Mapping the Cyberstalking Landscape: An Empirical Analysis of Federal U.S Crimes

Sasha Romanosky, Peter Schirmer
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Abstract

Among the new forms of technology-facilitated abuses, cyberstalking has become a growing and important problem. Cyberstalking involves the use of technology to stalk, threaten, or harass one or more individuals. For example, it can include tracking and intimidating a victim over social media, email, or text messages, or threatening to expose someone’s intimate photographs (sextortion). Cyberstalking has become a mechanism used by current or former domestic or intimate-partners, lone perpetrators, individuals targeting victims based on their employment or public image, and members of extremist groups. The innovations of this research are twofold. First, using multiple data sets, we developed an automated capability to identify and collect the complete set of all federally prosecuted cyberstalking cases in the U.S.. Second, we employ natural language processing, network, and regression methods to code and analyze the court records. We apply these methods in order to answer three main research questions: how many federal cyberstalking cases are there?; what kinds of stalking behavior are being committed?; and what characteristics are correlated with conviction and severity of punishment?
绘制网络跟踪景观:美国联邦犯罪的实证分析
在新形式的技术促进滥用中,网络跟踪已经成为一个日益严重的问题。网络跟踪涉及使用技术跟踪、威胁或骚扰一个或多个个人。例如,它可以包括通过社交媒体、电子邮件或短信跟踪和恐吓受害者,或者威胁要暴露某人的私密照片(性勒索)。网络跟踪已成为现任或前任家庭或亲密伴侣、单独犯罪者、基于就业或公众形象针对受害者的个人以及极端组织成员使用的一种机制。这项研究的创新是双重的。首先,使用多个数据集,我们开发了一种自动化的能力来识别和收集美国所有联邦起诉的网络跟踪案件的完整集合。其次,我们采用自然语言处理、网络和回归方法对法庭记录进行编码和分析。我们运用这些方法来回答三个主要的研究问题:有多少联邦网络跟踪案件?有哪些跟踪行为?哪些特征与定罪和惩罚的严重性相关?
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