Detecting cyberbullying in Spanish texts through deep learning techniques
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Abstract (arXiv)
Recent recollected data suggests that it is possible to automatically detect events that may negatively affect the most vulnerable parts of our society, by using any communication technology like social networks or messaging applications. This research consolidates and prepares a corpus with Spanish bullying expressions taken from Twitter in order to use them as an input to train a convolutional neuronal network through deep learning techniques. As a result of this training, a predictive model was created, which can identify Spanish cyberbullying expressions such as insults, racism, homophobic attacks, and so on.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 3 of its 35 references that are in the map. First posted on arXiv 22 Dec 2025.
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3 of 35 references.
References · 3
- 2013Efficient Estimation of Word Representations in Vector Spacecited by 4,346
- 2014Convolutional Neural Networks for Sentence Classificationcited by 1,124
- 2018Deep Learning for Detecting Cyberbullying Across Multiple Social Media Platformscited by 37
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