attitudes, or opinions expressed in reviews, social media, and customer feedback.
Key Features
- Text Classification: Categorizes text into positive, negative, or neutral sentiments.
- Emotion Detection: Recognizes nuanced emotions like joy, anger, or sadness.
- Aspect-Based Analysis: Analyzes specific aspects of a topic (e.g., product quality, customer service).
- Multilingual Support: Processes text in various languages with accuracy.
Use Cases
- Social Media Monitoring: Track brand reputation and public opinion.
- Customer Feedback Analysis: Automate sentiment extraction from surveys.
- Market Research: Analyze trends and consumer behavior.
- Content Moderation: Filter inappropriate or harmful language.
For deeper insights into NLP techniques, visit our NLP Projects page.