Enhancing the Identification of Cyberbullying through Participant Roles

Ratnayaka, Gathika; Atapattu, Thushari; Herath, Mahen; Zhang, Georgia; Falkner, Katrina

doi:10.48550/arxiv.2010.06640

2020

DOI: 10.48550/arxiv.2010.06640

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Enhancing the Identification of Cyberbullying through Participant Roles

Gathika Ratnayaka¹,

Thushari Atapattu²,

Mahen Herath³

et al.

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2024

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Improving automatic cyberbullying detection in social network environments by fine-tuning a pre-trained sentence transformer language model

Gutiérrez-Batista,

Gómez-Sánchez,

Fernandez-Basso

2024

Soc. Netw. Anal. Min.

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The internet use among children and adolescents has increased massively recently. This situation has promoted harmful situations such as cyberbullying, which is becoming a worldwide problem that entails serious consequences for well-being. The detection of these attitudes is essential to prevent and act accordingly. Groundbreaking techniques based on deep learning, like pre-trained language models, have achieved state-of-the-art results in many downstream Natural Language Processing tasks. This paper presents a simple but effective approach to improve the detection of cyberbullying situations by fine-tuning a pre-trained sentence transformer language model. We experimented on three datasets, and the results surpassed the state-of-the-art results. The approach could help prevent cyberbullying, filter those messages, and detect those children involved in the situation, providing opportunities to develop intervention programs to address this problem.

show abstract

Improving automatic cyberbullying detection in social network environments by fine-tuning a pre-trained sentence transformer language model

Gutiérrez-Batista,

Gómez-Sánchez,

Fernandez-Basso

2024

Soc. Netw. Anal. Min.

View full text Add to dashboard Cite

show abstract

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Enhancing the Identification of Cyberbullying through Participant Roles

Cited by 1 publication

References 0 publications

Improving automatic cyberbullying detection in social network environments by fine-tuning a pre-trained sentence transformer language model

Improving automatic cyberbullying detection in social network environments by fine-tuning a pre-trained sentence transformer language model

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