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Introduction
The objective of this package is simple: If you need to compute some emotion analysis on a word or a set of words this should be able to help. For now, it only supports plain text and subtitles, but the idea is to extend it to other formats (pdf, email, among other formats). In the meantime, this includes a basic example on how to use it on plain text and another example on how to use it in a collection of subtitles for series (all episodes for all seasons of a show). The name of the package is based on the limbic system <https://en.wikipedia.org/wiki/Limbic_system>__, which is a set of brain structures that support different functions, like emotions or behavior among others.
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There are two strategies to compute the emotions from text supported right now:
- Via lexicon-based word matching, which is quite straightforward and examples of its usage are described below.
- Via a multi-label machine learning classifier trained with the specific purpose of identifying emotions and their strength in full sentences.
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Limbic also has a set of tools that are easy to reuse and extend for different use cases. For example, contains tools for the analysis of subtitles in a show, but can be easily extended to analyze books, papers, websites, customer reviews, or even further applications like comparing a movie script with its book, comparing properties of movies in a sequel, among others.
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