Multi-agent simulation modeling of online Internet discussions

Joint analysis of the general structure of online Internet discussions and different attributes of particular text comments becomes an important scientific task in theoretical and applied aspects. Although methods of machine learning facilitate stochastic analysis of text messages, appropriate modeling of dynamics of online discussion and psycho-linguistic characteristics of comments in the presence of multiple individual authors remains the unresolved problem. In this article, the authors suggest applying the methods of multi-agent simulations for resolution of that problem. This work offers two models of online discussion which allow us to take into account characteristics of individual comments and the presence of multiple authors with individual models of behavior. The behavior models are designed in the result of analysis of actual online Internet discussions. The first model is centralized and represents the behavior of each author in the same manner, using a set of fixed parameters. In comparison to the centralized model, the multi-agent distributed model states the individualized behavior for every author through the Markov chain of the special form. Such individualized structure allows us not only to approach the real dynamics of the discussion, but also to compare the models with the actual online Internet discussions. Using pre-processed factual data of real discussions from various Internet portals became an important feature of the suggested approach to simulation modeling. Pre-processing includes expert evaluation of psycho-linguistic characteristics (intent and content analysis), as well as methods of mathematical statistics. Therefore, this research is a positive example of interdisciplinary research of Internet communication phenomena.