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nunoachenriques / vader-sentiment-analysis

Java port of Python NLTK sentiment VADER module. VADER (Valence Aware Dictionary and sEntiment Reasoner) is a lexicon and rule-based sentiment analysis tool that is specifically attuned to sentiments expressed in social media, and works well on texts from other domains.
Apache License 2.0
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java lexicon sentiment-analysis sentiment-polarity vader

readme

VADER Sentiment Analysis in Java

VADER (Valence Aware Dictionary and sEntiment Reasoner) is a lexicon and rule-based sentiment analysis tool that is specifically attuned to sentiments expressed in social media.

This is an implementation of the VADER in Java. It started as a fork of the Java port by Animesh Pandey of the NLTK VADER sentiment analysis module written in Python (NLTK VADER source code) from the original project by the paper's author C.J. Hutto. It's the same algorithm as an improved tool by extensive rewriting with relevant changes:

In progress

Repository

https://github.com/nunoachenriques/vader-sentiment-analysis

Citation

If you use either the data set or any of the VADER sentiment analysis tools (VADER sentiment lexicon or Python code for rule-based sentiment analysis engine) in your research, please cite the original paper:

Hutto, C. J., & Gilbert, E. (2014). VADER: A Parsimonious Rule-based Model for Sentiment Analysis of Social Media Text. In Proceedings of the Eighth International AAAI Conference on Weblogs and Social Media (pp. 216–225). Ann Arbor, Michigan, USA.

Retrieved from http://comp.social.gatech.edu/papers/icwsm14.vader.hutto.pdf

Install

From release

https://github.com/nunoachenriques/vader-sentiment-analysis/releases

From source code

  1. Get the code from the repository (clone or download).

  2. Change to the package root directory and ./gradlew installDist. NOTICE: check Troubleshooting for Java version 1.7 compatibility.

  3. The JAR packages will be in build/install/vader-sentiment-analysis directory.

Testing

All tests are 100% OK as expected!

./gradlew test

Languages

To support several languages there's the Language interface (text subpackage) to be implemented and, eventually, the Tokenizer too. The main effort will be in all the research around the specific language significant words, idiomatic expressions, constant and empirical values. Moreover, a data set has to be produced and validated by humans as ground truth for testing purposes.

English (Germanic family of languages)

The tests from the original Java port are validated against the ground truth of the original Python (NLTK) implementation. The algorithm running is still the original implementation from Hutto & Gilbert in Python and originally ported to Java by Animesh Pandey with modifications by Nuno A. C. Henriques.

Portuguese (Italic family of languages)

TODO

Use case example

As a Java library it will easily integrate with a bit of coding.

...
List<String> sentences = new LinkedList<>() {{
    add("VADER is smart, handsome, and funny.");
    add("VADER is smart, handsome, and funny!");
    add("VADER is very smart, handsome, and funny.");
    add("VADER is VERY SMART, handsome, and FUNNY.");
    add("VADER is VERY SMART, handsome, and FUNNY!!!");
    add("VADER is VERY SMART, really handsome, and INCREDIBLY FUNNY!!!");
    add("The book was good.");
    add("The book was kind of good.");
    add("The plot was good, but the characters are uncompelling and the dialog is not great.");
    add("A really bad, horrible book.");
    add("At least it isn't a horrible book.");
    add(":) and :D");
    add("");
    add("Today sux");
    add("Today sux!");
    add("Today SUX!");
    add("Today kinda sux! But I'll get by, lol");
}};

SentimentAnalysis sa = new SentimentAnalysis(new TokenizerEnglish(), new English());

for (String sentence : sentences) {
    System.out.println(sentence);
    System.out.println(sa.getSentimentAnalysis(sentence).toString());
}
...

Documentation

From release

https://github.com/nunoachenriques/vader-sentiment-analysis/releases

From source code

  1. Get the code from the repository (clone or download).

  2. Change to the package root directory and ./gradlew javadoc. NOTICE: check Troubleshooting for Java version 1.7 compatibility.

  3. The docs will be in build/docs/javadoc directory.

Troubleshooting

Java 1.7 compatibility

  1. Install OpenJDK 7.
  2. Suffix Gradle command-line with -Dorg.gradle.java.home=/path_to_jdk_7 such as (Debian GNU/Linux):
./gradlew test -Dorg.gradle.java.home=/usr/lib/jvm/java-7-openjdk-amd64/

License

Copyright 2017 Nuno A. C. Henriques [http://nunoachenriques.net/]

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.