Dynamic Social Network Analysis with Heterogeneous Sensors in Ambient Environment

This paper presents our vision of large-scale, dynamic social network analysis in real environments, which we expect to be enabled by the introduction of large-scale heterogeneous sensors in the ambient environment. We address challenges in realizing large-scale dynamic social network analysis in real environments, and discuss several promising applications. Moreover, we present our design and implementation of a prototype system for quasi-realtime social network construction. We finally present preliminary experimental results of dynamic social network analysis for six-person social gatherings in a real environment, and discuss the feasibility of dynamic social network analysis and its effectiveness.

Exploring the structure of social media application-based information-sharing clinical networks in a community in Japan using a social network analysis approach

Objective Currently,use of social networking services(SNSs)for interprofessional collaboration is increasing.However,few studies have reported on virtual interprofessional interactions in community healthcare services.Revealing such structural characteristics of the networks can provide insight into the functions of the interprofessional information-sharing network and lead to smoother collaboration.Thus,we aimed to explore the structure of SNS-based information-sharing clinical networks.Design Social network analysis(SNA).Setting We selected a community in City X in Japan.Data collection We analysed SNS-based information-sharing clinical network data linked to patients receiving home medical care or care services between January and December 2018.A network was created for each patient to allow healthcare professionals to post and view messages on the web platform.In the SNA,healthcare professions registered in a patient group were represented as nodes,and message posting/viewing relationships were represented as links in the patient network.We investigated the structural characteristics of the target networks using several measures for SNA,including indegree centrality and outdegree centrality,which reflect the number of incoming and outgoing links to/from a node,respectively.Additionally,the professions forming the most central nodes were investigated based on their ranking to identify those with a central role in the networks.Finally,to compare the networks of nursing care levels 1-3(lighter care requirement)and those with nursing care levels 4-5(heavier care requirement),we analysed the structural differences in the networks and investigated the roles of healthcare professionals using centrality measures of nodes.Results Among 844 groups,247 groups with any nursing care level data were available for analysis.Increasing nursing care level showed higher density,reciprocity and lower centralisation.Healthcare professions with high indegree centrality(physicians,care workers and physical therapists)differed from those with high outdegree centrality(home care workers,physical therapists,and registered dieticians).Visiting nurses and nurses in the clinic played a central role,but visiting nurses tended to have higher indegree and outdegree centrality,while nurses in the clinic had higher closeness and betweenness centrality in networks with heavier care requirement.Conclusion The SNS-based information-sharing clinical network structure showed that different professions played some form of a central role.Associations between network structures and patient outcomes,cost effectiveness and other factors warrant further investigation.