你站在哪一边?一个新的圆形监狱vs.隐私

Miltiadis Kandias, L. Mitrou, V. Stavrou, D. Gritzalis
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引用次数: 39

摘要

社交媒体和Web 2.0使互联网用户能够贡献在线内容,这些内容可能会被抓取并用于各种原因,从个性化广告到行为预测/分析。一个消极的情况是政治派别分析。我们的假设是,这种情况现在是现实的,适用于社交媒体,侵犯了公民权利、隐私和自由。为了证明这一点,我们开发了一个恐怖故事,即Panopticon方法,以揭示这种威胁,并有助于提高社会对它的认识。圆形监狱依赖于数据/意见挖掘技术;因此,它对从流行的社交媒体YouTube上收集的评论、视频和播放列表进行分类。然后,它汇总这些分类,以决定用户的政治派别。圆形监狱的实验案例是一个庞大的希腊YouTube用户社区。为了证明我们的案例,我们对收集的数据集进行了广泛的图形理论和内容分析,并展示了如何以及什么样的个人数据(例如政治态度)可以通过对公开可用的YouTube数据进行数据挖掘来获得。然后,我们为读者提供了今天可用的法律手段的分析,一个公民或一个社会作为一个整体,以有效地防止这种威胁。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Which side are you on? A new Panopticon vs. privacy
Social media and Web 2.0 have enabled internet users to contribute online content, which may be crawled and utilized for a variety of reasons, from personalized advertising to behaviour prediction/profiling. One negative case scenario is the political affiliation profiling. Our hypothesis is that this scenario is nowadays realistic, applicable to social media, and violates civil rights, privacy and freedom. To demonstrate this, we developed a horror story, i.e., a Panopticon method, in order to reveal this threat and contribute in raising the social awareness over it. The Panopticon relies on data/opinion mining techniques; hence it classifies comments, videos and playlists, collected from the popular social medium YouTube. Afterwards, it aggregates these classifications in order to decide over the users' political affiliation. The experimental test case of the Panopticon is an extensive Greek community of YouTube users. In order to demonstrate our case, we performed an extensive graph theoretical and content analysis of the collected dataset and show how and what kind of personal data (e.g. political attitude) can be derived via data mining on publicly available YouTube data. Then, we provide the reader with an analysis of the legal means that are available today, to a citizen or a society as a whole, so as to effectively be prevented from such a threat.
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