用深度学习识别西语网络欺凌内容，助力保护弱势群体
Detecting cyberbullying in Spanish texts through deep learning techniques
- 基于推特数据构建西语欺凌语料库，训练卷积神经网络
- 模型可准确识别侮辱、种族歧视、恐同攻击等欺凌表达
- 为西班牙语社交平台内容安全提供实用解决方案
近期收集的数据表明，通过社交媒体或即时通讯应用等通信技术，可自动检测可能对社会最弱势群体造成负面影响的事件。本研究整合并整理了来自推特的西班牙语欺凌表达语料库，用于训练卷积神经网络，采用深度学习技术。经过训练，建立了一个预测模型，能够识别西班牙语网络欺凌表达，如侮辱、种族主义、恐同攻击等。
原文摘要 · Abstract (English)
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.
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