Difference between revisions of "Automatically Detecting Corresponding Edit-Turn-Pairs in Wikipedia"
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| − | '''Automatically Detecting Corresponding Edit-Turn-Pairs in Wikipedia''' - scientific work related to Wikipedia quality published in 2014, written by Johannes Daxenberger and Iryna Gurevych. | + | '''Automatically Detecting Corresponding Edit-Turn-Pairs in Wikipedia''' - scientific work related to [[Wikipedia quality]] published in 2014, written by [[Johannes Daxenberger]] and [[Iryna Gurevych]]. |
== Overview == | == Overview == | ||
| − | In this study, authors analyze links between edits in Wikipedia articles and turns from their discussion page. Authors 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, authors have defined constraints for corresponding edit-turn-pairs. Authors manually annotated a corpus of 636 corresponding and non-corresponding edit-turn-pairs. Furthermore, authors show how data can be used to automatically identify corresponding edit-turn-pairs. With the help of supervised machine learning, authors achieve an accuracy of .87 for this task. | + | In this study, authors analyze links between edits in [[Wikipedia]] articles and turns from their discussion page. Authors 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, authors have defined constraints for corresponding edit-turn-pairs. Authors manually annotated a corpus of 636 corresponding and non-corresponding edit-turn-pairs. Furthermore, authors show how data can be used to automatically identify corresponding edit-turn-pairs. With the help of supervised machine learning, authors achieve an accuracy of .87 for this task. |
Revision as of 08:58, 19 January 2020
Automatically Detecting Corresponding Edit-Turn-Pairs in Wikipedia - scientific work related to Wikipedia quality published in 2014, written by Johannes Daxenberger and Iryna Gurevych.
Overview
In this study, authors analyze links between edits in Wikipedia articles and turns from their discussion page. Authors 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, authors have defined constraints for corresponding edit-turn-pairs. Authors manually annotated a corpus of 636 corresponding and non-corresponding edit-turn-pairs. Furthermore, authors show how data can be used to automatically identify corresponding edit-turn-pairs. With the help of supervised machine learning, authors achieve an accuracy of .87 for this task.
