scholarly journals Knowledge Discovery from Social Graph Data

2016 ◽  
Vol 96 ◽  
pp. 682-691 ◽  
Author(s):  
Peter Braun ◽  
Alfredo Cuzzocrea ◽  
Carson K. Leung ◽  
Adam G.M. Pazdor ◽  
Kimberly Tran
Keyword(s):  
Knowledge Discovery ◽  
Social Graph ◽  
Graph Data

KD-FGS: A Knowledge Discovery System from Graph Data Using Formal Graph System

1999 ◽  
pp. 438-442 ◽  
Author(s):  
Tetsuhiro Miyahara ◽  
Tomoyuki Uchida ◽  
Tetsuji Kuboyama ◽  
Tatsuya Yamamoto ◽  
Kenichi Takahashi ◽  
...  
Keyword(s):  
Knowledge Discovery ◽  
Graph Data ◽  
Discovery System ◽  
Graph System

Resisting re-identification mining on social graph data

2018 ◽  
Vol 21 (6) ◽  
pp. 1759-1771 ◽  
Author(s):  
Jianliang Gao ◽  
Qing Ping ◽  
Jianxin Wang
Keyword(s):  
Social Graph ◽  
Graph Data

Getting to know a new protocol in hypertension care

2020 ◽  
Vol 16 (1) ◽  
Author(s):  
Mona Lundin
Keyword(s):  
Blood Pressure ◽  
Digital Technology ◽  
Interaction Analysis ◽  
Medical Discourse ◽  
Graphical Form ◽  
Graph Data ◽  
Average Blood Pressure ◽  
Infrastructure Design

This study explores the use of a new protocol in hypertension care, in which continuous patient-generated data reported through digital technology are presented in graphical form and discussed in follow-up consultations with nurses. This protocol is part of an infrastructure design project in which patients and medical professionals are co-designers. The approach used for the study was interaction analysis, which rendered possible detailed in situ examination of local variations in how nurses relate to the protocol. The findings show three distinct engagements: (1) teasing out an average blood pressure, (2) working around the protocol and graph data and (3) delivering an analysis. It was discovered that the graphical representations structured the consultations to a great extent, and that nurses mostly referred to graphs that showed blood pressure values, which is a measurement central to the medical discourse of hypertension. However, it was also found that analysis of the data alone was not sufficient to engage patients: nurses' invisible and inclusion work through eliciting patients' narratives played an important role here. A conclusion of the study is that nurses and patients both need to be more thoroughly introduced to using protocols based on graphs for more productive consultations to be established. 

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