Automatic Identification of Rollback Edit with Reasons in Stack Overflow Q&A Site

Crowd-sourced developer forums, such as Stack Overflow (SO), rely on edits from users to improve the quality of the shared knowledge. Unfortunately, suggested edits in SO are frequently rejected by rollbacks due to undesired edits or violation of editing guidelines. Such rollbacks could frustrate and demotivate users to provide future suggestions. We thus need to warn a user of a potential rollback so that he can improve the suggested edit and thus increase its likelihood of acceptance. This study proposes to help users with an automated machine learning classification model that can warn them of potential rollbacks to their suggested edits. We present the conceptual design of EditEx, an online tool that can guide SO users during their editing by highlighting the potential causes of rollback. We offer details of an empirical study to assess the accuracy of the classifiers and a user study to evaluate the effectiveness of EditEx.