Learning from History: Predicting Reverted Work at the Word Level in Wikipedia
Authors | Jeffrey M. Rzeszotarski Aniket Kittur |
|---|---|
Publication date | 2012 |
DOI | 10.1145/2145204.2145272 |
Links | Original |
Learning from History: Predicting Reverted Work at the Word Level in Wikipedia - scientific work related to Wikipedia quality published in 2012, written by Jeffrey M. Rzeszotarski and Aniket Kittur.
Overview
Wikipedia's remarkable success in aggregating millions of contributions can pose a challenge for current editors, whose hard work may be reverted unless they understand and follow established norms, policies, and decisions and avoid contentious or proscribed terms. Authors present a machine learning model for predicting whether a contribution will be reverted based on word level features. Unlike previous models relying on editor-level characteristics, model can make accurate predictions based only on the words a contribution changes. A key advantage of the model is that it can provide feedback on not only whether a contribution is likely to be rejected, but also the particular words that are likely to be controversial, enabling new forms of intelligent interfaces and visualizations. Authors examine the performance of the model across a variety of Wikipedia articles.
Embed
Wikipedia Quality
Rzeszotarski, Jeffrey M.; Kittur, Aniket. (2012). "[[Learning from History: Predicting Reverted Work at the Word Level in Wikipedia]]".DOI: 10.1145/2145204.2145272.
English Wikipedia
{{cite journal |last1=Rzeszotarski |first1=Jeffrey M. |last2=Kittur |first2=Aniket |title=Learning from History: Predicting Reverted Work at the Word Level in Wikipedia |date=2012 |doi=10.1145/2145204.2145272 |url=https://wikipediaquality.com/wiki/Learning_from_History:_Predicting_Reverted_Work_at_the_Word_Level_in_Wikipedia}}
HTML
Rzeszotarski, Jeffrey M.; Kittur, Aniket. (2012). "<a href="https://wikipediaquality.com/wiki/Learning_from_History:_Predicting_Reverted_Work_at_the_Word_Level_in_Wikipedia">Learning from History: Predicting Reverted Work at the Word Level in Wikipedia</a>".DOI: 10.1145/2145204.2145272.
