Grounded in the socio-emotional selectivity theory, the purpose of this paper is to develop a people recommender and social matching system that better serves the information needs of older people on social networking sites or services (SNSs).
The paper uses systems development as a design science research methodology to construct a conceptual framework and then design and prototype a recommender system.
The research demonstrates that it is possible to exploit Google Maps-based interfaces, coupled with historical geo-temporal information, to develop a recommender system on SNSs that can empower older adults to reconnect with past acquaintances.
The proposed system is an advanced prototype that has been tested using simulated data sets as opposed to real-life data involving actual end-users through field studies.
When examined through the lenses of socio-emotional and neighborhood theories, this research opens new opportunities to develop supportive social networks for older people.
The paper promotes a better social engagement and contributes to the mental and physical health of older people, which can act as a shield against loneliness, anxiety and depression.
The paper uses Google Maps interfaces and the concept of geo-temporal proximity indices to build an “elder-friendly” recommender system that can assist older people to reconnect with past friends, neighbors and colleagues.
