@matteocacciola/sentiment
Advanced tools
This library aims to provide a support for the analysis of texts, like the evaluation of Sentiment or Text Matching. Please, consult the various methods here provided in order to have a wide overview of the possible features.
In order to install the library, please use
npm i @matteocacciola/sentiment
The available methods allow to use evaluations of Sentiment and scores by means of predefined strategies, already implemented within this package, or by using a custom and self-implemented Sentiment classifier, e.g. obtained by training suitable Machine Learning structures. If you want to consult possible algorithms you can train, please feel free to be inspired by my Machine Learning codes like Support Vector Machines, Convolutional Neural Network, Multilayer Perceptron Artificial Neural Network, Fuzzy C-means and so forth.
FAQs
Collection of functions for sentiment analysis
The npm package @matteocacciola/sentiment receives a total of 4 weekly downloads. As such, @matteocacciola/sentiment popularity was classified as not popular.
We found that @matteocacciola/sentiment demonstrated a not healthy version release cadence and project activity because the last version was released a year ago. It has 1 open source maintainer collaborating on the project.
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