Automated Organization ProfileSirivianos
Sirivianos
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets in this organization
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the organization's datasets
Total Mentions
Total mentions of the organization's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 3.6 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
This dataset is deprecated. The updated version of this Dataset is here: https://zenodo.org/record/3678559#.Xl9-Ji97FhE 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 consists 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, upon 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 a.m.founta at gmail dot com AND antonis26papa at gmail dot com. 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
Authors
- Antigoni-Maria ;
- Constantinos ;
- , Despoina ;
- , Ilias ;
- , Jeremy ;
- , Gianluca ;
- , Athena ;
- , Michael ;
- , Nicolas
This dataset is deprecated. The updated version of this Dataset is here: https://zenodo.org/record/3678559#.Xl9-Ji97FhE 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 consists 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, upon 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 a.m.founta at gmail dot com AND antonis26papa at gmail dot com. 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
Authors
- Antigoni-Maria ;
- Constantinos ;
- , Despoina ;
- , Ilias ;
- , Jeremy ;
- , Gianluca ;
- , Athena ;
- , Michael ;
- , Nicolas