图 书 馆
谁能编辑什么预测编辑生存Can Who‑Edits‑What Predict Edit Survival |
|
| 课程网址: | http://videolectures.net/kdd2018_kristof_edit_survival/ |
| 主讲教师: | Victor Kristof |
| 开课单位: | 洛桑联邦理工学院，EPFL |
| 开课时间: | 2018-11-23 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | 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 the edit survives or not. We apply our model on Wikipedia and the Linux kernel, two examples of large-scale peer-production systems, and we seek to understand whether it can effectively predict edit survival: in both cases, we provide a positive answer. Our approach significantly outperforms those based solely on user reputation and bridges the gap with specialized predictors that use content-based features. It is simple to implement, computationally inexpensive, and in addition it enables us to discover interesting structure in the data. |
| 关 键 词: | 在线同行生产系统; 有效地预测编辑生存; 维基百科和Linux内核; 编辑组件的难度 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2023-01-29：cyh |
| 最后编审: | 2023-01-30：cyh |
| 阅读次数: | 19 |