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Abstract.
Enhancing the timeliness of predicting negative user actions in social networks is a critical research direction, particularly in countering societal destabilization threats. This article presents an information model for forecasting potentially adverse coordinated user actions in software products with network effects. The proposed model is based on an adapted approach for predicting sudden surges in actor activity, originally developed to analyze the dynamics of social processes. The model identifies early warning signals of anomalous actor behavior by detecting deviations of key predictive metrics from typical values. The study describes the forecasting information model, the architecture of the software system, the database schema, and the algorithm for automated determination of the model’s key parameters. Additionally, the article presents validation results of the implemented software system using open data from Reddit comments and posts.
Keywords:
software product with network effect, information model, forecasting, social networks.
DOI 10.14357/20718632260104
EDN OONHVM
PP. 41-53.
References
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