论文标题
有毒评论猎人：有毒评论的严重程度
Toxic Comments Hunter : Score Severity of Toxic Comments
论文作者
论文摘要
有毒评论的检测和识别有利于创造文明和和谐的互联网环境。在此实验中，我们收集了与有毒评论有关的各种数据集。由于注释数据的特征，我们从不同角度执行数据清洁并进行特征提取操作，以获得不同的有毒评论训练集。在模型构建方面，我们使用培训集来基于TFIDF训练模型，并分别对BERT模型进行了填充。最后，我们将代码封装在软件中，以实时评分有毒评论。
The detection and identification of toxic comments are conducive to creating a civilized and harmonious Internet environment. In this experiment, we collected various data sets related to toxic comments. Because of the characteristics of comment data, we perform data cleaning and feature extraction operations on it from different angles to obtain different toxic comment training sets. In terms of model construction, we used the training set to train the models based on TFIDF and finetuned the Bert model separately. Finally, we encapsulated the code into software to score toxic comments in real-time.
