基于社交网络挖掘技术的网络欺凌检测研究

I. Ting, Wun Sheng Liou, Dario Liberona, Shyue-Liang Wang, G. T. Bermúdez
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引用次数: 21

摘要

近年来,用户普遍倾向于在互联网上表达和分享他们的观点。然而,由于社交媒体的特点,出现了对社交媒体的消极使用。网络欺凌是网络中的一种滥用行为,也是一个非常严重的社会问题。在这样的背景和动机下,如果我们能够开发相关的技术来发现社交媒体中的网络欺凌,将有助于预防网络欺凌的发生。因此,在本文中,我们提出了一种基于社交网络分析和数据挖掘的网络欺凌检测方法。在该方法中,将研究三种主要的网络欺凌发现技术,包括关键字匹配技术、意见挖掘和社会网络分析。除了方法之外,我们还将讨论性能评估的实验设计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards the detection of cyberbullying based on social network mining techniques
In recent years, users are widely intend to express and share their opinions over the Internet. However, due to the characters of social media, it appears negative use of social media. Cyberbullying is one of the abuse behavior in the Internet as well as a very serious social problem. Under this background and motivation, it can help to prevent the happen of cyberbullying if we can develop relevant techniques to discover cyberbullying in social media. Thus, in this paper we propose an approach based on social networks analysis and data mining for cyberbullying detection. In the approach, there are three main techniques for cyberbullying discovery will be studied, including keyword matching technique, opinion mining and social network analysis. In addition to the approach, we will also discuss the experimental design for the evaluation of the performance.
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