Edit Categories And Editor Role Identification In Wikipedia
Language Resources and Evaluation(2016)
摘要
In this work, we introduced a corpus for categorizing edit types in Wikipedia. This fine-grained taxonomy of edit types enables us to differentiate editing actions and find editor roles in Wikipedia based on their low-level edit types. To do this, we first created an annotated corpus based on 1,996 edits obtained from 953 article revisions and built machine-learning models to automatically identify the edit categories associated with edits. Building on this automated measurement of edit types, we then applied a graphical model analogous to Latent Dirichlet Allocation to uncover the latent roles in editors' edit histories. Applying this technique revealed eight different roles editors play, such as Social Networker, Substantive Expert, etc.
更多查看译文
关键词
Edit Category,Role Identification,Topic Modeling
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络