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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'.
| Version: | 0.1-6 |
| Depends: | R (≥ 3.0.0) |
| Published: | 2023-12-10 |
| Author: | Drew Schmidt [aut, cre] |
| Maintainer: | Drew Schmidt <wrathematics at gmail.com> |
| BugReports: | https://github.com/wrathematics/meanr/issues |
| License: | BSD 2-clause License + file LICENSE |
| URL: | https://github.com/wrathematics/meanr |
| NeedsCompilation: | yes |
| Citation: | meanr citation info |
| Materials: | README ChangeLog |
| CRAN checks: | meanr results |
| Reference manual: | meanr.pdf |
| Package source: | meanr_0.1-6.tar.gz |
| Windows binaries: | r-devel: meanr_0.1-6.zip, r-release: meanr_0.1-6.zip, r-oldrel: meanr_0.1-6.zip |
| macOS binaries: | r-release (arm64): meanr_0.1-6.tgz, r-oldrel (arm64): meanr_0.1-6.tgz, r-release (x86_64): meanr_0.1-6.tgz, r-oldrel (x86_64): meanr_0.1-6.tgz |
| Old sources: | meanr archive |
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