EMTk -- The Emotion Mining Toolkit
Fabio Calefato, Filippo Lanubile, Nicole Novielli, Luigi Quaranta
TL;DR
EMTk is a multi-language toolkit that enhances emotion and sentiment mining from developer communication, offering significant speed improvements over previous standalone tools.
Contribution
It introduces a comprehensive, multi-language toolkit with improved performance and benchmarks for emotion and sentiment analysis in technical texts.
Findings
Significant speed improvements over previous tools
Effective emotion and sentiment analysis in developer communication
Open source availability under MIT license
Abstract
The Emotion Mining Toolkit (EMTk) is a suite of modules and datasets offering a comprehensive solution for mining sentiment and emotions from technical text contributed by developers on communication channels. The toolkit is written in Java, Python, and R, and is released under the MIT open source license. In this paper, we describe its architecture and the benchmark against the previous, standalone versions of our sentiment analysis tools. Results show large improvements in terms of speed.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.