And we have a practical solution — we create a global unbiased decentralized CyberPravda platform for disputes, for analyzing the reliability of information and assessing the reputation of its authors, where people are accountable with personal reputation for their knowledge and arguments.
We have found a way to mathematically determine the veracity of Internet information and have developed a fundamentally new algorithm that does not require the use of cryptographic certificates of states and corporations, voting tokens that can bribe any user, or artificial intelligence algorithms that are not able to understand the exact meaning of what a person said. The algorithm does not require external administration, review by experts or special content curators. We have neither semantics nor linguistics — all these approaches have not justified themselves. We have found a unique and very unusual combination of mathematics, psychology and game theory and have developed a purely mathematical international multilingual correlation algorithm that uses graph theory and allows us to get a deeper scientometric assessment of the accuracy and reliability of information sources compared to the PageRank algorithm or the Hirsch index. The algorithm allows betting on different versions of events with automatic determination of the winner and allows to create a holistic structural and motivational frame in which users and news agencies can earn money by publishing reliable information, and a high reputation rating becomes a fundamentally new social elevator.
CyberPravda mathematically evaluates the balance of arguments used by different authors to confirm or refute various contradictory facts to assess their credibility, in terms of consensus in large international and socially diverse groups. From these facts, the authors construct their personal descriptions of the picture of events, for the veracity of which they are held responsible by their personal reputations. An unbiased and objective purely mathematical correlation algorithm based on graph theory checks these narratives for mutual correspondence and coherence according to the principle of "all with all" and finds the most reliable sequences of facts that describe different versions of events. Different versions compete with each other in terms of the value of the flow of meaning, and the most reliable versions become arguments in the chain of events for facts of higher or lower level, which loops the chain of mutual interaction of arguments and counterarguments and creates a global hypergraph of knowledge, in which the greatest flow of meaning flows through stable chains of consistent scientific knowledge that best meet the principle of falsifiability and Popper's criterion. A critical path in the sequence of the most credible facts forms an automatically generated multi-lingual article for each of the existing versions of events, which is dynamically rearranged according to new incoming evidences and the desired credibility levels set by readers in their personal settings ranging from zero to 100%. As a result, users have access to multiple Wikipedia-like articles describing competing versions of events, ranked by objectivity according to their desired level of credibility.