Selected papers from The 7th International Conference on Complex Networks and Their Applications

A special issue of Future Internet (ISSN 1999-5903).

Deadline for manuscript submissions: closed (10 April 2019) | Viewed by 10497

Special Issue Editors


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Guest Editor
University of Lyon 2, Lyon, France
Interests: information systems agility and big data management with applications on information systems and smart cities

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Guest Editor
Department of Computer Science, University of Milan, 20122 Milan, Italy
Interests: internet of people, things, and computers
Dalian University of Technology, China
Interests: data science, knowledge management, network science, mobile social networks
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Special Issue Information

Dear Colleagues,

The International Conference on Complex Networks and Their Applications brings together researchers from different scientific communities working on areas related to data and network science. The variety of scientific topics ranges from network and graph theory; statistical mechanics; models of networks; community structure; geometry; visualization; financial and economic networks; social and urban networks; human behavior; epidemic models; political networks; earth sciences applications; control and synchronization; resilience and robustness; machine learning; other fields of computer science, network medicine, and neuroscience, and many others. For the seventh edition of this annual event, 421 contributions have been received from 50 countries around the world. The papers invited for submission to this Special Issue are technically beyond the scope of the contributions appearing in the conference  proceedings and include significantly new material. They reflect the latest problems, advances, and diversity within the complex network community. 

Dr. Hocine Cherifi
Dr. Chantal Cherifi
Dr. Christian Quadri
Dr. Feng Xia
Guest Editors

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Keywords

  • Models of complex networks
  • Structural network properties
  • Complex networks and epidemics
  • Community structure and discovery
  • Motif discovery
  • Complex networks mining
  • Dynamics on and of complex networks
  • Link prediction
  • Multiplex networks
  • Network controllability
  • Synchronization in networks
  • Algorithms for network analysis
  • Networks visual representation
  • Large-scale graph analytics
  • Social reputation, influence, and trust
  • Information spreading in social media
  • Rumor and viral marketing
  • Recommendation systems and networks
  • Financial and economic networks
  • Complex networks and mobility
  • Biological and technological networks
  • Mobile call complex networks
  • Bio-informatics and earth sciences applications
  • Resilience and robustness
  • Networks for physical infrastructures
  • Networks, smart cities, and smart grids
  • Political networks
  • Supply chain networks
  • Complex networks and information systems
  • Complex networks and CPS/IoT
  • Graph signal processing
  • Cognitive network science

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Published Papers (1 paper)

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Research

14 pages, 2019 KiB  
Article
Epidemic Spreading in Urban Areas Using Agent-Based Transportation Models
by Jürgen Hackl and Thibaut Dubernet
Future Internet 2019, 11(4), 92; https://doi.org/10.3390/fi11040092 - 8 Apr 2019
Cited by 70 | Viewed by 9772
Abstract
Human mobility is a key element in the understanding of epidemic spreading. Thus, correctly modeling and quantifying human mobility is critical for studying large-scale spatial transmission of infectious diseases and improving epidemic control. In this study, a large-scale agent-based transport simulation (MATSim) is [...] Read more.
Human mobility is a key element in the understanding of epidemic spreading. Thus, correctly modeling and quantifying human mobility is critical for studying large-scale spatial transmission of infectious diseases and improving epidemic control. In this study, a large-scale agent-based transport simulation (MATSim) is linked with a generic epidemic spread model to simulate the spread of communicable diseases in an urban environment. The use of an agent-based model allows reproduction of the real-world behavior of individuals’ daily path in an urban setting and allows the capture of interactions among them, in the form of a spatial-temporal social network. This model is used to study seasonal influenza outbreaks in the metropolitan area of Zurich, Switzerland. The observations of the agent-based models are compared with results from classical SIR models. The model presented is a prototype that can be used to analyze multiple scenarios in the case of a disease spread at an urban scale, considering variations of different model parameters settings. The results of this simulation can help to improve comprehension of the disease spread dynamics and to take better steps towards the prevention and control of an epidemic. Full article
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