False Beliefs in Unreliable Knowledge Networks

The aims of this work are: (1) to extend knowledge dynamics analysis in order to assess the influence of false beliefs and unreliable communication channels, (2) to investigate the impact of selection rule-policy for knowledge acquisition, (3) to investigate the impact of targeted link attacks (“breaks” or “infections”) of certain “healthy” communication channels. We examine the knowledge dynamics analytically, as well as by simulations on both artificial and real organizational knowledge networks. The main findings are: (1) False beliefs have no significant influence on knowledge dynamics, while unreliable communication channels result in non-monotonic knowledge updates (“wild” knowledge fluctuations may appear) and in significant elongation of knowledge attainment. Moreover, false beliefs may emerge during knowledge evolution, due to the presence of unreliable communication channels, even if they were not present initially, (2) Changing the selection rule-policy, by raising the awareness of agents to avoid the selection of unreliable communication channels, results in monotonic knowledge upgrade and in faster knowledge attainment, (3) “Infecting” links is more harmful than “breaking” links, due to “wild” knowledge fluctuations and due to the elongation of knowledge attainment. Moreover, attacking even a “small” percentage of links (≤5%) with high knowledge transfer, may result in dramatic elongation of knowledge attainment (over 100%), as well as in delays of the onset of knowledge attainment. Hence, links of high knowledge transfer should be protected, because in Information Warfare and Disinformation, these links are the “best targets”.