In the current information ecosystem, it has become utterly challenging - while at the same time - extremely essential, to identify misinformation, information biases and manipulations. The 2016 U.S presidential elections, for example, were characterized with harsh accusations from both sides, blaming the media, political players, and even foreign governments, for deliberately spreading "fake news" to influence election outcomes. Content copying and editing procedures seem to become more accessible than ever, and despite the attempt to prevent it numerous "fake" copies exist. Our paper argues that it is imperative to consider more efficient ways to track content unit across different digital platforms, whether for keeping track of the agenda-setting building in Hybrid media systems or for the broader goal of keeping democratic processes uncontaminated. Weinberger (2007) suggested that an efficient way to deal with information overload is dynamic tagging, predetermined by the content creator or by post-evaluation of editors, users, and automated software. Thus, we suggest that hashtags or similar features (e.g., Barcodes) should be used to enable a reliable tracking system. As Blockchain mechanism thought us, tracking is not equal to governmental or industrial surveillance, thus, such system will make it possible for anyone of interest to identify the source, as well as the whole "life circle" of any piece of information and idea, which might have been traveling for a while across various social networks and the internet. This tracking mechanism might also drive some players away from any attempt to spread "alternative facts," lies, and biased information.