In order to detect IO, it is necessary to involve a complex of analytical techniques. The complex includes methods of nonlinear dynamics and computer linguistics.
The wavelet transform and its modifications are applied to detect periodicity, peaks, spikes, and behavioral patterns in the dynamics of the number of thematic publications.
To extract meaningful and significant words from the text of publications we use the TFIDF score, the standard deviation estimate, and horizontal visibility graphs.
Applying decision-making support methods, we provide the decomposition of the topics of the IO and assess rating of the effectiveness of these topics.
It is proposed a concept of a new information-analytical system for detection of IO through integration of a decision support system, a content-monitoring system, a system for distributed expert information collection and processing and an expert estimation system.