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 API that provides a simple and intuitive way to perform sentiment analysis on text data. It uses a set of rules to determine the sentiment of text, and can handle a wide range of languages.

2. **VADER (Valence Aware Dictionary and sEntiment Reasoner)**: A popular sentiment analysis tool developed by Social Intelligence that uses a combination of natural language processing (NLP) and machine learning algorithms to determine the sentiment of text. It is particularly effective at handling complex and nuanced text data.

3. **Stanford CoreNLP**: A Java library for NLP that provides a wide range of tools for sentiment analysis, including named entity recognition, part-of-speech tagging, and sentiment analysis. It is widely used in academic and industry settings, and is known for its accuracy and reliability.

These tools can be used to analyze text data, such as social media posts, reviews, and customer feedback, to determine the sentiment of the text.