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- What is the best model for sentiment analysis?
- What methods can be used for sentiment analysis?
- Which is the suitable platform for sentiment analysis?
- What is the most accurate explanation of sentiment analysis?
What is the best model for sentiment analysis?
Logistic regression is a good model because it trains quickly even on large datasets and provides very robust results. Other good model choices include SVMs, Random Forests, and Naive Bayes.
What methods can be used for sentiment analysis?
Sentiment analysis uses machine learning and natural language processing (NLP) to identify whether a text is negative, positive, or neutral. The two main approaches are rule-based and automated sentiment analysis.
Which is the suitable platform for sentiment analysis?
Sentiment analysis tool provided by Hootsuite Insights helps you understand sentiment behind your brand. The platform will help you mine your customer opinions and share the insights with your team. Social media data will be beneficial in improving your business's bottom line.
What is the most accurate explanation of sentiment analysis?
Sentiment analysis focuses on the polarity of a text (positive, negative, neutral) but it also goes beyond polarity to detect specific feelings and emotions (angry, happy, sad, etc), urgency (urgent, not urgent) and even intentions (interested v. not interested).
