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 used for sentiment analysis:

1. **TextBlob**: A free, open-source tool that uses a set of simple rules to determine the sentiment of text. It can analyze text in multiple languages and is known for its simplicity and ease of use.

2. **NLTK (Natural Language Toolkit)**: A comprehensive library for natural language processing tasks, including sentiment analysis. It provides tools for tokenization, stemming, and sentiment analysis, and can be used with a variety of languages.

3. **VADER (Valence Aware Dictionary and sEntiment Reasoner)**: A popular sentiment analysis tool developed by Microsoft Research. It uses a dictionary-based approach to analyze the sentiment of text, and is known for its high accuracy and flexibility.