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.
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.gitTo set up the tool, simply run the following script from the command line:
$ sh requirements.shTo run the script you need:
- Java 8
- R
The script will also install, if not already present, three R packages:
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.
- Nicole Novielli, [email protected]
- Fabio Calefato