Naive-Bayes for Sentiment Classification

A lexicon is the vocabulary of a language or branch of knowledge (such as nautical or medical). In linguistics, a lexicon is a language's inventory of lexemes. The word lexicon derives from Greek word λεξικόν (lexikon), neuter of λεξικός (lexikos) meaning 'of or for words'.[1] Linguistic theories generally regard human languages as consisting of two parts: a lexicon, essentially a catalogue of a language's words (its wordstock); and a grammar, a system of rules which allow for the combination of those words into meaningful sentences. The lexicon is also thought to include bound morphemes, which cannot stand alone as words (such as most affixes).[2] In some analyses, compound words and certain classes of idiomatic expressions, collocations and other phrases are also considered to be part of the lexicon. Dictionaries represent attempts at listing, in alphabetical order, the lexicon of a given language; usually, however, bound morphemes are not included.

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Emotion Lexicons References

A lexicon is the vocabulary of a language or branch of knowledge (such as nautical or medical). In linguistics, a lexicon is a language's inventory of lexemes. The word lexicon derives from Greek word λεξικόν (lexikon), neuter of λεξικός (lexikos) meaning 'of or for words'.[1] Linguistic theories generally regard human languages as consisting of two parts: a lexicon, essentially a catalogue of a language's words (its wordstock); and a grammar, a system of rules which allow for the combination of those words into meaningful sentences. The lexicon is also thought to include bound morphemes, which cannot stand alone as words (such as most affixes).[2] In some analyses, compound words and certain classes of idiomatic expressions, collocations and other phrases are also considered to be part of the lexicon. Dictionaries represent attempts at listing, in alphabetical order, the lexicon of a given language; usually, however, bound morphemes are not included.

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Lexicon-based Emotion analysis from text tool for series/movie subtitles, books, etc

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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:

1. Via lexicon-based word matching, which is quite straightforward and examples of its usage are described below.
2. 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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NEXT:

https://githubmemory.com/repo/glhuilli/limbic

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