The usage of On-line Social Networks (OSN) and Virtual Communities (VC) has exploded in the last decade. People use these tools for a better communication with friends, colleagues and relatives. These have also been adopted by companies and organizations to improve their interactions with customers. Therefore, a description of the posting dynamics would further enhance the analysis by describing future tendencies. Current methods of diffusion analysis rely on machine learning techniques that analyze content activity history in OSNs. Our work presents a stochastic model based on decision making psychology to describe content posting dynamics on OSNs and VCs. Our proposal was simulated on a real VC, recovering most of its average content generation behavior. Simulated posted topic distribution becomes near to observed data within a mean absolute percentage error MAPE of 1:2%.