A ground-truth dataset and classification model for detecting bots in GitHub issue and PR comments

Published 2021 View Full Article

  1. Home
  2. Publications
  3. Publication Search
  4. Publication Details
Title
A ground-truth dataset and classification model for detecting bots in GitHub issue and PR comments
Authors
Keywords
Distributed software development, Bot identification, GitHub repositories, Text similarity, Classification model
Journal
JOURNAL OF SYSTEMS AND SOFTWARE
Volume -, Issue -, Pages 110911
Publisher
Elsevier BV
Online
2021-01-23
DOI
10.1016/j.jss.2021.110911
References
View 5 related references

Ask authors/readers for more resources

Protocol

Community support

Reagent

Community support

Reprint

Contact the author

Find the ideal target journal for your manuscript

Explore over 38,000 international journals covering a vast array of academic fields.

Search

Add your recorded webinar

Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.

Upload Now
Webinars Posters Questions Hubs Funding Journals Articles Connect Collections Reviewers About Us FAQs Mobile App Privacy Policy Terms of Use
© Peeref 2019-2024. All rights reserved.