Social relationships in the digital sphere are becoming more usual and
frequent, and they constitute a very important aspect for all of us. {Violent
interactions in this sphere are very frequent, and have serious effects on the
victims}. Within this global scenario, there is one kind of digital violence
that is becoming really worrying: sexism against women. Sexist comments that
are publicly posted in social media (newspaper comments, social networks,
etc.), usually obtain a lot of attention and become viral, with consequent
damage to the persons involved. In this paper, we introduce an anti-sexism
alert system, based on natural language processing (NLP) and artificial
intelligence (AI), that analyzes any public post, and decides if it could be
considered a sexist comment or not. Additionally, this system also works on
analyzing all the public comments linked to any multimedia content (piece of
news, video, tweet, etc.) and decides, using a color-based system similar to
traffic lights, if there is sexism in the global set of posts. We have created
a labeled data set in Spanish, since the majority of studies focus on English,
to train our system, which offers a very good performance after the validation
experiments.

基于自然语言处理和人工智能的反性别歧视警报系统可分析任何公共帖子，判断是否为性别歧视评论，提供类似于交通灯的颜色系统来判断整体帖子中是否存在性别歧视，该系统在西班牙语标记数据集上训练，并取得了很好的性能表现。