Automatically detecting corresponding edit-turn-pairs in Wikipedia
In this study, we analyze links between edits in Wikipedia articles and turns from their discussion page.
Our motivation is to better understand implicit details about the writing process and knowledge flow in collaboratively created resources. Based on properties of the involved edit and turn, we have defined constraints for corresponding edit-turn-pairs. We manually annotated a corpus of 636 corresponding and non-corresponding edit-turn-pairs. Furthermore, we show how our data can be used to automatically identify corresponding edit-turn-pairs. With the help of supervised machine learning, we achieve an accuracy of .87 for this task.
Daxenberger, Johannes; Gurevych, Iryna: Automatically detecting corresponding edit-turn-pairs in Wikipedia, in: ACL (ed.): Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics. Short Papers Stroudsburg, PA: Association for Computational Linguistics (2014), 187-192