Detection of Cyberbullying Incidents on the Instagram Social Network
Detection of Cyberbullying Incidents on the Instagram Social Network
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Instagram 社交网络上的网络欺凌事件检测
DOI：
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发表时间：
2015
期刊：
影响因子：
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通讯作者：
Shivakant Mishra
中科院分区：
文献类型：
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作者：
Homa Hosseinmardi;S. Mattson;R. Rafiq;Richard O. Han;Q. Lv;Shivakant Mishra
网络欺凌是一个日益严重的问题，影响着超过半数的美国青少年。本文的主要目的是从根本上研究新的方法，以理解并自动检测Instagram（一个基于媒体的移动社交网络）上图片中的网络欺凌事件。为此，我们收集了一个由图片及其相关评论组成的Instagram样本数据集，并在众包网站Crowdflower上利用人工标注员设计了一项针对网络欺凌以及图片内容的标注研究。然后对标注数据进行了分析，包括对不同特征与网络欺凌以及网络攻击之间相关性的研究。利用标注数据，我们进一步设计并评估了一个分类器自动检测网络欺凌事件的准确性。
Cyberbullying is a growing problem affecting more than half of all American teens. The main goal of this paper is to investigate fundamentally new approaches to understand and automatically detect incidents of cyberbullying over images in Instagram, a media-based mobile social network. To this end, we have collected a sample Instagram data set consisting of images and their associated comments, and designed a labeling study for cyberbullying as well as image content using human labelers at the crowd-sourced Crowdflower Web site. An analysis of the labeled data is then presented, including a study of correlations between different features and cyberbullying as well as cyberaggression. Using the labeled data, we further design and evaluate the accuracy of a classifier to automatically detect incidents of cyberbullying.