The availability of social infrastructure plays a vital role in promoting the health and well-being of communities. Historically, people found a sense of place in gathering spaces located within mixed-use neighbourhoods (Oldenburg 1997); however, the proliferation of dormitory suburbs and single-use zoning has resulted in decreased informal public life and social support (Lawson 2004). Intermediary spaces have emerged to balance the shuttle between home (the first place) and the workplace (the second place), providing a necessary anchor for community life and enabling the development of reciprocal social networks. While the significance of these "third places" is well recognised, the interplay between the physical characteristics of the space along with the spatiotemporal behaviours of individuals utilising these places is less well understood. This research draws on passively collected social sensing data and observation studies to explore the interaction between people and place within a large metropolitan university campus. Results suggest that behaviours in these third places vary markedly in response to the changing social environment as well as the more fixed physical and functional characteristics of the space.

This paper presents a new smartphone application, Wander, to capture high resolution space-time information on urban dwellers. We detail both the mechanism as well as the analytic platform through which broad scale spatial mobility studies can be mounted to reveal how individuals move through spaces and interact with the social and physical elements of urban life. Results demonstrate the utility of Wander for collecting spatial mobility data that for the first time enables empirical testing of theories first forwarded by urban sociologists at the turn of the 20th Century. We use data collected through the Wander application to examine the timing and regularity of spatial mobility patterns, how these are related to particular urban features, and differ by participant characteristics.

People with dementia (PWD) suffer from a constellation of progressive cognitive issues, with memory problems being the most frequent reasons for admission to residential nursing facilities. Global healthcare systems are shifting to ones that are predictive, preventive, personalized and participatory (P4). A key challenge is how to generate effective patient-activated social networks centred on the requirements and opportunities of P4 medicine.

This paper explores the use of geospatial-based social media networks, providing recommendations and assistance, facilitating a broader network of help for PWD than is currently provided by the immediate friends, family and care givers. Smartphones and location-based social networking technologies can create an additional layer of interaction from a broader community network providing support for the PWD for decision making and condition monitoring.

We focus on ways to enhance our understanding of interactions between people, specifically community participation, knowing when and how to call on the different networks for help and advice. This is supported by the use of human geography models and knowledge of memory problems to develop user profiles for PWD that can be predictive and actionable. Monitoring and profiling will assist with the recommendations from the social network-based connections.