首页> 外文会议>Second workshop on abusive language online 2018 >Aggression Detection on Social Media Text Using Deep Neural Networks
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Aggression Detection on Social Media Text Using Deep Neural Networks

机译:深度神经网络对社交媒体文本的攻击检测

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摘要

In the past few years, bully and aggressive posts on social media have grown significantly, causing serious consequences for victims/users of all demographics. Majority of the work in this field has been done for English only. In this paper, we introduce a deep learning based classification system for Face-book posts and comments of Hindi-English Code-Mixed text to detect the aggressive behaviour of/towards users. Our work focuses on text from users majorly in the Indian Subcontinent. The dataset that we used for our models is provided by TRAC-1 in their shared task. Our classification model assigns each Facebook post/comment to one of the three predefined categories: "Overtly Aggressive", "Covertly Aggressive" and "Non-Aggressive". We experimented with 6 classification models and our CNN model on a 10 K-fold cross-validation gave the best result with the prediction accuracy of 73.2%.
机译:在过去的几年中,社交媒体上的霸凌和侵略性帖子大量增长,给所有人口统计的受害者/用户造成了严重后果。该领域的大部分工作仅以英语完成。在本文中,我们引入了一种基于深度学习的分类系统,该系统用于脸书帖子和印地文-英语代码混合文本的注释,以检测用户/对用户的攻击行为。我们的工作主要集中在印度次大陆用户的文字上。我们用于模型的数据集由TRAC-1在其共享任务中提供。我们的分类模型将每个Facebook帖子/评论分配给三个预定义类别之一:““积极进取””,““积极进取””和““不积极进取””。我们使用6种分类模型进行了实验,我们的CNN模型在10 K折交叉验证中给出了最佳结果,预测准确性为73.2%。

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  • 会议地点 Brussels(BE)
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    Language Technologies Research Centre (LTRC) International Institute of Information Technology Hyderabad, Telangana, India;

    Language Technologies Research Centre (LTRC) International Institute of Information Technology Hyderabad, Telangana, India;

    Language Technologies Research Centre (LTRC) International Institute of Information Technology Hyderabad, Telangana, India;

    Language Technologies Research Centre (LTRC) International Institute of Information Technology Hyderabad, Telangana, India;

    Language Technologies Research Centre (LTRC) International Institute of Information Technology Hyderabad, Telangana, India;

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