Sentiment analysis is a popular technique in text mining that attempts to determine the emotional state of some text. We provide a new implementation of a common method for computing sentiment, whereby words are scored as positive or negative according to a dictionary lookup. Then the sum of those scores is returned for the document. We use the 'Hu' and 'Liu' sentiment dictionary ('Hu' and 'Liu', 2004) <doi:10.1145/1014052.1014073> for determining sentiment. The scoring function is 'vectorized' by document, and scores for multiple documents are computed in parallel via 'OpenMP'.
|Author||Drew Schmidt [aut, cre]|
|Maintainer||Drew Schmidt <firstname.lastname@example.org>|
|License||BSD 2-clause License + file LICENSE|
|Package repository||View on CRAN|
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