Faouzi Kamoun, Sofien Gharbi and Ali Amine Ghazeli
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…
Abstract
Purpose
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).
Design/methodology/approach
The paper uses systems development as a design science research methodology to construct a conceptual framework and then design and prototype a recommender system.
Findings
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.
Research limitations/implications
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.
Practical implications
When examined through the lenses of socio-emotional and neighborhood theories, this research opens new opportunities to develop supportive social networks for older people.
Social implications
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.
Originality/value
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.