  In this paper, we study how an agent's belief is affected by her neighbors in
a social network. We first introduce a general framework, where every agent has
an initial belief on a statement, and updates her belief according to her and
her neighbors' current beliefs under some belief evolution functions, which,
arguably, should satisfy some basic properties. Then, we focus on the majority
rule belief evolution function, that is, an agent will (dis)believe the
statement iff more than half of her neighbors (dis)believe it. We consider some
fundamental issues about majority rule belief evolution, for instance, whether
the belief evolution process will eventually converge. The answer is no in
general. However, for random asynchronous belief evolution, this is indeed the
case.
