Transmissão de rumores em redes

Abstract

With the advancement of communication technologies, it has become easy to pass on information, whether true or not. This brings enormous challenges to ensuring that only correct information remains in circulation. This work studies how information spreads using four probabilistic models proposed in this study. More specifically, branching processes are used, which help to understand how a news item can grow or disappear over time. The idea is as follows: each person who receives the information can pass it on to others, and this dynamic follows a random pattern. Several important characteristics of the process are analyzed. For example, the number of people who receive the news from a single individual, the height of the cascade (i.e., how far the information reaches), the total size of the cascade, and the probability of the information ceasing to spread. These models help to identify patterns that can be useful for developing strategies to control the dissemination of false information.