Three tools used for sentiment analysis are Lexalytics, OpinionFinder, and Google Cloud Natural Language. Lexalytics uses statistical language models and machine learning algorithms to identify sentiment in large-scale text data. OpinionFinder is a text mining tool designed to detect sentiment in web-based text data. Google Cloud Natural Language is a cloud-based platform that uses natural language processing and machine learning to analyze sentiment in text.
Below is an instruction that describes a task. Write a response that appropriately completes the request.

### Instruction:
Name three tools used for sentiment analysis

### Response:
Three tools used for sentiment analysis are Lexalytics, OpinionFinder, and Google Cloud Natural Language. Lexalytics uses statistical language models and machine learning algorithms to identify sentiment in large-scale text data. OpinionFinder is a text mining tool designed to detect sentiment in web-based text data. Google Cloud Natural Language is a cloud-based platform that uses natural language processing and machine learning to analyze sentiment in text.
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Here are three tools commonly used for sentiment analysis:

1. **Natural Language Processing (NLP) Libraries**: 
   - NLTK (Natural Language Toolkit) in Python
   - spaCy in Python
   - Stanford CoreNLP in Java

2. **Text Analysis Tools**:
   - TextBlob in Python
   - VADER (Valence Aware Dictionary and sEntiment Reasoner) in Python
   - Lexicon (also known as Sentiment Lexicon) in Python

3. **Machine Learning Libraries**:
   - scikit-learn in Python
   - TensorFlow in Python
   - PyTorch in Python