Abstract
The social environment of people is an important factor for the mental health. However, in many internet interventions for mental health the interaction with the environment has no explicit role. It is known that the social environment can help people to reduce the feelings of loneliness and has a positive impact on mood in particular. Participation in social activities and maintaining social interaction with friends and relatives are frequently seen as indicators of a happy and healthy life. It is also commonly accepted that being integrated in social network has a strong protective effect on health and helps to avoid feelings of loneliness. In this paper we present a computational model that can be used for analyzing and predicating the mood level of individuals by taking into account the social integration, the participation in social activities and the enjoyableness of those activities. In addition to this, we explain the method that we developed to validate the computational model. For the validation, we use real EMA data that was collected from E-COMPARED project. This model allows to make more precise predictions on the effect of social interaction on mood and might be part of future internet interventions.
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Funding for this research work is provided by the E-COMPARED project. The E-COMPARED project is funded by the European Commission’s Seventh Framework Programme, under grant number 603098.
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Abro, A.H., Klein, M.C.A. (2016). Validation of a Computational Model for Mood and Social Integration. In: Spiro, E., Ahn, YY. (eds) Social Informatics. SocInfo 2016. Lecture Notes in Computer Science(), vol 10047. Springer, Cham. https://doi.org/10.1007/978-3-319-47874-6_27
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DOI: https://doi.org/10.1007/978-3-319-47874-6_27
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