Research on the Barrage Classification Algorithm for the Protection of Teenager on Video Websites

Tiansheng Xu, Rumeng Wang
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Abstract

In order to avoid the adverse impact of barrages on teenagers on video website, the author realizes the layering, classification and grading of users' barrages by using the text classification algorithm of deep learning, guides the users' barrages and creates a good ecological environment of network language. The algorithm of barrage classification display needs to be updated in real time. In terms of data, we need to expand the sample of machine learning training in real time, in addition, the classification of language score should be further refined and accurate. In terms of technology, we can combine the latest development of psychology, communication and statistics to make the classification of barrages more accurate.
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视频网站青少年保护的弹幕分类算法研究
为了避免视频网站上的狂语对青少年的不良影响,作者利用深度学习的文本分类算法实现了用户狂语的分层、分类和分级,引导用户狂语,营造良好的网络语言生态环境。弹幕分类显示算法需要实时更新。在数据方面,我们需要实时扩大机器学习训练的样本,此外,语言分数的分类也要进一步细化和准确。在技术方面,我们可以结合心理学、传播学和统计学的最新发展,使弹幕的分类更加准确。
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