基于硒和SVM的Facebook网络欺凌分类

Kim D. Gorro, M. J. Sabellano, Ken Gorro, C. Maderazo, Kris Capao
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引用次数: 11

摘要

网络欺凌是近年来新出现的问题之一,尤其是对青少年而言。由于智能手机的普及,大约24%的青少年经常上网。近21%的青少年表示,他们查看社交媒体的主要原因是确保没有人对他们说刻薄或不好的话。与网络欺凌相关的Facebook帖子是由一个定制的网络刮板工具收集的。这些收集的数据使用支持向量机(SVM)模型进行分类。总共有2263个数据被用于训练数据、Facebook帖子。在这些帖子的基础上,研究达到了88%的准确率和87%的召回率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Classification of Cyberbullying in Facebook Using Selenium and SVM
Cyberbullying is one of the emerging problems over the past few years especially to teenagers. Approximately 24% of teens goes online constantly, facilitated by the widespread availability of smartphones. Almost 21% of teens said the main reason they checked social media always was to make sure nobody was saying mean or bad things to them. Cyberbullying related Facebook posts were harvested by a customized web scraper tool. These harvested data were used for classification using Support Vector Machines (SVM) model. A total of 2263 data was used for training data, Facebook posts. Based on these posts, the study achieved the precision of 88% and the recall is 87%.
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