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

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... 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.