| Jeffrey Rzeszotarski|
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|Authorship||Publications (2), datasets (0), tools (0)|
|Citations||Total (0), average (0), median (0), max (0), min (0)|
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Jeffrey Rzeszotarski is an author.
PublicationsOnly those publications related to wikis are shown here.
|Title||Keyword(s)||Published in||Language||DateThis property is a special property in this wiki.||Abstract||R||C|
|Learning from history: Predicting reverted work at the word level in wikipedia||Applied machine learning
|English||2012||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. We 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, our 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. We examine the performance of the model across a variety of Wikipedia articles.||0||0|
|Learning from history: predicting reverted work at the word level in wikipedia||Applied machine learning
|Computer-Supported Cooperative Work||English||2012||0||0|