  Constructing personalized and anthropomorphic agents holds significant
importance in the simulation of social networks. However, there are still two
key problems in existing works: the agent possesses world knowledge that does
not belong to its personas, and it cannot eliminate the interference of diverse
persona information on current actions, which reduces the personalization and
anthropomorphism of the agent. To solve the above problems, we construct the
social media agent based on personalized knowledge and dynamic persona
information. For personalized knowledge, we add external knowledge sources and
match them with the persona information of agents, thereby giving the agent
personalized world knowledge. For dynamic persona information, we use current
action information to internally retrieve the persona information of the agent,
thereby reducing the interference of diverse persona information on the current
action. To make the agent suitable for social media, we design five basic
modules for it: persona, planning, action, memory and reflection. To provide an
interaction and verification environment for the agent, we build a social media
simulation sandbox. In the experimental verification, automatic and human
evaluations demonstrated the effectiveness of the agent we constructed.
