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ZENODO
Dataset . 2019
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2019
License: CC BY
Data sources: ZENODO
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Dataset for "Large Scale Crowdsourcing and Characterization of Twitter Abusive Behavior"

Authors: Antigoni-Maria Founta; Constantinos Djouvas; Despoina Chatzakou; Ilias Leontiadis; Jeremy Blackburn; Gianluca Stringhini; Athena Vakali; +2 Authors

Dataset for "Large Scale Crowdsourcing and Characterization of Twitter Abusive Behavior"

Abstract

This is the updated dataset for the publication "Large Scale Crowdsourcing and Characterization of Twitter Abusive Behavior". Antigoni-Maria Founta, Constantinos Djouvas, Despoina Chatzakou, Ilias Leontiadis, Jeremy Blackburn, Gianluca Stringhini, Athena Vakali, Michael Sirivianos and Nicolas Kourtellis. International AAAI Conference on Web and Social Media (ICWSM), 2018. The dataset provided here includes an updated version of the original dataset, with ~100k tweets annotated using the CrowdFlower platform: hatespeech_labels.csv: contains ~100k rows, where every row is consisted of a unique Tweet ID and its associated majority annotation UPDATE: It has come to our understanding that a number of the tweets are not available anymore for download on Twitter. Therefore, under request, we can provide one more file with the full 100k tweet text and their associated majority labels. The tweets are shuffled so that there is no connection between tweet IDs and texts (in order to be aligned with the T&C of Twitter). To obtain the file contact the authors through email. Please cite the paper in any published work that uses any of these resources. @inproceedings{founta2018large, title={Large Scale Crowdsourcing and Characterization of Twitter Abusive Behavior}, author={Founta, Antigoni-Maria and Djouvas, Constantinos and Chatzakou, Despoina and Leontiadis, Ilias and Blackburn, Jeremy and Stringhini, Gianluca and Vakali, Athena and Sirivianos, Michael and Kourtellis, Nicolas}, booktitle={11th International Conference on Web and Social Media, ICWSM 2018}, year={2018}, organization={AAAI Press} } For any further questions contact a.m.founta at gmail dot com. Publication DOI: https://doi.org/10.5281/zenodo.1443348 Github: https://github.com/ENCASEH2020/hatespeech-twitter

EOSC Subjects

Twitter Data

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    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).
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    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.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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    download downloads 111
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visibility
download
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!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
OpenAIRE UsageCountsDownloads provided by UsageCounts
0
Average
Average
Average
116
111
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