IMPROVED METHOD FOR DETECTING FALSE INFORMATION BASED ON EXPERT ASSESSMENT

DOI: 10.31673/2409-7292.2025.020252

Abstract

The method of expert evaluation is an ancient scientific method that allows to obtain an objective assessment based
on a certain set of individual expert opinions. The word "expert" (expertus) in Latin means "experienced", which, in turn,
comes from the word "experire" - to explore. An expert is a person (specialist) entrusted with expressing an opinion on a
controversial or complex case, as humanity has always tried to take into account the opinion of highly qualified specialists
in various fields of life in difficult situations [2].
The article improves the method of detecting false information based on the method of expert evaluation. The
Delphi expert evaluation method was chosen as the basic method for improvement. This is because it has undoubted
advantages over methods based on conventional statistical processing of individual survey results. Unlike the existing
approach, the improved method allows for the selection of experts rather than adjusting the answers of experts to obtain
the required result.
The main feature is that the experts are selected by averaging the scores for each expert. Specifically, the selfassessment of the expert and the assessment of the same expert by the working group. This allows you to reduce the error
of the expert's real assessment.
The ability to set the confidence interval for the assessment of false information will allow obtaining results that
satisfy the task of detecting false information with proper accuracy. However, this leads to the task of optimizing the
evaluation criteria and the time for solving the task. Therefore, the direction of further research is the task of optimizing
the evaluation criteria.
The scientific novelty lies in substantiating and assessing the comparative importance of the factors limiting the
appointment of each individual expert to detect false information using the method of group expert assessment.
Keywords: false information, expert opinions, quartile, median, confidence interval, limitations.

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