Fraudsters keep up with the times and take advantage of new technologies

The category "social networks" is becoming an increasingly popular term in studies of all spheres of society. The development of technology and the ever-increasing volumes of information have led to the fact that the word "fake" or "information fake" has firmly entered our lives. All sorts of scammers keep up with the times and quickly put technology at their service, inventing new ways to influence people. Information noise and a huge amount of content in social networks forces us to choose. At the moment, there are practically no social networks that use the trust score.

What can help us? But what could really help is the use of data management approaches to recognize fakes and simply check the facts. It is clear that real technological solutions are somewhat more complicated, and they give answers following the language of data matching algorithms, i.e. as a percentage of the chance of a match. And then decision-making patterns from different subject areas are applied to this. As a result, we will get the answer in the form of the probability of the authenticity of the fact, and then applying subjective threshold values, depending on the risk and consequences of making one or another decision in relation to the fact being verified.

So, the calculation of trust in social networks is a new, developing area of ​​research within the framework of the general theory of Information retrieval. Modern problems require modern solutions, and certain algorithms can be used automatically with the help of a trained neural network. Therefore, Exorde as a knowledge network can use the unstructured content of the Internet and perform a first-of-its-kind analysis of the virality of information circulating throughout the network.

Exorde is a decentralized protocol that allows anyone to commission 100 or even 1000 people to run blockchain-based software to research a particular topic or keyword. Exorde not only crawls social media and blog platforms to collect the most recent published conversations, but also uses machine learning to collate data and interpret how people feel about a topic.

Exorde receives input URLs for public information such as social media posts, press articles, photos, and videos. These URLs are then processed in a decentralized data pipeline that produces output graphs linking all similar data and facts. The analyzed content is stored in an archive that has open access, so any person can access the original information at any time and from anywhere in the world.

Today, the Exorde protocol can be used in many ways, whether it be public opinion issues, for commercial purposes of any fast-growing company, for journalists in the field of censorship and information evaluation.

And it turns out that:

Exorde can record online activity before it is deleted.

Exorde can go to any public platform.

Exorde can detect censorship that social networking sites might not even be aware of.

As we can see, there are a huge number of ways to use Exorde both for commercial purposes and for issues of public interest. In conclusion, we can say that automatic detection of fakes is a fairly young area, in which there are many difficulties and opportunities. This task can bring (and already brings) new popularity to the classical methods of information management. At the same time, it is safe to say that the demand for approaches to detecting fakes will grow, as the popularity of tools for their creation will grow, as well as its availability, which will lead to a huge wave of fakes. In addition, models for creating fakes will improve, and the quality of the results will only improve. If now an unprepared person can still discern inconsistencies in most of the generated videos, then in five to ten years it will be much more difficult, if not impossible. Therefore, the key issue is the education of an information culture by society. And Exorde will help us evaluate the information.

Written by Bimevox
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