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Differences in structure and dynamics of networks retrieved from dark and public web forums

机译:从黑暗和公共网络论坛中检索网络的结构和动态的差异

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摘要

Humans make decisions based on the information they obtain from several major sources, among which the comments of others in Internet forums play an increasing role. Such forums cover a wide spectrum of topics and represent an essential tool in choosing the best products, manipulating views or optimizing our decisions regarding a number of aspects of our everyday life. However, many forums have extremely controversial topics and contents including those which radicalize the readers or spread information about dangerous products and ideas (e.g., drugs, weapons or aggressive ideologies). These just mentioned activities are taking place mainly on the so called "dark web" allowing the hiding of the identity of members using dark forums. We use network theoretical approaches to analyze the data we obtained by studying the connectivity features of the members and the threads within a wide selection of forums (including dark and semi-dark) and establish several characteristic behavioral patterns. Our findings reveal both common and rather different features in the two types of behavior. In particular, we show that the various distributions of quantities, like the activity of the commenters, the dynamics of the threads (defined using their lifetime) or the degree distributions corresponding to the three major types of forums we have investigated display characteristic deviations. This knowledge can be useful, for example, in identifying an activity typical for the dark web when it appears in the public web (since the public web can be accessed and used much more easily). (C) 2019 Elsevier B.V. All rights reserved.
机译:人类根据从几个主要来源获得的信息做出决定,其中互联网论坛中其他人的评论起着越来越大的作用。此类论坛涵盖了广泛的主题,代表了选择最佳产品,操纵视图或优化我们日常生活的多个方面的决策方面的基本工具。然而,许多论坛具有极具争议的主题和内容,包括那些激进读者或传播有关危险产品和想法的信息(例如,药物,武器或侵略意识形态)。这些刚才提到的活动主要是在所谓的“暗网络”中举行,允许使用黑暗论坛隐藏成员的身份。我们使用网络理论方法来分析我们通过研究各种论坛(包括黑暗和半暗)的成员和线程的连接性特征来分析我们获得的数据,并建立几种特征性行为模式。我们的研究结果显示了两种类型的行为中的常见和相当不同的功能。特别地,我们表明,许多分布,如评论者的活动,线程的动态(使用它们的寿命定义)或与我们已经调查显示特征偏差的三种主要类型的论坛的程度分布。例如,此知识可以有用,例如,在公共网络中出现时识别暗网的典型活动(因为可以更轻松地访问和使用公共网络以来)。 (c)2019 Elsevier B.v.保留所有权利。

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