Identifying Semantic Edit Intentions From Revisions In Wikipedia – ACL Anthology

Identifying Semantic Edit Intentions from Revisions in Wikipedia Diyi Yang writer Aaron Halfaker author Robert Kraut creator Eduard Hovy writer 2017-sep textual content Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing Association for Computational Linguistics Copenhagen, Denmark convention publication Most studies on human editing focus merely on syntactic revision operations, failing to seize the intentions behind revision modifications, which are important for facilitating the one and collaborative writing course of. On this work, we develop in collaboration with Wikipedia editors a 13-class taxonomy of the semantic intention behind edits in Wikipedia articles. Using labeled article edits, we build a computational classifier of intentions that achieved a micro-averaged F1 rating of 0.621. We use this model to analyze edit intention effectiveness: how different types of edits predict the retention of newcomers and modifications in the standard of articles, two key concerns for Wikipedia right this moment. Our analysis reveals that the forms of edits that users make in their first session predict their subsequent survival as Wikipedia editors, and articles in several stages need different types of edits.
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