M
Mark Kibanov
Researcher at University of Kassel
Publications - 21
Citations - 291
Mark Kibanov is an academic researcher from University of Kassel. The author has contributed to research in topics: Ubiquitous computing & Social computing. The author has an hindex of 10, co-authored 21 publications receiving 272 citations.
Papers
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Journal ArticleDOI
Temporal evolution of contacts and communities in networks of face-to-face human interactions
TL;DR: This article analyzes the evolution of contacts and communities over time to consider the stability of the respective communities and assess different factors which have an influence on the quality of community prediction.
Journal ArticleDOI
Ubicon and its applications for ubiquitous social computing
Martin Atzmueller,Martin Becker,Mark Kibanov,Christoph Scholz,Stephan Doerfel,Andreas Hotho,Bjoern-Elmar Macek,Folke Mitzlaff,Juergen Mueller,Gerd Stumme +9 more
TL;DR: The architecture of the Ubicon platform, its applications, and a large spectrum of analysis results are summarized and the implementation of the framework is exemplified using four real-world applications built on top of Ubicon.
Proceedings ArticleDOI
Ubicon: Observing Physical and Social Activities
Martin Atzmueller,Martin Becker,Stephan Doerfel,Andreas Hotho,Mark Kibanov,Bjoern-Elmar Macek,Folke Mitzlaff,Juergen Mueller,Christoph Scholz,Gerd Stumme +9 more
TL;DR: This paper describes data mining methods for ubiquitous and social data, specifically focusing on physical and social activities, and provides exemplary analysis results and gives an overview on the Ubicon platform which provides a framework for the creation and hosting of ubiquitous andsocial applications for diverse tasks and projects.
Journal ArticleDOI
Mining social media to inform peatland fire and haze disaster management
TL;DR: It is demonstrated that social media are a valuable source of complementary and supplementary information for haze disaster management by showing how Twitter data reveal changes in users’ behavior during severe haze events.
Is Web Content a Good Proxy for Real-Life Interaction?
TL;DR: This paper investigates whether relations captured by online social networks can be used as a proxy for the relations in offline social networks, such as networks of human face-to-face (F2F) proximity and coauthorship networks.