How can you model the spread of information or influence in social networks?

Markov processes mathematically describe the mechanisms in the system, and predict the system's equilibrium behavior upon intervention, but do not support ... Dec 3, 2021 ... A stochastic model that depicts a sequence of possible events where predictions or probabilities for the next state are based solely on its previous event ... A Weibull distribution based semi-Markov process model for urban bridge deterioration prediction was proposed in this paper. Mar 11, 2025 ... A Markov process with stationary transition probabilities may or may not be a stationary process in the sense of the preceding paragraph. If Y1, ... Jan 4, 2013 ... I have a transition probability matrix with 100 states (100x100) and I'd like to simulate 1000 steps with the initial state as 1. A 'continuous time' stochastic process that fulfills the Markov property is called a Markov process. We will further assume that the Markov process for all i,j ... ... Markov-Process and Time Division Multiple Access (TDMA) protocol. A customized module to the controller only initializes the mapping when there are ... Using the fact that by a suitable recursive generation from independent random processes with arbitrary image spaces Markov chains with regular. Markov Processes and Potential Theory By R. M. Blumenthal and R. K. Getoor. Pp. x + 313. (Academic Press: New York and London, 1968.) 140s. Feb 6, 2008 ... Recap. Last lecture, we talked about two types of Markov processes: the Poisson process and the Brownian motion process.