Context Models of how people move around cities play a role in making decisions about urban and land-use planning. Previous models have been based on space and time, and have neglected the social aspect of travel. Recent work on agent-based modelling shows promise as a new approach, especially for models with both social and spatial elements. Objective This paper demonstrates the design and implementation of an agent-based model of social activity generation and scheduling for experimental purposes to explore the effects of social space in addition to physical space. As a side-effect, the paper discusses the need for and requirements on structured design of agent-based models and simulations. Method Model design was based on the MASQ meta-model and implemented in Python. The model was then tested against several hypotheses with several initial networks. Results The model allowed us to investigate the effects of social networks. We found that the model was most sensitive to the pair attributes of the network, rather than the global or personal attributes. Conclusion As demonstrated, a structured approach to model development is important in order to be able to understand and apply the results, and for the model to be extensible in the future. Agent-based modelling approaches allow for inclusion of social elements. For models incorporating social networks, testing the sensitivity to the initial network is important to ensure the model performs as expected.