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ZENODO
Dataset . 2019
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2019
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2019
License: CC BY
Data sources: Datacite
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WAC Corpus - Wikipedia Abusive Conversations

Authors: Cécillon, Noé; Labatut, Vincent; Dufour, Richard;

WAC Corpus - Wikipedia Abusive Conversations

Abstract

This repository contains conversations between Wikipedia editors, which are annotated in terms of various types of abuse, at the level of messages. This corpus is described in the following publication: N. Cécillon, V. Labatut, R. Dufour, and G. Linarès, “WAC: A Corpus of Wikipedia Conversations for Online Abuse Detection,” in 12th Language Resources and Evaluation Conference, 2020, pp. 1375–1383. ⟨hal-02497514⟩ The repository also contains the figures shown in this article. Sources. Our corpus aligns two existing corpora: Messages and conversation structures of WikiConv (https://github.com/conversationai/wikidetox/tree/master/wikiconv) Manual annotations in toxicity of Wikipedia Comment Corpus (WCC -- https://doi.org/10.6084/m9.figshare.4054689) Citation. If you use this dataset, please cite the above article. @InProceedings{Cecillon2020, author = {Cécillon, Noé and Labatut, Vincent and Dufour, Richard and Linarès, Georges}, title = {{WAC}: A Corpus of {W}ikipedia Conversations for Online Abuse Detection}, booktitle = {12\textsuperscript{th} Language Resources and Evaluation Conference}, year = {2020}, pages = {1375-1383}, address = {Marseille, FR}, url = {http://www.lrec-conf.org/proceedings/lrec2020/pdf/2020.lrec-1.172.pdf},}

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Keywords

Online comments, Wikipedia conversations, Evaluation framework, Automatic moderation, Abuse detection

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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