Demonstrate NLP techniques through the research of Sentiment Analysis using Twitter data
- John Ng (Chair)
- Melanie Zhang
- Arshad Khan
- Claudio Giancaterino
- Neptune Jin
- Zack Chan
What is Sentiment Analysis?
Sentiment analysis, also known as opinion mining or emotion AI, refer to the use of Natural Language Processing (NLP) and text analytics to automatically determine the overall feeling a writer is expressing in a piece of text.
Sentiment classification is often framed as binary (positive/negative), ternary (positive/neutral/negative) or multi-class (for example neutral, happy, sad, anger, hate).
Sentiment analysis is used in many applications:
- Monitor and analyse online and social media content around a specific topic
- Evaluating survey response
- Voice of the customer analysis, leading to value proposition
- Product analytics: e.g. categorising product reviews
- Improve Customer Support and feedback analysis
- Reputation and Brand management
- Market Research, Competitor Analysis