To reduce misinformation, it is necessary to identify the source of malicious messages on the web, that is, the sources of reproduction. A similar mechanism allows, among other things, to identify patient zero at the beginning of the epidemic. RPaSDT lets you know where fake news is coming from and how it’s spreading on social media.

Damien Frąszczak, a doctoral student at the Military University of Technology’s Doctoral School, presented the program he developed in an article published in the journal SoftwareX from Science Group. The young scientist is engaged in modeling social networks, spreading and learning about fake news.

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Social account holders, which are a large number of people and organizations, are eager to share information about their lives, activities, travels, and opinions. Therefore, social networks have become a valuable and free source of data, for example for advertising agencies that adjust advertisements according to users’ preferences ”- says Damien Friesczak. He asserts that the emergence of social networking sites has changed the image of the world. New modes of communication between people have replaced the traditional media of information. For For most people, social media platforms are the primary source of information. Social media can be used to alert people to dangerous situations or to collect donations for good causes. However, it also presents an excellent opportunity to spread misinformation – easily, quickly, and almost at no cost. Various aspects of life, for example, election results, financial status and mental state of users ”- he enumerates.

Damien Friesczak’s research shows that many methods for determining the “source of spread” have been developed, but that it is difficult to compare these solutions, and to verify reliably and choose the best, because there is no “testing area” for researchers. According to the creator, RPaSDT may have such a function.

In his article, the PhD student presented an easy-to-use set of IT tools that allow the identification of ‘diffusion sources’. The program supports the processes of analyzing, evaluating and visualizing social networks, as well as comparing the effectiveness of different methods for identifying sources. Tests can be performed for the opposite problems, that is, on the basis of a particular network (initial mode), select nodes, the propagation of which will cover all nodes in the network in the shortest time.

The scientific article “RPaSDT – Rumor Spreading and Source Discovery Toolkit” was published in January 2022 in the journal SoftwareX.

Damien Friesczak’s PhD promoters are: Dr. M. Ryszard Antkiewicz and dr inż. Marius Shmielewsky.

Information source: Science in Poland