TL;DR
This paper introduces a simple, general model to predict whether an edit in peer-production systems like Wikipedia and Linux kernel will survive, based on who made the edit and the nature of the component affected.
Contribution
The paper proposes a novel, content-independent model for predicting edit survival that outperforms reputation-based methods and approaches specialized content-based predictors.
Findings
Model accurately predicts edit survival in Wikipedia and Linux kernel.
Outperforms reputation-based prediction methods.
Bridges the gap with content-based predictors.
Abstract
As the number of contributors to online peer-production systems grows, it becomes increasingly important to predict whether the edits that users make will eventually be beneficial to the project. Existing solutions either rely on a user reputation system or consist of a highly specialized predictor that is tailored to a specific peer-production system. In this work, we explore a different point in the solution space that goes beyond user reputation but does not involve any content-based feature of the edits. We view each edit as a game between the editor and the component of the project. We posit that the probability that an edit is accepted is a function of the editor's skill, of the difficulty of editing the component and of a user-component interaction term. Our model is broadly applicable, as it only requires observing data about who makes an edit, what the edit affects and whether…
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