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Publication Detailed Description
Using fuzzy fingerprints for cyberbullying detection in social networks
2018 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
Year (definitive publication)
2018
Language
English
Country
United States of America
More Information
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Abstract
As cyberbullying becomes more and more frequent in social networks, automatically detecting it and pro-actively acting upon it becomes of the utmost importance. In this work, we study how a recent technique with proven success in similar tasks, Fuzzy Fingerprints, performs when detecting textual cyberbullying in social networks. Despite being commonly treated as binary classification task, we argue that this is in fact a retrieval problem where the only relevant performance is that of retrieving cyberbullying interactions. Experiments show that the Fuzzy Fingerprints slightly outperforms baseline classifiers when tested in a close to real life scenario, where cyberbullying instances are rarer than those without cyberbullying.
Acknowledgements
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Keywords
Cyberbullying,Fuzzy fingerprints,Machine learning,Abusive language
Fields of Science and Technology Classification
- Physical Sciences - Natural Sciences
Funding Records
| Funding Reference | Funding Entity |
|---|---|
| PTDC/MHCPED/3297/2014 | Fundação para a Ciência e a Tecnologia |
| UID/CEC/50021/2013. | Fundação para a Ciência e a Tecnologia |
| PTDC/IVCESCT/4919/2012 | Fundação para a Ciência e a Tecnologia |
Contributions to the Sustainable Development Goals of the United Nations
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