Senti4SD

Senti4SD is an emotion polarity classifier specifically trained to support sentiment analysis in developers' communication channels. Senti4SD is trained and evaluated on a gold standard of over 4K posts extracted from Stack Overflow.

Fair Use Policy

Please, cite the following paper if you intend to use our tool for your own research:

F. Calefato, F. Lanubile, F. Maiorano N. Novielli. “Sentiment Polarity Detection for Software Development”, to appear in Empirical Software Engineering, DOI: 10.1007/s10664-017-9546-9

NOTE: You will need to install Git LFS extension to check out this project. Once installed and initialized, simply run:

$ git lfs clone https://github.com/collab-uniba/Senti4SD.git

How do I get set up?

To set up the tool, simply run the following script from the command line:

$ sh requirements.sh

To run the script you need:

• Java 8
• R

The script will also install, if not already present, three R packages:

• Caret
• LiblineaR
• e1071

Running

To classify your data using Senti4SD, execute the following instruction from the command line:

$ cd ClassificationTask
$ sh classificationTask.sh inputCorpus.csv outputPredictions.csv

where inputCorpus.csv is a file containing the data you want to classify, considering a document for each line, and outputPredictions.csv is where the predictions will be saved. This last parameter is optional, if not present the output of the classification will be saved in a file called predictions.csv.

To see how the tool works, you can execute the following example:

$ cd ClassificationTask
$ sh classificationTask.sh Sample.csv

This will produce as output a csv file called predictions.csv.

Who do I talk to?

• Nicole Novielli, [email protected]
• Fabio Calefato