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Characterizing discussions in the Spanish Wikipedia

Abstract:

Wikipedia, as the largest online encyclopedia, is edited collaboratively by hundreds of users. The content in some articles can have dispute, giving rise to discussions which are registered in the related talk pages. In this paper, we propose an annotation schema for Spanish Wikipedia talk pages in order to determine the type of opinions expressed in them. We apply the annotation schema to a corpus that includes a collection of discussions about 148 topics drawn from 25 Spanish Wikipedia talk pages. We make the resulting dataset publicly available for download on github1. Furthermore, we train and evaluate supervised machine learning models to automatically identify the annotation labels. Linear Support Vector classifier (LinearSVC) performs better compared to other baseline models, and achieves an accuracy F1 = 0.71 in our experiments.