Summary:
- This article discusses the use of Natural Language Processing (NLP) for sentiment analysis, which is the process of determining the emotional tone or attitude expressed in a piece of text.
- The article highlights 7 key challenges that can make sentiment analysis difficult, such as handling sarcasm, understanding context, and dealing with multilingual data.
- It explains how these challenges can be addressed using various NLP techniques, such as machine learning algorithms, lexicon-based approaches, and hybrid methods, to improve the accuracy and reliability of sentiment analysis.