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README.md

Collab Emotion Mining Toolkit

Table of Contents

About

Download

Programming languages, 3rd party libs, and OS

License

How to cite

About EMTk

The emotion-mining toolkit comprises the following software:

  • EmoTXT - A general-purpose toolkit for training custom emotion classifiers from text. Together with the toolkit, we distribute an emotion classifier specifically tuned for emotion mining from developers' communication channels, tranied using our gold standard of about 5k posts from Stack Overflow
  • Senti4SD - An emotion-polarity classifier specifically trained on technical corpora from developers' communication channels

Choose Collab EMTk if:

  • You need to assess the polarity of technical text snippets (e.g., issue comments) from the software development domain but you don't want to train your own classification model => select Senti4SD
  • You need to classify the emotion expressed in technical text snippets (e.g., commit comments) from the software development domain but you don't want to train your own classification model => use the classification function of EmoTXT.
  • You have a corpus of text from any domain that you intend to use for training your own emotion classifier => use the training function of EmoTXT

Download

EMTk and all other software developed by Collab is available on GitHub. If you don't want to clone the repos, click on any of the buttons below to download directly.

EmoTXT   Senti4SD

Programming languages, 3rd party libs, and OS

Collab EMTk is developed using a mix of Java, Python, R. Hence, it works on Linux, macOS, and Windows. The following 3rd party libraries are also used:

License

Collab EMTk is licensed under the MIT License.

How to cite

If you intend to use the Collab EMTk for your work, please cite the following papers:

@article{calefato2017emse,
 author="Calefato, Fabio and Lanubile, Filippo and Maiorano, Federico and Novielli, Nicole",
 title="Sentiment Polarity Detection for Software Development",
 journal="Empirical Software Engineering",
 year="2017",
 issn="1573-7616",
 doi="10.1007/s10664-017-9546-9",
 url="https://doi.org/10.1007/s10664-017-9546-9"
}
@inproceedings{calefato2017acii,
 title={EmoTxt: A Toolkit for Emotion Recognition from Text},
 author={Calefato, Fabio and Lanubile, Filippo and Novielli, Nicole},
 booktitle = {Proc. of 7th Int'l Conf. on Affective Computing and Intelligent Interaction Workshops and Demos},
 series = {ACII 2017},
 year = {2017},
 isbn = {978-1-5386-0563-9},
 doi = {10.1109/ACIIW.2017.8272591},
 url ={http://doi.ieeecomputersociety.org/10.1109/ACIIW.2017.8272591},
 location = {San Antonio, TX, USA},
 pages = {79--80},
 numpages = {2}
}
@inproceedings{Novielli2018msr,
 title={A Gold Standard for Emotions Annotation in Stack Overflow},
 author={Novielli, Nicole and Calefato, Fabio and Lanubile, Filippo},
 booktitle = {Proc. of 15th Int'l Conf. on Mining Software Repositories},
 series = {MSR 2018},
 year = {2018},
 isbn = {978-1-4503-5716-6/18/05},
 doi = {10.1145/3196398.3196453},
 location = {Gothenburg, Sweden},
 pages = {??--??},
 numpages = {4}
}

Support or Contact

Having trouble with our toolkit? Contact us and we’ll help you sort it out.