open all | close all

     If you are looking for a specific digital content online, both public and copyrighted, peer-to-peer file sharing using a BitTorrent client quickly comes into the picture once the traditional search engines (Google, Yahoo) fail to deliver what you need.

     Finding new contents may be a joyous event in the beginning if you are lucky enough to find exactly what you want. But it quickly becomes a chore or a complete waste of time once unrelated junks or fake items fill up your search results. Most users typically discover new contents by performing a keyword search on the traditional search engines or by visiting a torrent index site. A typical user may not really know what he or she is looking for, what is trending, or what is currently the latest and greatest. To offer such user some ideas, a torrent site’s category view comes in useful to allow browsing of specific content such as videos, music, software or games.

     It would be great if there is an automatic mechanism through which to find new content. One that simply works with almost no effort. It neither involves visiting a torrent index site nor requires any kind of keyword search. One that would find new contents available from large peer-to-peer networks such as the BitTorrent mainline DHT and the Vuze DHT, the current trending and the latest and greatest based on the activities of other most active users. This automatic mechanism, in a sense, is similar to the "suggested video” feature on YouTube which displays a list of somewhat related videos next to the one you selected for viewing based upon certain ranking criteria. You save yourself a great deal of time and resources to look for new and even find unexpected contents since the work has already been done for you by your peers.

     Fortunately, this mechanism already exists.

     Almost all new contents in many languages and locales are available to acquire from two large BitTorrent networks: the mainline DHT and the Vuze DHT network. The mainline DHT can have more than several hundred millions to billions of users worldwide at a time. The Vuze DHT network is a lot smaller but can also have millions of users at a time. Contents are mostly illegally distributed motion pictures, TV shows, pirated music tracks, cracked software applications and utilities, ripped adult movies from websites or recorded media, specialty genre such as Anime, copyrighted books and publication stored in files of compressed digital format, noteably files with the extension pdf and epub.

     The above video clip shows some of the features of the popular BitTorrent client Vuze Azureus to acquire contents from these DHT networks. Most if not all modern BitTorrent clients can search or download for a specific torrent but cannot show the complete picture of what peers are currently trading on the entire network. This website is a documentary in progress to test customized BitTorrent protocol software tools designed to provide snapshots of trading activities of top peers appeared worldwide on both the mainline and Vuze DHT networks over an approximate four- to six-week interval.

     These snapshots are available in database files to enable further analysis by any relational database engine. By investigating the contents that are actively traded without downloading or uploading anything, one can have a very good idea of "what's new", "what's available", and "who is doing what" without having to deal with search engines, torrent sites, abusive feeds, potential legal issues, regional blockage to access, while being completely anonymous.

     The main goal of this website is not to participate in any type of file sharing, either uploading or downloading contents, but to develop, integrate, and test new reporting tools to see what new contents currently are available and actively shared by millions of users worldwide. It is possible to design and implement a system to perform automatic searching for new contents using time tested off the shelf open source components. If only the title description of the contents and the IP address of the peers referring to the contents are recorded, millions of such titles can be collected in just a matter of days to be analyzed further by standard relational database tools. With proper database analysis methods, those peers that refer to a list of contents similar to what you are looking for can be built as lists of “suggested contents” quickly. By looking at the related and suggested contents, there is the likelihood that new contents that match your needs and interest can be detected with a reasonable degree of success.

     In a nutshell, if you are interested in contents A, B and C and there are thousands of other users in the network refer to contents A, B, D and A, B, E, then contents A, B are related contents while D and E are suggested contents and might be of interest to you. The implication of the unintended consequences of this mechanism is the ability to monitor sharing activities based upon specific peer, specific contents distributed among specific peers, and how the contents are distributed worldwide.