The Text Metrics Vector was built to provide the ability to analyze text on your website. It is useful for learning more about comments, reviews, blog posts, etc. It provides data such as sentiment, processed versions of the given text, and word frequencies. This Vector utilizes the "sentiment" node module to provide sentiment information on arbitrary blocks of text. It is based on the AFINN-165 Wordlist, and allows the vector to score provided text as well as highlight positive and negative words in the text. The "stopword" node module is also used to remove stopwords, such as "a", "the", and "what", from the provided text to allow for more accurate analysis. This module even supports stopword removal for multiple languages. To learn more about how and when to use this vector, see here: https://medium.com/@velocity360/text-metrics-vector-7da5cb6cec37 To view the source code for this vector, see here: https://github.com/Turbo-360/text-metrics
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