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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
Twitter Data
Twitter Data
| 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). | 0 | |
| 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. | Average |
| views | 116 | |
| downloads | 111 |

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