This paper explains how agents in a social network can learn the arbitrary time-varying true state of the network. This is practical in social networks where information is released and updated without any coordination. Most existing literature for learning the true state using the non-Bayesian learning approach. assumes that this true state is fixed. https://www.roneverhart.com/Washington-Capitals-Topanga-Cooler-Tote-Bag/