1 COMPLEX NETWORKS 2018 THE 7TH INTERNATIONAL CONFERENCE ON COMPLEX NETWORKS AND THEIR APPLICATIONS December 11 - 13, 2018 Cambridge, United Kingdom Dear Colleagues and Friends, It is a great pleasure to welcome you in Cambridge for the 7th edition of the International Conference on Complex Networks and Their Applications. Cambridge is an elegant city very well connected with the world, and it is a very inspiring place. Its University dates from 1231, i.e. it is the second-oldest university in the English-speaking world and the world's fourth-oldest surviving university. The University of Cambridge is consistently ranked among the foremost universities in the world. 118 Nobel Laureates, 11 Fields Medalists, 6 Turing Award winners and 15 British Prime Ministers have been affiliated with Cambridge as students, alumni, faculty or research staff. The Colleges also represent the lifestyle, some of them contain important piece of arts and provide the visitor with the opportunity of a truly interdisciplinary and multidisciplinary experience. The conference is hosted in the Department of Computer Science and Technology. It was founded in 1937 (as the Mathematical Laboratory) by John Edward Lennard- Jones who was well known among scientists for his work on intermolecular forces. The department led original pioneering works in building complete computers (the EDSAC was commissioned in 1949 and the EDSAC 2 in 1958). Former members of the department have introduced in Computer Science the first videogame, the ancestor of the ASCII code, the concept of subroutine, the pi calculus and several programming languages such as C++, raspberry pi and others. The Cambridge Diploma in Computer Science was the world's first taught course in computing, starting in 1953. We wish you a very productive conference. We are confident that you will benefit from its rich program with stimulating discussions and many opportunities of networking. Through our social events, you will also discover some aspects of Cambridge's culture. Our wish is that you will enjoy this conference, contribute effectively toward it and take back with you knowledge, experiences, contacts and happy memories of this 7th edition of the International Conference on Complex Networks and Their Applications. Welcome to Cambridge! Pietro Liò Luca Maria Aiello Jon Crowcroft Renaud Lambiotte University of Cambridge Nokia Bell Labs University of Cambridge University of Oxford 1 TABLE OF CONTENTS Conference Events 5 Tutorial: Jesús Gómez-Gardeñes – Network Epidemiology: From simple to 6 data-driven models Tutorial: Silvio Lattanzi – From micro to macro: ego-network analysis and 7 its applications Keynote Day 1: Aristides Gionis – Maximizing diversity in social networks 8 [Elsevier Online Social Networks and Media Lecture] Keynote Day 1: Vittoria Colizza – Vulnerability of networked host 9 populations to epidemics [Springer Applied Network Science Lecture] Keynote Day 1: Romualdo Pastor-Satorras – Effects of Social Influence on 10 Collective Motion Keynote Day 2: Heather Harrington - Topological data analysis for 11 investigation of dynamics and biological networks Keynote Day 2: Hernan Makse - Essential nodes and keystone species in 12 the brain, ecosystems and social systems [PLOS Lecture] Keynote Day 2: Markus Strohmaier - Network analysis literacy: a 13 socioinformatic approach Keynote Day 3: Donald Towsley - Motifs in Social Networks 14 [MDPI Future Internet Lecture] Keynote Day 3: Sune Lehmann - Measuring Social Networks with High 15 Resolution: What have we learned? Sessions Day 1 16 Lighting L1: Networks in Finance and Economics – Structural Network 18 Measures Poster P1: Biological Networks - Community Structure - Link Analysis and 19 Ranking Oral O1A: Diffusion and Epidemics 20 2 Oral O1B: Quantifying Success 20 Oral O1C: Network Neuroscience 21 Oral O2A: Link Analysis and Ranking 21 Oral O2B: Resilience and Control 22 Oral O2C: Ecological Networks and Food Webs 22 Poster P2: Diffusion and Epidemics - Modeling Human Behavior - Machine 23 Learning and Networks Oral O3A: Network Models 24 Oral O3B: Multilayer Networks 24 Oral O3C: Social Networks 25 Sessions Day 2 26 Lighting L2: Social Networks – Diffusion, Resilience and Control 28 Poster P3: Dynamics of/on Networks - Multilayer Networks - Network 29 Neuroscience Oral O4A: Network Models 30 Oral O4B: Machine Learning and Networks 30 Oral O4C: Networks in Finance and Economics 31 Oral O5A: Diffusion and Epidemics 31 Oral O5B: Community Structure 32 Oral O5C: Modeling Human Behavior 32 Poster P4: Network Analysis - Resilience and Control - Urban Systems and 33 Networks Oral O6A: Structural Network Measures 34 Oral O6B: Urban Systems and Networks 34 Oral O6C: Resilience and Control 35 Sessions Day 3 36 Lighting L3: Machine Learning and Networks - Network models 37 Poster P5: Network Models - Networks in Finance and Economics - Social 37 Networks 3 Oral O7A: Diffusion and Epidemics 39 Oral O7B: Community Structure 39 Oral O7C: Biological Networks 40 Oral O8A: Modeling Human Behavior 40 Oral O8B: Resilience and Control 41 Oral O8C: Link Analysis and Ranking 41 Oral O9A: Dynamics on/of Networks 42 Oral O9B: Social Networks 42 Oral O9C: Network Analysis 43 Social Events Lunch 44 Welcome Reception Day 1 45 Dinner Banquet Day 2 46 Program at a Glance all days 48 4 CONFERENCE EVENTS Monday, December 10th, 2010 13:00 – 15:30 Tutorial 1: Jesús Gómez-Gardeñes 16:00 – 18:30 Tutorial 2: Silvio Lattanzi Tuesday, December 11th, 2018 08:45 – 09:00 Opening 09:00 – 09:35 Keynote Speaker: Aristides Gionis 10:30 – 11:05 Keynote Speaker: Vittoria Colizza 16:55 – 17:30 Keynote Speaker: Romualdo Pastor-Satorras 20:00 – 22:00 Welcome Reception Wednesday, December 12th, 2018 08:45 – 09:20 Keynote Speaker: Heather Harrington 10:15 – 10:50 Keynote Speaker: Hernan Makse 16:55 – 17:30 Keynote Speaker: Markus Strohmaier 20:00 – 22:00 Dinner Banquet Thursday, December 13th, 2018 08:45 – 09:20 Keynote Speaker: Donald Towsley 16:25 – 17:00 Keynote Speaker: Sune Lehmann 18:30 – 18:45 Closing Ceremony 5 MONDAY, DECEMBER 10th, 2018 Tutorials Jesús GÓMEZ-GARDEÑES University of Saragoza, Spain Jesus Gomez-Gardeñes is Associate Professor and head of the Group of Theoretical and Applied Modeling (GOTHAM) at the Institute of Biocomputation and Physics of Complex Systems (BIFI) of the University of Zaragoza (Spain). His main fields of research are statistical physics, nonlinear dynamics and the theory of complex networks. Within these disciplines he has mainly focused in the study of the emergence of collective phenomena out of nonlinearity and the structure of interactions in complex systems. Along these lines he has studied some paradigmatic problems such as energy localization, synchronization, random walks, traffic congestion, disease propagation and evolutionary dynamics. He has authored more than 100 scientific articles in international journals, including Nature Physics, PNAS, Physical Review Letters, Physics Reports, Science Advances, Nature Human Behavior among others. In the recent years he has focused on the study of multilayer networks and network epidemiology. Network Epidemiology: From simple to data-driven models In this tutorial we will deal with a topic that has advanced enormously in the recent decades thanks to contribution of network science: the modeling of epidemics. We will begin by reviewing the building blocks of the broad field of theoretical epidemiology: the compartmental models. From this point, we will progressively add ingredients aimed at capturing the real patterns of connectivity (networks) and mobility (metapopulations) observed in real societies. Finally, after analyzing the behavior of these models from the theoretical point of view, we will address the current challenges of epidemics prediction and the design of containment strategies. Chair: Sarah Morgan 6 Silvio LATTANZI Google Research Europe, Switzerland Silvio Lattanzi is a Research Scientist at Google Research Europe since April 2017. Before he was in the NY Algorithm group at Google New York from January 2011 to March 2017. He received my PhD from Sapienza University of Rome under the supervision of Alessandro Panconesi. During his PhD he interned twice at Google and once at Yahoo! Research. His research interests are in the areas of algorithms, machine learning and information retrieval. From micro to macro: ego-network analysis and its applications Detecting the clustering structure of real-world networks has emerged as an important primitive in a wide range of data analysis tasks such as community detection, event detection, spam detection, computational biology, link prediction and many others. As a result, the study of the topology of real world networks and of their clustering (or community) structure is central in modern network analysis. In particular, in recent years, several models have been introduced to capture the community structure of social networks and numerous empirical studies analyzed the community structures at a macroscopic and microscopic levels. One of the main observations in this line of work is the lack of a clear macroscopic community structure in real world networks. In sharp contrast with these findings, it has been observed that while the community detection problem is hard at a macroscopic level, it becomes simple at a microscopic level. This is especially true when we restrict our attention to local structures know as ego-nets (a.k.a. ego-networks) which consist of the subgraph induced over the neighborhood of a single node in the graph. Intuitively,