A5015087294- Mental Health Research Topics
- Internet Traffic Analysis and Secure E-voting
- Bipolar Disorder and Treatment
- Advanced Malware Detection Techniques
- Digital Mental Health Interventions
- Spam and Phishing Detection
- Access Control and Trust
- Manufacturing Process and Optimization
- Privacy-Preserving Technologies in Data
- Privacy, Security, and Data Protection
- Impact of Technology on Adolescents
- Peer-to-Peer Network Technologies
- Opinion Dynamics and Social Influence
- Complex Network Analysis Techniques
Leuphana University of Lüneburg
2011-2016
Community Research and Development Information Service
2013
Background Relapse prevention in bipolar disorder can be improved by monitoring symptoms patients' daily life. Smartphone apps are easy-to-use, low-cost tools that used to assess this information. To date, few studies have examined the usefulness of smartphone data for disorder. Objective We present results from a pilot test smartphone-based system, Social Information Monitoring Patients with Bipolar Affective Disorder (SIMBA), tracked mood, physical activity, and social communication 13...
Centrality is an important element of social network analysis (SNA) measuring the relative power and influence members a network. In face book-style online networks every member potentially able to communicate with everyone else within This has impact on centrality: derivable from (exclusive) connections graph reduced because must not necessarily follow links. this paper we propose new measure for centrality which reflects paradigm shift. It based connectedness but trust. We discuss...
Knowing about trust between members of an online social network (OSN) is essential for many applications. In this paper we propose and discuss methods deriving information within a by analyzing disclosure personal items. A formal model presented possible functions were analysed. We distinguish different types assess their privacy value. methodology calculating values provided.
For many intelligence and security applications it is important to know how close people in a network are. In online social networks (OSN) friendship links are frequently chosen basis for the analysis. this paper we show that can be misleading, if want what extent trust into each other. We also unveil hidden relations based on an analysis of exceptions privacy settings. furthermore discuss resulting options defeating crime terrorism as well associated privacy, civil liberty issues.