https://github.com/nicbet/sentiment-analysis-java

Domain-independent sentiment analysis via AFINN and SentiNet 3.0, written in Java
https://github.com/nicbet/sentiment-analysis-java

Last synced: 13 days ago
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Domain-independent sentiment analysis via AFINN and SentiNet 3.0, written in Java

• Host: GitHub
• URL: https://github.com/nicbet/sentiment-analysis-java
• Owner: nicbet
• License: gpl-3.0
• Archived: true
• Created: 2018-11-10T20:01:57.000Z (about 6 years ago)
• Default Branch: master
• Last Pushed: 2018-11-10T20:11:47.000Z (about 6 years ago)
• Last Synced: 2024-11-06T15:12:49.262Z (13 days ago)
• Language: Java
• Size: 4.4 MB
• Stars: 0
• Watchers: 2
• Forks: 2
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# sentiment-analysis-java

Example implementation of AFINN and SentiNet 3.0 sentiment analysis.

## Usage

- Build with gradle.

- Run the `App` main file with passing in a string to obtain AFINN and SentiNet3 scores.

## Example

Calculate sentiment for a fictitious product review:

```sh

./gradlew run --args="'The product works really well. Does it exaclty what it says, well worth the price. Quality could be better.'"

> Task :run

AFINN SCORE: 4

SWN SCORE: 0.21629727936297283

BUILD SUCCESSFUL in 1s

2 actionable tasks: 1 executed, 1 up-to-date

```

## AFINN

Implements AFINN-111.

AFINN is a list of English words rated for valence with an integer

between minus five (negative) and plus five (positive). The words have

been manually labeled by Finn Årup Nielsen in 2009-2011. The file

is tab-separated. There are two versions:

AFINN-111: Newest version with 2477 words and phrases.

## SentiNet 3.0

Sentiment scores are between -1 and 1, greater than 0 for positive and less than 0 for negative.

Dictionary-based sentiment analysis does not perform as well as a trained classifier, but it is domain-independent, based on a priori knowledge of words' sentiment values.

The class handles negations and multiword expressions.

## Credits

AFINN: http://www2.imm.dtu.dk/pubdb/views/publication_details.php?id=6010

SentiNet 3.0: http://nmis.isti.cnr.it/sebastiani/Publications/LREC10.pdf