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edu.usc.ir:sentiment-analysis-parser
Advanced tools
Combines Apache OpenNLP and Apache Tika and provides facilities for automatically deriving sentiment from text.
A parser performing sentiment analysis that uses the Apache OpenNLP and Apache Tika libraries to perform text analysis on the the Large Movie Review Dataset. Negative and positive reviews were combined together in a file "result", and each review has a "positive" or a "negative" label before it.
$ cd $HOME/src
$ git clone https://github.com/USCDataScience/SentimentAnalysisParser
$ cd SentimentAnalysisParser
$ mvn install assembly:assembly
$ cd target/sentiment
$ mkdir -p model/org/apache/tika/parser/sentiment/topic/
$ bin/sentiment SentimentTrainer -model model/org/apache/tika/parser/sentiment/topic/en-sentiment.bin -lang en -data ./../../examples/categorical_dataset -encoding UTF-8
The model is written to en-sentiment.bin
Make sure you are in target/sentiment
$ bin/sentiment Tika -model model/org/apache/tika/parser/sentiment/topic/en-sentiment.bin -o ../../examples/gun-output1 -j ../../examples/gun-ads
This project began as the Google Summer of Code 2016 project of Anastasija Mensikova for Apache Software Foundation under the supervision of Chris Mattmann
FAQs
Combines Apache OpenNLP and Apache Tika and provides facilities for automatically deriving sentiment from text.
We found that edu.usc.ir:sentiment-analysis-parser demonstrated a not healthy version release cadence and project activity because the last version was released a year ago. It has 0 open source maintainers collaborating on the project.
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