SentimentAnalysisParser

Combines Apache OpenNLP and Apache Tika and provides facilities for automatically deriving sentiment from text.

License	The Apache License, Version 2.0
GroupId	edu.usc.ir
ArtifactId	sentiment-analysis-parser
Last Version	0.1
Release Date	Jun 8, 2016
Type	jar
Description	SentimentAnalysisParser Combines Apache OpenNLP and Apache Tika and provides facilities for automatically deriving sentiment from text.
Project URL	https://github.com/USCDataScience/SentimentAnalysisParser
Source Code Management	https://github.com/USCDataScience/SentimentAnalysisParser.git

Download sentiment-analysis-parser

Filename	Size
sentiment-analysis-parser-0.1.pom
sentiment-analysis-parser-0.1.jar	28 KB
sentiment-analysis-parser-0.1-sources.jar	22 KB
sentiment-analysis-parser-0.1-javadoc.jar	114 KB

How to add to project

Apache Maven

<!-- https://jarcasting.com/artifacts/edu.usc.ir/sentiment-analysis-parser/ -->
<dependency>
    <groupId>edu.usc.ir</groupId>
    <artifactId>sentiment-analysis-parser</artifactId>
    <version>0.1</version>
</dependency>

Gradle Groovy

// https://jarcasting.com/artifacts/edu.usc.ir/sentiment-analysis-parser/
implementation 'edu.usc.ir:sentiment-analysis-parser:0.1'

Gradle Kotlin

// https://jarcasting.com/artifacts/edu.usc.ir/sentiment-analysis-parser/
implementation ("edu.usc.ir:sentiment-analysis-parser:0.1")

Apache Buildr

'edu.usc.ir:sentiment-analysis-parser:jar:0.1'

Apache Ivy

<dependency org="edu.usc.ir" name="sentiment-analysis-parser" rev="0.1">
  <artifact name="sentiment-analysis-parser" type="jar" />
</dependency>

Groovy Grape

@Grapes(
@Grab(group='edu.usc.ir', module='sentiment-analysis-parser', version='0.1')
)

Scala SBT

libraryDependencies += "edu.usc.ir" % "sentiment-analysis-parser" % "0.1"

Leiningen

[edu.usc.ir/sentiment-analysis-parser "0.1"]

Dependencies

compile (9)

Group / Artifact	Type	Version
org.apache.tika : tika-core	jar	1.13
org.apache.tika : tika-parsers	jar	1.13
org.apache.tika : tika-langdetect	jar	1.13
org.apache.tika : tika-batch	jar	1.13
org.apache.opennlp : opennlp-tools	jar	1.6.0
org.slf4j : slf4j-log4j12	jar	1.7.21
org.slf4j : jul-to-slf4j	jar	1.7.21
org.slf4j : jcl-over-slf4j	jar	1.7.21
log4j : log4j	jar	1.2.17

test (1)

Group / Artifact	Type	Version
junit : junit	jar	4.12

Project Modules

There are no modules declared in this project.

Sentiment Analysis Parser

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.

Use

How to build Sentiment Analysis Parser

$ cd $HOME/src
$ git clone https://github.com/USCDataScience/SentimentAnalysisParser
$ cd SentimentAnalysisParser
$ mvn install assembly:assembly

How to train a model

$ 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

How to run the parser

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

Contributors

• Chris A. Mattmann, JPL
• Anastasija Mensikova, Trinity College, CT

Credits

This project began as the Google Summer of Code 2016 project of Anastasija Mensikova for Apache Software Foundation under the supervision of Chris Mattmann

License

Apache License, version 2

USC Information Retrieval & Data Science

USC Information Retrieval and Data Science Group

Versions

Version
0.1 Jun 8, 2016