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Tag 1.0.1
Committed At 2018-08-24 21:11:17 UTC




    elm-sentiment is an Elm module that uses the AFINN-111 wordlist to perform sentiment analysis on arbitrary blocks of input text. Other wordlists are easy to integrate.

    It is inspired by the the Sentiment-module for Node.js.

    Please note that a wordlist-based approach for sentiment analysis might not be the best available approach for every (your) application. It is a simple and easy to use solution that does not need training like a Bayes classifier, that might perform better in classifying sentiments.


    elm package install ggb/elm-sentiment


    Usage is straightforward:

    import Sentiment
    tweet = """
    #StarWars fans are the best kind of people. 
    I'm so, so lucky & honored to get to hang 
    out with you at Celebration. Thank you for 
    being you.
    Sentiment.analyse tweet
    -- Result:
    -- { tokens = ["starwars","fans","are","the","best", ... ,"for","being","you"]
    -- , score = 12
    -- , words = ["best","kind","lucky","honored","thank"]
    -- , positive = [3,2,3,2,2]
    -- , negative = []
    -- , comparative = 0.42857142857142855 
    -- }

    For more advanced usage please take a look at the function-level documentation and especially at the analyseWith-function.


    There are lots of possibilities to improve the current module. Some ideas:

    • handling of negations
    • more and different word lists
    • compression of word lists
    • possibility to train a model (word list as fallback or support)