Aims and Scope:

Most of the massive ubiquitous networks in our day to day life are evolving in real time. Be it the network of persons, entities, genes, sensors or their combinations, they are inherently complex and evolving with nodes appearing, disappearing, associating and disassociating with each other as time flies. In fact, most real-life networks evolve in a wide variety of ways that lead to different kinds of evolution semantics. While a deep foundation has been developed in the past years on analytics on complex networks, relatively little progress has been made when considering evolving networks. The scalability issues also keep growing alongside networks. In the light of above complexities, this special session welcomes novel research about mining and analytics in networks that evolve over time. We are interested since foundation methods that make feasible the analysis of large dynamic networks, like distributed processing, streaming, incremental algorithms, sampling etc., until pattern mining and predictive modeling tasks on evolving networks, such as community detection and event mining. We also encourage submissions exploring applications over evolving network data. The objective of this special session is to bring together researchers from different communities in this emerging topic.

Topics of Interest:

This special session is intended to attract researchers who are actively engaged in theoretical, technical and application oriented aspects of Evolving networks. The topics include, but are not limited to the following:

• Evolutionary network analysis
• Social networks and social media
• Graph data analytics
• Sampling from evolving networks
• Network data mining
• Distributed network analysis and mining
• Statistical techniques for network analysis and mining
• Temporal and streaming networks
• Predictive modeling on evolving networks
• Change detection, anomaly detection
• Incorporating network content in evolution analysis
• Community detection in evolving networks

Submission:

Please follow the special session papers guidelines. Submissions will be handled through EasyChair.

Overview:

• Conference paper submissions should be limited to a maximum of 10 pages, in the IEEE 2-column format.
• All paper submissions should be prepared for Double Blind reviewing. That is neither the reviewers are revealed nor the author information is disclosed.
• All accepted papers will be published by IEEE and included in the IEEE Xplore Digital Library. The conference proceedings will be submitted for EI indexing through INSPEC by IEEE.
• Top quality papers accepted and presented at the conference will be selected for extension and invited to the special issues of International Journal of Data Science and Analytics (JDSA, Springer).

Session Chairs

• Pedro Ribeiro (University of Porto, Portugal)
  pribeiro [at] dcc.fc.up.pt
• Shazia Tabassum (University of Porto, Portugal)
  shtb [at] inesctec.pt
• Fabíola S. F. Pereira (Federal University of Uberlândia, Brazil)
  fabiola.pereira [at] ufu.br
• Mário Cordeiro (University of Porto, Portugal)
  pro11001 [at] fe.up.pt

Program Committee

• Bruno Travençolo (Federal University of Uberlândia, Brazil)
• Muhammad Ajmal Azad (Newcastle University, UK)
• Orestis Kostakis (Aalto University, Finland)
• Jianpeng Zhang (Eindhoven University of Technology, Netherlands)
• Luis E. C. Rocha (Karolinska Institutet, Sweden)
• João Gama (University of Porto, Portugal)
• Salisu Abdulrahman (LIADD, INESC-TEC Porto, Portugal)
• Ricardo Sousa (LIADD, INESC-TEC Porto, Portugal)
• Carlos Ferreira (LIADD, INESC-TEC Porto, Portugal)