Complex Networks 2018 the 7Th International Conference on Complex Networks and Their Applications

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

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

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

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

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

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

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, this happens because, even if a node is part of many communities, if we restrict our attention to a node and one of her neighbors, there is only one or a limited number of communities in which the two nodes interact, which present a clearer structure at the level of the neighborhood. In this talk we will first present this phenomenon then we will discuss how to analyze ego- networks at scale and finally describe few applications of ego-network analysis.

Chair: Sarah Morgan

TUESDAY, DECEMBER 11th, 2018

Keynote Speakers Aristides GIONIS Aalto University, Finland Aristides Gionis is a professor in the department of Computer Science in Aalto University. His previous appointments include being a visiting professor in the University of Rome and a senior research scientist in Yahoo! Research. He is currently serving as an action editor in the Data Management and Knowledge Discovery journal (DMKD), an associate editor in the ACM Transactions on Knowledge Discovery from Data (TKDD), and an associate editor in the ACM Transactions on the Web (TWEB). He has contributed in several areas of data science, such as algorithmic data analysis, web mining, social-media analysis, data clustering, and privacy-preserving data mining. His current research is funded by the Academy of Finland (projects Nestor, Agra, AIDA) and the European Commission (project SoBigData). Maximizing diversity in social networks Online social media are a major venue of public discourse today, hosting the opinions of hundreds of millions of individuals. Social media are often credited for providing a technological means to break information barriers and promote diversity and democracy. In practice, however, the opposite effect is often observed: users tend to favor content that agrees with their existing world-view, get less exposure to conflicting viewpoints, and eventually create "echo chambers" and increased polarization. Arguably, without any kind of moderation, current social- media platforms gravitate towards a state in which net-citizens are constantly reinforcing their existing opinions. In this talk we present our ongoing line of work on analyzing and moderating online social discussions. We first consider the questions of detecting controversy using network structure and content. We then address the problem of designing algorithms to break filter bubbles, reduce polarization, and increase diversity. We discuss a number of different strategies such as user and content recommendation, as well as approaches based on information cascades. Elsevier Online Social Networks and Media Lecture

Vittoria COLIZZA Inserm, France Dr. Vittoria Colizza is Director of Research at Inserm (French National Institute of Health and Medical Research) & Sorbonne University, Faculté de Médecine, Paris, France. She leads the EPIcx lab within the Pierre Louis Institute of Epidemiology and Public Health. Her work focuses on real episodes of human and animal epidemics to gather context epidemic awareness and provide risk assessment analyses for preparedness, mitigation, and control. Her research also includes more theoretical approaches for the modeling of small- to large-scale diffusion events where contacts between hosts and their mobility are explicitly considered from data. Colizza received several awards, including the Erdős–Rényi Prize by the Network Science Society in 2017. She also served as Young Advisor to the Vice President of the European Commission Mrs. Neelie Kroes for the Digital Agenda for Europe. Vulnerability of networked host populations to epidemics Our understanding of communicable diseases prevention and control is rooted in the theory of host population transmission dynamics. The network of host-to-host contacts along which transmission can occur drives the epidemiology of communicable diseases, determining how quickly they spread and who gets infected. A large body of epidemiological, mathematical and computational studies has provided a number of insights into the understanding of the process and the identification of efficient control strategies. The explosion of time resolved contact data has however opened the stage to new challenges. What are the structural and temporal aspects, and possibly their non-trivial interplay, that are critical for disease spread? To answer this question, I will introduce the infection propagator approach, a theoretical analytical framework for the assessment of the degree of vulnerability of a host population to disease epidemics, once we account for the time variation of its contact pattern. By reinterpreting the tensor formalism of multilayer networks, this approach allows the analytical computation of the epidemic threshold for an arbitrary time-varying network of host contacts, i.e. the critical pathogen transmissibility above which large-scale propagation occurs. I will apply this framework to a set of empirical time-varying contact networks and show how it can be used to test different intervention strategies for infection prevention and control in realistic settings.

Springer Applied Network Science Lecture

Romualdo PASTOR-SATORRAS Universitat Politècnica de Catalunya, Spain Romualdo Pastor-Satorras (Barcelona, Spain, 1967) received a PhD in Condensed Matter Physics from the Universitat de Barcelona in 1995. He spent four years as postdoctoral researcher at the Massachusetts Institute of Technology (1996-1998) and The Abdus Salam International Centre for Theoretical Physics, ICTP (1998- 2000). At present, he is Associate Professor of Applied Physics at the Universitat Politècnica de Catalunya since 2006. He has been visiting scientist at, among others, Yale University (USA), the University of Notre Dame (USA), the Kavli Institute for Theoretical Physics (USA), the Helsinky University of Technology TKK (Finland), Indiana University (USA) and the Institute for Scientific Interchange (ISI) Foundation (Italy). He has been awarded twice with the national “ICREA Academia Prize” by the Government of Catalonia. He has published more than 100 publications in peer- reviewed journals in the field of statistical physics, and is author of the book “Evolution and Structure of the Internet” (Cambridge University Press, 2007), together with Professor Alessandro Vespignani. Effects of Social Influence on Collective Motion Collective motion in animals is able to produce such stunning patterns as flocks of birds turning in unison or shoals of fish splitting and reforming while outmaneuvering a predator. The study of these phenomena is mainly based in simple models, a paradigmatic example being the one proposed by Vicsek and collaborators in the 90s. The main assumption of this and similar models is that individuals tend to orient their velocity parallel to the average velocity of their local neighborhood. The Vicsek model predicts a phase transition between an ordered phase, with individuals travelling in a common direction, and a disordered one, that has been recently the subject of a large interest in the statistical mechanics community. Here we will consider variations of the Vicsek model incorporating social interactions between individuals, represented in terms of a complex social network. The main result of the numerical study of this model is the observation that the heterogeneity of the social network can increase the resilience of the ordered state, making it immune to external perturbations. A related scalar version of the Vicsek model in networks allows for a mathematical treatment that lends support to the numerical observations, and allows for further generalizations.

WEDNESDAY, DECEMBER 12th, 2018

Keynote Speakers Heather HARRINGTON Oxford University, UK Prof. Heather Harrington is a Royal Society University Research Fellow and Associate Professor in the Mathematical Institute at the University of Oxford. She is Co-Director of the Centre for Topological Data Analysis. Her research focuses on the problem of reconciling models and data by extracting information about the structure of models and the shape of data. To develop these methods, Prof Harrington integrates techniques from a variety of disciplines such as computational algebraic geometry and topology, statistics, optimisation, network theory, linear algebra, and dynamical systems. Based on this research, she was recently awarded a London Mathematical Society Whitehead Prize.

Topological data analysis for investigation of dynamics and biological networks Persistent homology (PH) is a technique in topological data analysis that allows one to examine features in data across multiple scales in a robust and mathematically principled manner, and it is being applied to an increasingly diverse set of applications. We investigate applications of PH to dynamic biological networks with concrete examples from contagions, neuroscience, and blood vessels.

Hernan MARKSE City College of New York, USA Prof. Hernan Makse leads the Complex Networks and Data Science Lab of at the Levich Institute and Department of Physics of City College of New York in New York City.Hernan research focuses on the theoretical understanding of Complex Systems from a Statistical Physics viewpoint. He is working towards the development of new emergent laws for complex systems, ranging from brain networks to biological networks and social systems. Treating these complex systems from a unified theoretical approach, he uses concepts from statistical mechanics, network and optimization theory, machine learning, and big-data science to advance new views on complex systems and networks.

Essential nodes and keystone species in the brain, ecosystems and social systems Identifying essential nodes in complex networks is a central problem for biological systems to social systems. We treat this problem in three paradigmatic cases: the brain, ecosystems and social networks. Mathematically, we find the set of influential nodes by optimizing the damage to the giant connected component with systematic inactivation of nodes. We then apply network theory and pharmacogenetic interventions in a rat brain to predict and target essential nodes responsible for global integration in a model of learning and memory. We find that the integration of the brain network is mediated by a set of weak nodes through optimization of influence in optimal percolation. Pharmacogenetic inhibitions confirm the theoretical predictions. We discuss the relevance of these influencers to ecological systems dominated by abrupt first order tipping points as well as connectomes with regularities.

PLOS Lecture

Markus STROHMAIER RWTH Aachen University, Germany Markus Strohmaier is the Professor for Methods and Theories of Computational Social Sciences and Humanities at RWTH Aachen University (Germany), and the Scientific Coordinator for Digital Behavioral Data at GESIS - Leibniz Institute for the Social Sciences. Previously, he was a Post-Doc at the University of Toronto (Canada), an Assistant Professor at Graz University of Technology (Austria), a visiting scientist at (XEROX) Parc (USA), a Visiting Assistant Professor at Stanford University (USA) and the founder and scientific director of the department for Computational Social Science at GESIS (Germany). He is interested in applying and developing computational techniques to research challenges on the intersection between computer science and the social sciences / humanities.

Modeling minorities in social networks Homophily can put minority groups in social networks at a disadvantage by restricting their ability to establish links with people from a majority group. This can limit the overall visibility of minorities in the network, and create biases. In this talk, I will show how the visibility of minority groups in social networks is a function of (i) their relative group size and (ii) the presence or absence of homophilic behavior. In addition, the results show that perception biases can emerge in social networks with high homophily or high heterophily and unequal group sizes, and that these effects are highly related to the asymmetric nature of homophily in networks. This work presents a foundation for assessing the visibility of minority groups and corresponding perception biases in social networks in which homophilic or heterophilic behaviour is present.

THURSDAY, DECEMBER 13th, 2018

Keynote Speakers Donald TOWSLEY UMass Amhrest, USA Professor Towsley's research spans a wide range of activities from stochastic analyses of queueing models of computer and telecommunications to the design and conduct of measurement studies. He has performed some of the pioneering work on the exact and approximate analyses of parallel/distributed applications and architectures. More recently, he pioneered the area of network tomography and the use of fluid models for large networks. He has published extensively, with over 150 articles in leading journals. Towsley is the recipient of one of the IEEE's most prestigious honors, the 2007 IEEE Koji Kobayashi Computers and Communications Award. Motifs in Social Networks Complex networks that occur in nature and engineering, often exhibit simple, network structural properties, or “motifs.” Network motifs refer to recurring, significant patterns of interaction between sets of nodes and represent basic building blocks of graphs. Motifs in social networks exhibit spatial patterns and temporal patterns that vary according to the type of network. This talk reports on these variations across several network types and identify several common substructures. Reciprocity of directed ties occurs much more frequently than expected by chance in all networks. Similarly, we find that completely connected triads and tetrads (i.e., four-node sub-graphs) occur more often than expected, highlighting the tendency of actors to form clusters of ties. We also identify motifs that suggest patterns of hierarchy. Motifs are also useful for the purpose of subgraph classification. We demonstrate their value in identifying the type of network that a sub-graph belongs to. We also consider the challenge of characterizing motifs in large graphs, and show how carefully designed sampling algorithms can accurately characterize them using a small number of samples. Last, we close with open problems regarding motifs whose solution can lead to better understanding of social networks and analytical tools for characterizing them. MDPI Future Internet Lecture

Sune LEHMANN Technical University of Denmark, Denmark

Sune Lehmann is an associate professor at the Technical University of Denmark, an adjunct (full) professor at University of Copenhagen's Department of Sociology, and an adjunct associate professor at the Niels Bohr Institute (Department of Physics, University of Copenhagen). Sune is the associate director of the Center for Social Data Science at University of Copenhagen. Sune's work focuses on the dynamics of complex networks as well as processes unfolding on such evolving networks. He is the author of multiple highly cited papers and his work has received world-wide press coverage.

Measuring Social Networks with High Resolution: What have we learned? In other to understand the multi-layered and dynamic social interactions within a large social system, I equipped 1000 freshmen students at the Technical University of Denmark with top-of-the-line smartphones running custom software designed to collect interactions mediated through face-to-face meetings (proximity estimated via Bluetooth), telecommunication (phone-calls, text messages), and online social networks (Facebook friendships and interactions). The phones also collected geo- locations, wifi-signals, and a number of other data channels; participants also answered paneled questionnaires regarding personality, study habits, and health- related behavior. The data collection lasted 2.5 years. Through this rich dataset, we have learned about much more than social networks. In my talk, I will discuss key findings from this study, with an emphasis on communities in dynamic networks and recent results on human mobility.

TUESDAY, DECEMBER 11th, 2018

Program at a Glance Day 1

08:00 Registration 08:45 Opening 09:00 Keynote Speaker: Aristides GIONIS Elsevier Online Social Networks and Media Lecture Chair: Luca Maria Aiello 09.35 Lighting L1: Networks in Finance and Economics – Structural Network Measures Chair: Huijuan Wang 10:30 Keynote Speaker: Vittoria COLIZZA Springer Applied Network Science Lecture Chair: Jesus Gómez-Gardeñes 11:05 Poster P1: Biological Networks Community Structure Link Analysis and Ranking Chair: Giovanna Maria Dimitri Coffee Break 11:45 Oral O1A Oral O1B Oral O1C Diffusion and Quantifying Success Network Epidemics Neuroscience Chair: Piet Van Chair: Noshir Chair: Mario Mieghem Contractor Ventresca 13:15 Lunch 14:45 Oral O2A Oral O2B Oral O2C Link Analysis and Resilience and Ecological Networks Ranking Control and Food Webs Chair: Francisco Chair: Luis M. Rocha Chair: Samuel Aparecido Rodrigues Johnson 16:15 Poster P2: Diffusion and Epidemics Modeling Human Behavior Machine Learning and Networks Chair: Christian Quadri Coffee Break

16:55 Keynote Speaker: Romualdo PASTOR-SATORRAS Chair: Carlo Vittorio Cannistraci 17:30 Oral O3A Oral O3B Oral O3C Network Models Multilayer Networks Social Networks

Chair: Michael Schaub Chair: Sergio Gómez Chair: Javier Borge- Holthoefer 19:00 Sessions end!

20:00 Welcome Reception

DETAILED PROGRAM DAY 1

08:00 Registration 08:45 Opening 09:00 Aristides GIONIS Maximizing diversity in social networks Elsevier Online Social Networks and Media Lecture Chair: Luca Maria Aiello 09:35 Lighting L1: Network in Finance and Economics [1-6] Structural Network Measures [7-10] Chair: Huijuan Wang 1. Tomomi Kito, Petter Holme. Triadic and quadratic closure as mechanisms for inter-firm transactional network dynamics 2. Akihiro Hamamoto, Tomomi Kito. Effects of industrial and geographical proximities of firms on the Japanese inter-firm network 3. Viviana Viña Cervantes, Michele Coscia, Renaud Lambiotte. Struggle for existence in the world economic ecosystem 4. Luis Ospina-Forero, Mihai Cucuringu, Gesine Reinert. Influence of network correlation structure in multivariate time series forecasting 5. Giovanni Bonaccorsi, Massimo Riccaboni, Giorgio Fagiolo, Gianluca Santoni. Finding the most central countries in the international exchange multiplex using the multirank 6. Juan Carlos Rocha Gordo, Jessica Gephart. How far does a shock event spreads on a network? Detecting causality on the salmon trade network 7. Michael Schaub, Marco Avella-Medina, Francesca Parise, Santiago Segarra. Centrality measures for graphons: Accounting for uncertainty in networks 8. Francesco Tudisco, Desmond Higham. Logistic core-periphery detection in networks 9. Zakariya Ghalmane, Mohammed El Hassouni, Chantal Cherifi and Hocine Cherifi. Centrality in Networks with Overlapping Communities 10. Matteo Cinelli, Leto Peel, Antonio Iovanella, Jean-Charles Delvenne. Network Constraints on the Mixing Patterns of Binary Node Metadata

10:30 Vittoria COLIZZA Vulnerability of networked host populations to epidemics Springer Applied Network Science Lecture Chair: Jesus Gómez-Gardeñes 11:05 Poster P1: Biological Networks [1-6] Community Structure [7-13] Link Analysis and Ranking [14-17] Chair: Giovanna Maria Dimitri 1. Bishnu Sarker, David W Ritchie, Sabeur Aridhi. Exploiting Complex Protein Domain Networks for Protein Function Annotation 2. William Grant, Sebastian Ahnert. Systematic identification of protein structure domains using Infomap and GLOSIM 3. Simone Marini, Danila Vella, Nelson Nazzicari, Riccardo Bellazzi. Gene-gene interaction module identification insingle-cell RNA sequencing 4. Nora S. Martin, Sebastian E. Ahnert. Identifying Dominant Connection Patterns in Protein Structure Networks 5. Chandrakala Meena, Pranay Deep Rungta, Sudeshna Sinha. Threshold-activated transport stabilizes chaotic populations to steady states 6. Damian Omar Ortiz-Rodríguez, Maarten J. van Strien, Antoine Guisan, Rolf Holderegger. Topological variables of habitat networks as predictors of species occurrence 7. Radek Marik, Tomas Zikmund. Overlapping Communities in Bipartite Graphs 8. Valérie Poulin, François Théberge. Ensemble Clustering for Graphs 9. Arya McCarthy, David Matula. Evaluating the leximin method for community detection 10. Mateusz Wilinski, Piero Mazzarisi, Daniele Tantari, Fabrizio Lillo. Detectability of Macroscopic Structures in Directed Networks: a Stochastic Block Model Approach 11. Valérie Poulin, François Théberge. Comparing Graph Clusterings: Set partition measures vs. Graph-aware measures 12. Hiroshi Okamoto, Xule Qiu. Community detection by modular decomposition of random walk 13. Yuichi Kichikawa, Hiroshi Iyetomi, Takashi Iino, Hiroyasu Inoue. Community Structure Based on Circular Flow in a Large-Scale

Transaction Network 14. Alessandro Muscoloni, Carlo Vittorio Cannistraci. A ‘dramatic truth’ in link prediction: SBM inference fails to effectively predict even the structure of synthetic networks generated with the SBM model 15. Laxmi Amulya Gundala, Francesca Spezzano. Link Prediction via Indirect Interaction Duration 16. Onuttom Narayan, Iraj Saniee. Scaling of random walk betweenness in networks 17. Clément Bertier, Farid Benbadis, Marcelo Dias de Amorim, Vania Conan. Centrality Maps for Moving Nodes 11:45 Oral O1A: Diffusion and Epidemics Chair: Piet Van Mieghem • Long Ma, Qiang Liu, Piet Van Mieghem. Inferring properties of the underlying network based on the epidemic prevalence • Gergely Szlobodnyik. Reachability analysis of discrete state epidemiological models • Istvan Kiss, Joel Miller, Peter Simon. Fast variables determine the epidemic threshold in the pairwise model with an improved closure • Ewan Colman, Petter Holme, Hiroki Sayama, Carlos Gershenson. Cost-efficient sentinel surveillance strategies for preventing epidemics on networks • Brennan Antone, Alina Lungeanu, Noshir Contractor. An Extension of Autologistic Actor Attribute Models for Multi- Attribute Influence Processes • Kuntal Dey, Hemank Lamba, Seema Nagar, Shubham Gupta, Saroj Kaushik. TopSPA: Modeling Topical Information Diffusion over Microblog Networks 11:45 Oral O1B: Quantifying Success Chair: Noshir Contractor • Cameron DeChurch, Noshir Contractor. Using Network Science to Discover the Grand Masters of the Florentine Renaissance • Donghyeok Choi, Juyong Park. Lifelong Career Success: Joseon Dynasty’s Bureaucrats • Christopher Spratt, Jun Hong, Kevin McAreavey, Weiru Liu. Community-Based Measures for Social Capital • Weihua Li, Tomaso Aste, Fabio Caccioli, Giacomo Livan. Reciprocity and success in academic careers • Yinon Nahum. Rich-Clubs in Preferential Attachment Networks

• Gyuhyeon Jeon, Juyong Park. Ties and Event Flow Network in Basketball 11:45 Oral O1C: Network Neuroscience Chair: Mario Ventresca • Erik Bollt, Jie Sun. Identifying the Coupling Structure in Complex Systems through the Optimal Causation Entropy Principle, Information Flow and Information Fragility • Ali Safari, Paolo Moretti. Robustness of hierarchical network organization in models of functional connectivity • Onerva Korhonen, Elisa Ryyppö, Jari Saramäki. Internal connectivity and topological roles of nodes in functional brain networks • Chengtao Ji, Natasha Maurits, Jos Roerdink. Comparison of Brain Connectivity Networks Using Local Structure Analysis • Caroline Garcia Forlim, Roma Siugzdaite, Yang Yu, Ye-Lei Tang, Wei Liao, Daniele Marinazzo. Functional connectivity hubs and thalamic hemodynamics in Rolandic Epilepsy • Sarah Morgan, Jonathan Young, Ameera Patel, Kirstie Whitaker, Cristina Scarpazza, Therese van Amelsvoort, Machteld Marcelis, Jim van Os, Gary Donohoe, David Mothersill, Aiden Corvin, Martijn van den Heuvel, Edward Bullmore, Michael Brammer. Can MRI brain networks reproducibly distinguish psychosis patients from control subjects? 13:15 Lunch 14:45 Oral O2A: Link Analysis and Ranking Chair: Francisco Aparecido Rodrigues • Riccardo Marcaccioli, Giacomo Livan. A parametric approach to information filtering in complex networks: The Pólya filter • Vincenza Carchiolo, Marco Grassia, Alessandro Longheu, Michele Malgeri, Giuseppe Mangioni. Long distance connections for ranking and robustness enhancement in networks • Aakash Sinha, Remy Cazabet, Remi Vaudaine. Systematic Biases in Link Prediction: comparing heuristic and graph embedding based methods • Chuankai An, James O'Malley, Daniel Rockmore. Walk Prediction in Directed Networks • Takayasu Fushimi, Kazumi Saito, Tetsuo Ikeda, Kazuhiro Kazama. A New Group Centrality Measure for Maximizing the

Connectedness of Network under Uncertain Connectivity • Alexander Schickedanz, Deepak Ajwani, Ulrich Meyer, Pawel Gawrychowski. Average-case behavior of k-shortest path algorithms 14:45 Oral O2B: Resilience and Control Chair: Luis M. Rocha • Giacomo Rapisardi, Giulio Cimini, Guido Caldarelli. Numerical assessment of the percolation threshold using complement networks • Richard La. Identifying Vulnerable Nodes to Cascading Failures: Centrality to the Rescue • Clara Pizzuti, Annalisa Socievole. A Genetic Algorithm for Enhancing the Robustness of Complex Networks through Link Protection • Louis Shekhtman, Shlomo Havlin. Resilience of Hierarchical Networks and Interdependent Hierarchical Networks • Madhav Marathe, S. S. Ravi, Daniel Rosenkrantz, Richard Stearns. Computational Aspects of Fault Location and Resilience Problems for Interdependent Infrastructure Networks • Gian Maria Campedelli, Iain Cruickshank, Kathleen M. Carley. Detecting Latent Terrorist Communities Testing a Gower's Similarity-based Clustering Algorithm for Multi-Partite Networks 14:45 Oral O2C: Ecological Networks Chair: Samuel Johnson • Albert Solé-Ribalta, Claudio Juan Tessone, Carlo Ferrari, Javier Borge-Holthoefer. High-order nested subsets and the structure of sites-species-species hypernetworks • Samuel Johnson. Trophic Structure of Directed Networks: Effects on Topology and Dynamics • Malbor Asllani, Renaud Lambiotte, Timoteo Carletti. The structure and dynamics of non-normal networks • Juan Fernandez-Gracia, Jorge P. Rodriguez, Lauren Peel, Konstantin Klemm, Mark Meekan, Victor M Eguiluz. Inferring social relations from presence data. Manta Rays case study • Gitanjali Yadav, Suresh Babu. Extinction Curves and Error Propagation in Mutualistic Ecological Networks: The Case of Frugivores in a Tropical Rainforest • Suresh Babu, Gitanjali Yadav. Robustness Through Regime Flips in Collapsing Ecological Networks

16:15 Poster P2: Diffusion and Epidemics [1-8] Modeling Human Behavior [9-13] Machine Learning and Networks [14-17] Chair: Christian Quadri 1. Qiang Liu, Piet Van Mieghem. Network localization is unalterable by infections in bursts 2. Jason Bassett, Inia Steinbach, H. K. Hartmut Lentz, Philipp Hoevel. Disease Risk Assessment of the German Cattle Trade Network: A Static and Temporal Network Analysis 3. Daniel Goldsmith, Yonah Shmalo, Yitzchak Shmalo. Reframing the Gossip Problem as Information Spreading over Complex, Dynamic Networks 4. Flavio Iannelli, Manuel Sebastian Mariani, Igor M Sokolov. ViralRank: A new metric for influencers identification 5. Diego Fregolente Mendes de Oliveira, Kevin S. Chan. The effects of trust and influence on the spreading of low and high quality information 6. Mei Yang, Bing Wang, Yuexing Han. Impacts of mutual selection in temporal networks on random walk process 7. Côme Billard. Cascading Technology in Networks 8. Md Arquam, Anurag Singh, Rajesh Sharma. Modelling and Analysis of Delayed SIR Model on Complex Network 9. Juergen Lerner, Alessandro Lomi. Let's talk about refugees: Network effects drive contributor attention to Wikipedia articles about migration-related topics 10. Dirk-Jan van Veen, Hans Rudolf Heinimann. Exploring Information Dissemination Strategies to Foster Collective Intelligence 11. Arkadiusz Jędrzejewski. Opinion spreading on complex networks with local and global interactions 12. Yan Leng, Xiaowen Dong, Alex Pentland. Learning Quadratic Games on Networks 13. Paulo Freitas Gomes, Sandro Martinelli Reia, Francisco Aparecido Rodrigues and José Fernando Fontanari. Mobility helps problem-solving systems to avoid Groupthink 14. Vahid Mirzaebrahim Mostofi, Sadegh Aliakbary. Towards quantitative methods to assess network generative models 15. Richa Tripathi, Amit Reza, Dinesh Garg. Prediction of the disease controllability in a complex network using machine learning algorithms

16. Warren Keil, Mehmet Aktas. Topological Data Analysis of Attribute Networks using Diffusion Frechet Function with Ego- Networks 17. Supriyo Mandal, Abyayananda Maiti. Explicit Feedbacks Meet with Implicit Feedbacks: A Combined Approach for Recommendation System 16:55 Romualdo PASTOR-SATORRAS Effects of Social Influence on Collective Motion Chair: Carlo Vittorio Cannistraci 17:30 Oral O3A: Network Models Chair: Michael Schaub • Tiago Peixoto. Reconstructing networks with unknown and heterogeneous errors • Alessandro Muscoloni, Carlo Vittorio Cannistraci. Minimum curvilinear automata with similarity attachment for network embedding and link prediction in the hyperbolic space • Ofer Biham, Eytan Katzav, Reimer Kuhn. The microstructure of the giant component in configuration model networks • Jan Treur. Mathematical Analysis of a Network’s Asymptotic Behaviour Based on its Strongly Connected Components • Gáspár Sámuel Balogh, Péter Pollner, Gergely Palla. A generalized class of thresholding functions for the hidden variable model of scale-free networks • Júlia Komjáthy, Roland Molontay, Károly Simon. Modified box dimension of trees and hierarchical scale-free graphs 17:30 Oral O3B: Multilayer Networks Chair: Sergio Gómez • Kwang-Il Goh. Majority-vote dynamics on multiplex networks • Lucas Lacasa. Multiplex decomposition of non-Markovian dynamics and the hidden layer reconstruction problem • Maria Angelica Araujo, Murilo S. Baptista. Extensivity in infinitely large multiplex networks • Hanjo Boekhout, Frank Takes, Walter Kosters. Counting Multilayer Temporal Motifs in Complex Networks • Roberto Interdonato, Raffaele Gaetano, Danny Lo Seen, Mathieu Roche. Extracting Multi-Layer Networks from Sentinel- 2 Satellite Image Time Series • Youssef Mourchid, Benjamin Renoust, Hocine Cherifi, Mohammed El Hassouni. Multilayer Network Model of Movie Scripts

17:30 Oral O3C: Social Networks Chair: Javier Borge-Holthoefer • Kuntal Dey, Ritvik Shrivastava, Saroj Kaushik, Kritika Garg. Assessing Topical Homophily on Twitter • Sameera Horawalavithana, Clayton Gandy, Juan Arroyo-Flores, John Skvoretz, Adriana Iamnitchi. Diversity, Homophily and the Risk of Node Re-identification in Labeled Social Graphs • Ecem Basak, Ali Tafti, Peng Huang. Network Topology and Tie Strength in Online Communities of Practice • Siddharth Pal, Feng Yu, Yitzchak Novik, Ananthram Swami, Amotz Bar-Noy. Quantifying the strength of the friendship paradox • Ross Schuchard, Andrew Crooks, Anthony Stefanidis, Arie Croitoru. Bots in Nets: Empirical Comparative Analysis of Bot Evidence in Social Networks • Ming-Hung Wang, Nhut-Lam Nguyen and Chyi-Ren Dow. Detecting Potential Cyber Armies of Election Campaigns Based on Behavioral Analysis

19:00 Sessions end!

20:00 Welcome Reception

22:00 Day ends!

WEDNESDAY, DECEMBER 12th, 2018

Program at a Glance Day 2

08:00 Registration 08:45 Keynote Speaker: Heather HARRINGTON Chair: Madhav Marathe 09.20 Lighting L2: Social Networks – Diffusion, Resilience and Control Chair: Chantal Cherifi 10:15 Keynote Speaker: Hernan MAKSE PLOS Lecture Chair: Pietro Liò 10:50 Poster P3: Dynamics on/of Networks Multilayer Networks Network Neuroscience Chair: Matteo Zignani Coffee Break 11:30 Oral O4A Oral O4B Oral O4C Network Models Machine Learning Networks in Finance and Networks and Economics Chair: Tiago Peixoto Chair: Frank Takes Chair: Yuchi Ikeda

13:15 Lunch 14:45 Oral O5A Oral O5B Oral O5C Diffusion and Community Structure Modeling Human Epidemics Behavior Chair: Kwang-Il Goh Chair: Gergely Palla Chair: Emoke Agnes Horvat 16:15 Poster P4: Network Analysis Resilience, Control and Synchronization Urban System and Networks Chair: Sarah Morgan Coffee Break

16:55 Keynote Speaker: Markus STROHMAIER Chair: Taha Yasseri

17:30 Oral O6A Oral O6B Oral O6C Structural Network Urban System and Resilience and Measures Networks Control Chair: Tsuyoshi Chair: Elsa Arcaute Chair: Richard La Murata 19:00 Sessions end! 20:00 Dinner Banquet

DETAILED PROGRAM DAY 2

08:00 Registration 08:45 Heather HARRINGTON Topological data analysis for investigation of dynamics and biological networks Chair: Madhav Marathe 09:20 Lighting L2: Social Networks [1-3] Diffusion, Resilience and Control [4-10] Chair: Chantal Cherifi 1. Fariba Karimi, Eun Lee, Claudia Wagner, Hang-Hyun Jo, Markus Strohmaier, Mirta Galesic. Homophily explains perception biases in social networks 2. Janos Török, Yohsuke Murase, Hang-Hyun Jo, Janos Kertesz, Kimmo Kaski. The homophily shows the Dunbar's number: modeling and data 3. Inés Caridi, Pablo Balenzuela. Topological study of the convergence in the Voter Model 4. Valerio Restocchi, Markus Brede, Sebastian Stein, Lewis Hill, Soheil Eshghi. Dynamic competitive opinion control: theory, simulations, and experiments 5. Reimer Kuehn, Tim Rogers. Heterogeneity in Percolation on Complex Networks 6. Hengda Yin, Raul Mondragon, Richard Clegg. Alternative routing maps with smaller search information 7. Somaye Sheykhali, Juan Fernandez-Gracia, Victor M Eguiluz. Co- occurrence plasticity increases modularity and stability in bipartite networks 8. Gergely Röst. Pairwise Approximations of Non-Markovian Network Epidemics 9. Ana Triana, Enrico Glerean, Jari Saramäki, Onerva Korhonen. Effects of spatial smoothing on group-level differences in functional brain networks 10. Giovanni Iacobello, Stefania Scarsoglio, Hans Kuerten, Luca Ridolfi. Temporal network-based analysis of turbulent mixing

10:15 Hernan MAKSE Essential nodes and keystone species in the brain, ecosystems and social systems PLOS Lecture Chair: Pietro Liò 10:50 Poster P3: Dynamics on/of Networks [1-8] Multilayer Networks [9-14] Network Neuroscience [15-18] Chair: Matteo Zignani 1. Steve Huntsman. A Markov model for inferring flows in directed contact networks 2. Yuting Feng, Zhisheng Duan, Guanrong Chen. Distributed PI control for multi-agent consensus tracking of heterogeneous networks with heterogeneous uncertainties 3. Mateusz I. Dubaniowski, Hans R. Heinimann. Time granularity in system-of-systems simulation of infrastructure networks 4. Eeti Jain, Anurag Singh, Rajesh Sharma. TTPROF: A Weighted threshold model for studying opinion dynamics in directed temporal network 5. Hadar Miller, Osnat Mokryn. Size Agnostic Change Point Detection Framework for Evolving Networks 6. Maria Grácio. Full-Commanding a network: the dictator 7. Jan Treur. Relating an Adaptive Social Network’s Structure to its Emerging Behaviour Based on Homophily 8. Jan Treur. Multilevel Network Reification: Representing Higher Order Adaptivity in a Network 9. Juan Carlos S. Herrera, Carolyn Dimitri. The Development of the Organic Dairy Supply Chain in the the U.S.A 2002-2015. A Network Science Approach. 10. Blaž Škrlj, Jan Kralj, Nada Lavrač. Py3plex: A library for scalable multilayer network analysis and visualization 11. Yasuyuki Nakamura, Koichi Yasuake, Keiya Ando, Takahiro Tagawa. Effects of Interaction and Learning Distance on Cooperation in Evolutionary Games on a Multiplex Network 12. Chen Chang, Yong Jie Niu, Guo Ji Kun. Structural Invulnerability Evaluation of Complex Multi-layer Emergency Logistics System Based on Interdependent Network Theory 13. Ho-Chun Herbert Chang, Feng Fu. Multiplex Complex Contagion Co-Diffusion

14. Angelika Schmid, Thomas Bock, Janet Siegmund, Sven Apel. Coordination in Open-Source Software Engineering - A Multiplex Network Analysis 15. Zalan Heszberger, Andras Majdan, Andras Gulyas, Tibor Gyimothy, Vilmos Bilicki, Jozsef Biro. Robust Navigable Cores in the Human Brain Networks 16. Roma Siugzdaite, Hannelore Aerts, Daniele Marinazzo. Communicalibity indicates structural and functional connectivity changes in children with autism spectrum disorder 17. Angela Lombardi, Nicola Amoroso, Domenico Diacono, Eufemia Lella, Roberto Bellotti, Sabina Tangaro. Age Related Topological Analysis of Synchronization-Based Functional Connectivity 18. Mario Ventresca. Using Algorithmic Complexity to Differentiate Cognitive States in fMRI 11:30 Oral O4A: Network Models Chair: Tiago Peixoto • Alessandro Muscoloni, Carlo Vittorio Cannistraci. Leveraging the nonuniform PSO network model as a benchmark for performance evaluation in community detection and link prediction • Saskia Metzler, Pauli Miettinen. Random Graph Generators for Hyperbolic Community Structures • Viplove Arora, Mario Ventresca. Evaluating the Natural Variability in Generative Models for Complex Networks • Peter Overbury, Istvan Kiss, Luc Berthouze. Mapping structural diversity in networks sharing a given degree distribution and global clustering: Adaptive resolution grid search evolution with Diophantine equation-based mutations • Emil Saucan, Melanie Weber. Forman’s Ricci curvature - From networks to hypernetworks • Alessandro Lomi, Alberto Caimo, Francesca Pallotti. A Bayesian approach to reference Exponential Random Graph Models (ERGMs) for comparing networks of different size and composition: Models and empirical tests • Jan Treur. Relating Emerging Network Behaviour to Network Structure 11:30 Oral O4B: Machine Learning and Networks Chair: Frank Takes • Stefan Dernbach, Arman Mohseni-Kabir, Siddharth Pal, Don Towsley. Quantum Walk Neural Networks for Graph-Structured

Data • Nicolas Dugué, Jean-Charles Lamirel, Anthony Perez. Bringing a feature selection metric from machine learning to complex networks • Arunkumar Bagavathi, Siddharth Krishnan. Multi-Net: A Scalable Multiplex Network Embedding Framework • Rémi Vaudaine, Christine Largeron, Rémy Cazabet. Network properties captured by graph embeddings • Niklas Steenfatt, Giannis Nikolentzos, Michalis Vazirgiannis, Qiang Zhao. Learning Structural Node Representations on Directed Graphs • Kaushalya Madhawa, Tsuyoshi Murata. Exploring Partially Observed Networks with Nonparametric Bandits • Xavyr Rademaker, Frank Takes, Michel Chaudron. Automatic identification of component roles in software design networks 11:30 Oral O4C: Networks in Finance and Economics Chair: Yuchi Ikeda • Christian Diem, Anton Pichler, Stefan Thurner. Optimising Systemic Risk in Interbank Networks • Giovanni Covi, Gorpe Mehmet Ziya, Kok Christoffer. Contagion Risk in the Euro Area Interbank Network • Yoshi Fujiwara, Shinsuke Koyama. Point-process network of firms bankruptcies • Nils Bundi, Khaldoun Khashanah. Complex interbank network estimation: sparsity-clustering threshold • Celian Colon, Jean-Philippe Bouchaud. Transition from plasticity to instability in the structure of economic networks • Damiano Di Francesco Maesa, Andrea Marino, Laura Ricci. The Graph Structure of Bitcoin • Nino Antulov-Fantulin. Inferring short-term volatility indicators from the Bitcoin blockchain

13:15 Lunch

14:45 Oral O5A: Diffusion and Epidemics Chair: Kwang-Il Goh • Alex Bishop, Istvan Kiss, Thomas House. Consistent approximation of epidemic dynamics on degree-heterogeneous clustered network • Julien Petit, Martin Gueuning, Timoteo Carletti, Ben Lauwens,

Renaud Lambiotte. A three-time-scales random walk on temporal networks • George Panagopoulos, Fragkiskos Malliaros, Michalis Vazirgiannis. DiffuGreedy: An Influence Maximization Algorithm based on Diffusion Cascades • Kateryna Lytvyniuk, Rajesh Sharma, Anna Jurek-Loughrey. Predicting Information Diffusion in Online Social Platforms: A case study using Twitter • Shankar Iyer, Lada Adamic. The Costs of Overambitious Seeding of Social Products • Hafizh Adi Prasetya, Tsuyoshi Murata. Modeling The Co- evolving Polarization of Opinion and News Propagation Structure in Social Media 14:45 Oral O5B: Community Structure Chair: Gergely Palla • Till Hoffmann, Leto Peel, Renaud Lambiotte, Nick Jones. Community detection in networks with unobserved edges • Max Glonek, Jonathan Tuke, Lewis Mitchell, Nigel Bean. GLaSS: Semi-Supervised Graph Labelling with Markov Random Walks to Absorption • Ilias Sarantopoulos, Dimitrios Papatheodorou, Dimitrios Vogiatzis, Grigorios Tzortzis, Georgios Paliouras. TimeRank: a Random Walk approach for Community Discovery in Dynamic Networks • Elham Alghamdi, Derek Greene. Semi-Supervised Overlapping Community Finding based on Label Propagation with Pairwise Constraints • Ryan Hartman, Diego Pinheiro, Seyed Mohammad Mahdi Seyednezhad, Josemar Faustino Da Cruz, Ronaldo Menezes. A Comparison of Community Detection Techniques Across Thematic Twitter Emoji Networks • Kimon Fountoulakis, David Gleich, Michael Mahoney. A Short Introduction to Local Graph Clustering Methods and Software 14:45 Oral O5C: Modeling Human Behavior Chair: Emoke Agnes Horvat • Abhijin Adiga, Chris Kuhlman, Madhav Marathe, S. S. Ravi, Daniel Rosenkrantz, Richard Stearns. Using Active Queries to Learn Local Stochastic Behaviors in Social Networks • Gerrit Jan de Bruin, Frank Takes, Cor J Veenman, Jaap van den Herik. Understanding Behavorial Patterns in Truck Co-Driving

Networks • Andreia Sofia Teixeira, Francisco C. Santos, Alexandre P Francisco, Fernando P. Santos. Fairness in multiplayer ultimatum games through degree-based role assignment • Nicolo Pagan, Florian Dorfler. Learning strategic behavior in social and economic networks • Andrey V. Dmitriev, Svetlana Maltseva, Olga Tsukanova, Victor Dmitriev. Theoretical Study of Self-Organized Phase Transitions in Microblogging Social Networks • Iftah Gamzu, Iordanis Koutsopoulos. Advertisement Allocation and Mechanism Design in Native Stream Advertising 16:15 Poster P4: Network Analysis [1-10] Resilience and Control [11-14] Urban System and Networks [15-17] Chair: Sarah Morgan 1. Xiaochuan Xu, Gesine Reinert. Triad-based Comparison and Signatures of Directed Networks 2. Mohamad Kanaan, Hamamache Kheddouci. Mining Patterns With Durations from E-commerce Dataset 3. Raul Castillo. A software to extract criminal networks from unstructured text in Spanish; the case of Peruvian criminal networks 4. Andrea Fornaia, Misael Mongiovì, Giuseppe Pappalardo, Emiliano Tramontana. A General Powerful Graph Pattern Matching System for Graph Analysis 5. Natalia Meshcheryakova. The Impact of Indirect Connections: The Case of Food Security Problem 6. Yi-Chun Chang, Wei Weng, Seng-Cho Chou, Yen-Sheng Chiang, Chia-Te Chiang. Unpacking maritime trafficking from the complex network approach 7. Denisse Pasten, Zbigniew Czechowski, Benjamin Toledo. Time series analysis in earthquake complex networks 8. Tetsuya Kojima, Jun Ishida, Shigeyuki Miyagi, Osamu Sakai. Network property and learning model of weblike equation system in a scientific category 9. Uta Pigorsch, Marc Sabek. Assortative mixing in weighted directed networks 10. Ahmed Ould Mohamed Moctar. Survey on Social Ego- Community Detection 11. Nicole Balashov, Reuven Cohen, Simi Haber, Michael

Krivelevich. Optimal attacks on random graphs 12. Matthew R. Karlsen, Sotiris Moschoyiannis. Optimal control rules for random Boolean networks 13. Kin Yau Tsang, Bo Li, Kwok Yee Wong. Enhancing Synchronization Stability in Probabilistic Environment for Complex Networks 14. Jocelyn Bernard, Sicong Shao, Cihan Tunc, Hamamache Kheddouci, Salim Hariri. Quasi-Cliques Analysis for IRC Channel Thread Detection 15. Jerome Benoit, Saif Eddin Jabari. On the Statistics of Urban Street Networks 16. Trivik Verma, Marc Folini, Yi Wang, Nuno Araujo. Decentralized Optimal Route Navigation 17. Julian David Reyes-Silva, Jonatan Zischg, Robert Sitzenfrei, Peter Krebs. Application of Complex Network Analysis for Urban Drainage Systems 16:55 Markus STROHMAIER Modeling minorities in social networks Chair: Taha Yasseri 17:30 Oral O6A: Structural Network Measures Chair: Tsuyoshi Murata • Giulio Cimini, Tiziano Squartini, Fabio Saracco, Diego Garlaschelli, Andrea Gabrielli, Guido Caldarelli. Statistical Physics of Networks • George T. Cantwell, M. E. J. Newman. Mixing patterns and individual differences in networks • María Palazzi, Javier Borge-Holthoefer, Claudio Juan Tessone, Albert Solé-Ribalta. Coexisting Mesoscale Patterns in Complex Networks • Gorka Zamora-López, Romain Brasselet. Interpreting and comparing the length of complex networks • Eytan Katzav, Ofer Biham, Reimer Kühn. The distribution of shortest path lengths in random networks • Franz-Benjamin Mocnik. Dimension as an Invariant of Street Networks 17:30 Oral O6B: Urban Systems and Networks Chair: Elsa Arcaute • Ruiqi Li, Gene Stanley. Simple Spatial Scaling Rules behind Complex Cities • Albert Sole, Sergio Gómez, Alex Arenas. Decongestion of urban

areas with hotspot-pricing • Efrat Blumenfeld-Lieberthal, Nimrod Serok, Orr Levy, Elya Lucy Milner, Shlomo Havlin. Mapping the discourse on Smart Cities by means of NLP (Natural Language Processing) and complex network analysis • Jerome Mayaud, Sam Anderson, Martino Tran, Valentina Radic. Insights from self-organizing maps for characterizing accessibility to healthcare networks • Michele Tirico. Morphogenesis of complex networks: a reaction- diffusion framework for spatial graphs • Rounak Meyur, Anil Vullikanti, Madhav Marathe, Anamitra Pal, Mina Youssef, Virgilio Centeno. Cascading effects of targeted attacks on the power grid 17:30 Oral O6C: Resilience and Control Chair: Richard La • Leonhard Horstmeyer, Christian Kuehn, Jan Korbel, Tuan Minh Pham, Stefan Thurner. Precursor Theory of Adaptive Networks • Edgar Wright, Sooyeon Yoon, José Mendes, Alexander Goltsev. Controlling synchronization in bow-tie architectures • Lluís Arola-Fernandez, Albert Diaz-Guilera, Alex Arenas. Synchronization invariance under network structural transformations • Iryna Omelchenko. Chimera states in complex networks: from nonlocal to fractal modular and multilayer topologies • Madhurima Nath, Srinivasan Venkatramanan, Bryan Kaperick, Stephen Eubank, Madhav Marathe, Achla Marathe, Abhijin Adiga. Using Network Reliability to Understand International Food Trade Dynamics • Samuel Heroy, Dane Taylor, Feng Shi, Greg Forest, Peter Mucha. Rigidity percolation in random rod packings 19:00 Sessions End

Dinner Banquet 20:00 DoubleTree by Hilton Hotel

22:00 Day ends!

THURSDAY, DECEMBER 13th, 2018

Program at a Glance Day 3

08:00 Registration 08:45 Keynote Speaker: Donald TOWSLEY MDPI Future Internet Lecture Chair: Ronaldo Menezes 09.20 Lighting L3: Machine Learning and Networks – Network Models Chair: Sebastian Anhert 10:15 Poster P5: Network Models Network in Finance and Economics Social Networks Chair: Helena Andres Coffee Break 11:00 Oral O7A Oral O7B Oral O7C Diffusion and Community Structure Biological Networks Epidemics Chair: Istvan Kiss Chair: Letho Peel Chair: Stephen Eubank 13:00 Lunch 14:30 Oral O8A Oral O8B Oral O8C Modeling Human Resilience and Link Analysis and Behavior Control Ranking Chair: Fariba Karimi Chair: Clara Pizzuti Chair: Roberto Interdonato 16:00 Coffee Break 16:25 Keynote Speaker: Sune LEHMANN Chair: Renaud Lambiotte 17:00 Oral O9A Oral O9B Oral O9C Dynamics of/on Social Networks Network Analysis Networks Chair: Reuven Cohen Chair: Rosa M. Benito Chair: Giuseppe Mangioni 18:30 Closing

DETAILED PROGRAM DAY 3

08:00 Registration 08:45 Donald TOWSLEY Motifs in Social Networks MDPI Future Internet Lecture Chair: Ronaldo Menezes 09:20 Lighting L3: Machine Learning and Networks [1-6] – Network Models [7-10] Chair: Sebastian Anhert 1. Xutong Liu, Yu-Zhen Janice Chen, John C.S. Lui, Konstantin Avrachenkov. Graphlet Count Estimation via Convolutional Neural Networks 2. Leonardo Gutierrez Gomez, Jean-Charles Delvenne. Network Embeddings For Graph Classification and Visualization 3. Ferenc Beres, Robert Palovics, Domokos Miklos Kelen, David Szabo, Andras A. Benczur. Node Embeddings in Dynamic Graphs 4. Mikel Joaristi, Edoardo Serra, Francesca Spezzano. Detecting Suspicious Entities in the Panama Papers 5. Siobhán Grayson, Derek Greene. Temporal Alignment of Reddit Network Embeddings 6. Arya McCarthy. An Exact No Free Lunch Theorem for Community Detection 7. Alessandro Muscoloni, Carlo Vittorio Cannistraci. Local- community network automata modelling based on length- three-paths for prediction of complex network structures in protein interactomes, food webs and more 8. Tzu-Yi Chen. An Exploration of the Network Installation and Recovery Problem with Blackstart Nodes 9. Shiraj Arora, Abhishek Jain, Ramesh Yenda, - Mvprao. Specialist Cops Catching Robbers on Complex Networks 10. Priodyuti Pradhan, Sarika Jalan. Network construction: A learning framework through localizing principal eigenvector 10:15 Poster P5: Network Models [1-6] Network in Finance and Economics [7-12] Social Networks [13-19] Chair: Helena Andres 1. Swupnil Sahai, Timothy Jones, Sarah Cowan, Tian Zheng. Estimating Personal Network Size with Non-Random Mixing via

Latent Kernels 2. Theresa Migler-Vondollen, Glencora Borradaile, Gordon Wilfong. Random Network Models Based on Density 3. Xiaoyi Peng, Yi Zhao. A geometrically equivalent transformation between time series and complex networks 4. Cristian Giardinà, Claudio Giberti, Elena Magnanini. A Monte Carlo method for Large Deviations applied to Erdos-Rényi random graphs 5. Amin Kaveh, Matteo Magnani, Christian Rohner. Characterizing Probabilistic Networks 6. Alexander Goryashko, Leonid Samokhine, Pavel Bocharov. New deterministic model of evolving trinomial networks 7. Pedro Souto, Andreia Sofia Teixeira, Alexandre P Francisco, Francisco C. Santos. Capturing Financial Volatility Through Simple Network Measures 8. Manish Sarkhel, Nagarajan Krishnamurthy. Stability in Core- Periphery Production Networks 9. Tembo Nakamoto, Abhijit Chakraborty, Yuichi Ikeda. Hierarchical Identification of Key Firms of International Tax Avoidance in Global Ownership Network 10. Uta Pigorsch, Marc Sabek. Hierarchical structure of the cryptocurrency market 11. Andrew Elliott, Paul Reidy, Milton Martinez Luaces, Mihai Cucuringu, Gesine Reinert. Anomaly detection in networks using spectral methods and network comparison approaches 12. Vladimir Balash, Alfia Chekmareva, Alexey Faizliev, Sergei Sidorov, Sergei Mironov, Danii Volkov. Analysis of news flow dynamics based on the company co-mention network characteristics 13. Kuntal Dey, Saroj Kaushik, Kritika Garg, Ritvik Shrivastava. A Socio-Temporal Hashtag Recommendation System for Twitter 14. Danila Vaganov, Valentina Guleva, Klavdiya Bochenina. Social Media Group Structure and Its Goals: Building an Order 15. Matteo Zignani, Christian Quadri, Sabrina Gaito and Gian Paolo Rossi. On the clustered structure of a decentralized social network and its dynamics 16. Kathrin Eismann. Procedural Influence on Consensus Formation in Social Networks 17. Abhishek Samantray, Massimo Riccaboni. Peer influence in large dynamic network: Quasi-experimental evidence from

Scratch 18. Paola Tubaro. Emergent relational structures at a “sharing economy” festival 19. Christoph Siebenbrunner. Clearing algorithms and network centrality 11:00 Oral O7A: Diffusion and Epidemics Chair: Istvan Kiss • Francisco Rodrigues, Yamir Moreno, Paulo Cesar Ventura, Colm Connaughton, Federico Vazquez, Fatima Velasquez-Rojas. Epidemic spreading with awareness and different time scales in multiplex networks • Maria Letizia Bertotti, Giovanni Modanese. The mixed assortativity property of finite Barabasi-Albert networks and its influence on diffusion times • Joan T. Matamalas, Sergio Gómez, Alex Arenas. Effective epidemic containment using link importance • Jürgen Hackl, Thibaut Dubernet. Modelling epidemic spreading in urban areas with large-scale agent-based transport simulations • Ebrahim Patel. Maxmin-omega: A New Threshold Model on Networks • Bastian Prasse, Piet Van Mieghem. Network Reconstruction from NIMFA Viral State Observations of Multiple Epidemic Outbreaks • Yongjoo Baek, Kihong Chung, Daniel Kim, Hawoong Jeong, Meesoon Ha. Interplay of hubs and cooperation in social contagion • Alexandre Bovet, Hernan Makse. Spreading and influence of misinformation and traditional fact-based news in Twitter 11:00 Oral O7B: Community Structure Chair: Letho Peel • Antonio Maria Fiscarelli, Matthias Brust, Grégoire Danoy, Pascal Bouvry. A Memory-based Label Propagation Algorithm for Community Detection • Ruimin Zhu, Wenxin Jiang. Bayesian Complex Network Community Detection Using Nonparametric Topic Model • Tobias Hecking, H. Ulrich Hoppe. Links in Context: Detecting and Describing the Nested Structure of Communities in Node- attributed Networks • Frank Havemann, Jochen Gläser, Michael Heinz. Communities

as Well Separated Subgraphs With Cohesive Cores: Identification of Core-Periphery Structures in Link Communities • Thomas Helling, Frank Takes, Johannes Scholtes. A community- aware approach for identifying node anomalies in complex networks • Victor Connes, Nicolas Dugué, Adrien Guille. Is community detection fully unsupervised? The case of weighted graphs. • Tristan J.B. Cann, Iain S. Weaver, Hywel T.P. Williams. Is it correct to project and detect? Assessing performance of community detection on unipartite projections of bipartite networks • Vinh Loc Dao, Cécile Bothorel, Philippe Lenca. Estimating the similarity of community detection methods based on cluster size distribution 11:00 Oral O7C: Biological Networks Chair: Stephen Eubank • Kimberly Glass. Highlighting the Complex Network Structure of Epigenetic Regulation using Message-Passing • Philip Tee, Allan Balmain. Phase Transitions in Spatial Networks as a Model of Cellular Symbiosis • Yi Ming Lai, Stephen Coombes, Ruediger Thul. Cardiac Alternans: Understanding Subcellular Calcium Patterns with the Master Stability Function • Vera Pancaldi. Chromatin Assortativity approaches to study phenotypic variability • Vandan Parmar, Pietro Lio. Multi-omic Network Regression: methodology, tool and case study • Mohammad Bozlul Karim, Shigehiko Kanaya, Md Altaf-Ul-Amin. Comparison of BiClusO with Five Different Biclustering Algorithms using Biological and Synthetic data • Jie Sun, Erik Bollt. Reconstructing Boolean Functions and Networks from Noisy Observational Data • Fumito Mori. Expected Number of Fixed Points in Boolean Networks with Arbitrary Topology 13:00 Lunch Break 14:30 Oral O8A: Modeling Human Behavior Chair: Fariba Karimi • Rion Brattig Correia, Ian Wood, Luis M. Rocha. Towards understanding the multi-level complexity of human health: from drug interactions to human sexual behavior

• Juyong Park, Semi Min. Network-Based Mapping of Narrative Structures • Kyosuke Tanaka, Emoke Agnes Horvat. Networking Strategies and Efficiency in Human Communication Networks • Marion Hoffman, Per Block, Timon Elmer, Christoph Stadtfeld. DyNAM-i: a statistical model for the analysis of face-to-face interactions • Andres M. Belaza, Jan Ryckebusch. Quantifying the Role of Inactive Links in Social Networks • Christian Quadri, Matteo Zignani, Sabrina Gaito and Gian Paolo Rossi. Characterization of Ego-network Circles in Mobile Phone Graphs 14:30 Oral O8B: Resilience and Control Chair: Clara Pizzuti • Rion Brattig Correia, Alexander Gates, Nathan D. Ratkiewicz, Alain Barrat, Luis M. Rocha. Redundancy in the Structure and Dynamics of Complex Networks • Ivan Kryven. Colour-dependant percolation in complex networks • Toshihiro Tanizawa. Percolation transition on scale-free networks with assortative degree correlation • Yongzheng Sun, Siyang Leng, Yingcheng Lai, Celso Grebogi, Wei Lin. Trade-off between time and energy cost for controlling complex networks • Gustav Lindmark, Claudio Altafini. Using non-normality for control energy reduction in network controllability problems • Camill Harter, Rob Zuidwijk, Otto Koppius. European hinterland container transport as a complex network - How is robustness affected by the multi-mode structure? 14:30 Oral O8C: Link Analysis and Ranking Chair: Roberto Interdonato • Violet Brown, Xi Chen, Maryam Hedayati, Camden Sikes, Julia Strand, Tegan Wilson, David Liben-Nowell. Node Ordering for Rescalable Network Summarization (or, the Apparent Magic of Word Frequency and Age of Acquisition in the Lexicon) • Jorge Silva, David Aparício, Fernando Silva. OTARIOS: OpTimizing Author Ranking with Insiders/Outsiders Subnetworks • Angelo Furno, El Faouzi Nour-Eddin, Rajesh Sharma, Eugenio Zimeo. Fast Approximated Betweenness Centrality of Directed and Weighted Graphs

• Helge Holzmann, Avishek Anand, Megha Khosla. Delusive PageRank in Incomplete Graphs • Henry Soldano, Sophie Bary, Guillaume Santini, Dominique Bouthinon. Core Stratification of two-mode Networks • Sergey Shvydun, Fuad Aleskerov. Stability and Similarity in Networks based on Topology and Nodes Importance 16:00 Coffee Break 16:25 Sune LEHMANN Measuring Social Networks with High Resolution: What have we learned? Chair: Renaud Lambiotte 17:00 Oral O9A: Dynamics on/of Networks Chair: Reuven Cohen • Gergely Palla, Dániel Zagyva, Sámuel G. Balogh, Péter Pollner. Preference in the restructuring mechanisms of time evolving hierarchies • Farzaneh Heidari, Manos Papagelis. EvoNRL: Evolving Network Representation Learning based on Random Walks • Jonathan Ward, John Evans Evans. A General Model of Dynamics on Networks with Graph Automorphism Lumping • Madhurima Nath, Yihui Ren, Stephen Eubank. An approach to structural analysis using Moore-Shannon network reliability • Shazia Tabassum, Joao Gama. Biased dynamic sampling for temporal network streams • Carlos Merlos. Communication and Coordination for DEEP Agents 17:00 Oral O9B: Social Networks Chair: Rosa M. Benito • David Schoch, Ulrik Brandes. Social Stratification from Networks of Leveling Ties • Johannes Wachs, Balazs Lengyel, Taha Yasseri, Janos Kertesz. Social structure in towns and corruption risk at city hall • Samuel Martin-Gutierrez, Juan Carlos Losada, Rosa M. Benito. Temporal evolution of mentions and retweets networks in the Spanish General Elections • Pablo Piedrahita, Javier Borge-Holthoefer, Yamir Moreno, Sandra Gonzalez-Bailon. The Contagion Effects of Repeated Activation in Social Networks • Alain Fonhof, Madeleine van der Bruggen, Frank Takes. Characterizing Key Players in Child Exploitation Networks on the

Dark Net • Martin Lukac. Recruiting Mechanisms on Online Labour Markets: Agent-Based Models of Bipartite Social Networks 17:00 Oral O9C: Network Analysis Chair: Giuseppe Mangioni • Lucas Peters, Juan-Juan Cai, Huijuan Wang. Characterizing Temporal Bipartite Networks - sequential- vs cross-tasking • Luca Castelli Aleardi, Semih Salihoglu, Gurprit Singh, Maks Ovsjanikov. Spectral Measures of Distortion for Change Detection in Dynamic Graphs • Hamidreza Mahyar, Rouzbeh Hasheminezhad, Elahe Ghalebi, Radu Grosu, H. Eugene Stanley. A Compressive Sensing Framework for Distributed Detection of High Closeness Centrality Nodes in Networks • Sadamori Kojaku, Mengqiao Xu, Haoxiang Xia, Naoki Masuda. Multiscale core-periphery structure in a global liner shipping network • Agostino Funel. Analysis of the Web Graph Aggregated by Host and Pay-Level Domain • Abin Krishnan, Raman Sujith. Characterising vorticity interactions during the intermittency route to thermoacoustic instability 18:30 Closing

LUNCH

West Café

The Cafe at the Hauser Forum is the all new social hub serving the West Cambridge site. With a contemporary and spacious design, free wifi access, and great views over rolling fields, the cafe is an ideal place to meet, work or relax.

Don’t forget to bring your lunch ticket

Address: 3 Charles Babbage Road, Cambridge, CB3 0FD

How to Get There

WELCOME RECEPTION

Tuesday, December 11th, 2018

King’s College King’s College Hall

Address: King's College, King's Parade, Cambridge CB2 1ST, UK

You are required to wear your identification badge!

How to Get There Walking Bus U Universal

DINNER BANQUET

Wednesday, December 12th, 2018

Double Tree By Hilton Hotel

Address: Granta Place Mill Lane, Cambridge, CB2 1RT, United Kingdom

Do not forget to bring your dinner ticket!

How to Get There

ORAL SESSIONS AT A GLANCE

Room A Room B Room C

DAY 1 - DECEMBER 11, 2018 11:45 - 13:15 O1 Diffusion & Epidemics Quantifying Success Network Neuroscience

14:45 - 16:15 O2 Link Analysis & Ranking Resilience & Control Ecological Networks & Food Webs

17:30 - 19:00 O3 Network Models Multilayer Networks Social Networks DAY 2 - DECEMBER 12, 2018 11:30 - 13:15 O4 Network Models Machine Learning & Networks Networks in Finance & Economics

14:45 - 16:15 O5 Diffusion & Epidemics Community Structure Modeling Human Behavior

17:30 - 19:00 O6 Structural Network Measures Urban Systems and Networks Resilience & Control DAY 3 - DECEMBER 13, 2018 11:00 - 13:00 O7 Diffusion & Epidemics Community Structure Biological Networks

14:30 - 16:00 O8 Modeling Human Behavior Resilience & Control Link Analysis & Ranking

17:00 - 18:30 O9 Dynamics on/of Networks Social Networks Network Analysis

LIGHTNING AT A GLANCE

Dec. 11 09:35 - 10:30 L1 Networks in Finance & Economics 1 to 6 Structural Network Measures 7 to 10

Dec. 12 09:20 - 10:15 L2 Social Networks 1 to 3 Diffusion, Resilience & Control 4 to 10

Dec. 13 09:20 - 10:15 L3 Machine Learning & Networks 1 to 6 Network Models 7 to 10

POSTER SESSIONS AT A GLANCE

DAY 1 - DECEMBER 11, 2018 11:05 - 11:45 P1 Biological Networks [1-6] Community Structure [7-13] Link Analysis & Ranking [14-17]

16:15 - 16:55 P2 Diffusion & Epidemics [1-8] Modeling Human Behavior [9-13] ML & Networks [14-18] DAY 2 - DECEMBER 12, 2018 10:50 - 11:30 P3 ML & Networks [1-8] Multilayer Networks [9-14] Network Neuroscience [15-18]

16:15 - 16:55 P4 Network Analysis [1-10] Resilience & Control [11-14] Urban Systems & Networks [15-17] DAY 3 - DECEMBER 13, 2018 10:15 - 11:00 P5 Network Models [1-6] Networks in Finance & Economics [7-12] Social Networks [13-19]

SPEAKERS PROGRAM AT A GLANCE

Dec. 11 09:00 - 09.35 Aristides Gionis Maximizing diversity in social networks

Dec. 11 10:30 - 11:05 Vittoria Colizza Vulnerability of networked host populations to epidemics

Dec. 11 16:55 - 17:30 Romualdo Pastor-Satorras Effects of Social Influence on Collective Motion

Topological data analysis for investigation of dynamics and biological Dec. 12 08:45 - 09:20 Heather Harrington networks Essential nodes and keystone species in the brain, ecosystems and Dec. 12 10:15 - 10:50 Hernan Makse social systems

Dec. 12 16:55 - 17:30 Markus Strohmaier Modeling minorities in social networks

Dec. 13 08:45 - 09:20 Donald Towsley Motifs in Social Networks

Measuring Social Networks with High Resolution: What have we Dec. 13 16:25 - 17:00 Sune Lehmann learned? Program at a Glance

DAY 1 - DECEMBER 11, 2018

08:00 - 08:45 Registration

08:45 - 09:00 Opening

09:00 - 09:35 Speaker 1: Aristides Gionis - Maximizing diversity in social networks

09:35 - 10:30 L1: Networks in Finance & Economics - Structural Network Measures

10:30 - 11:05 Speaker 2: Vittoria Colizza - Vulnerability of networked host populations to epidemics

11:05 - 11:45 P1: Biological Networks - Community Structure - Link Analysis and Ranking (Coffee Break)

11:45 - 13:15 O1A: Diffusion & Epidemics - O1B: Quantifying Success - O1C: Network Neuroscience

13:15 - 14:45 Lunch

14:45 - 16:15 O2A: Link Analysis & Ranking - O2B: Resilience and Control - O2C: Ecological Networks and Food Webs

16:15 - 16:55 P2: Diffusion & Epidemics - Modeling Human Behaviour - Machine Learning & Networks (Coffee Break)

16:55 - 17:30 Speaker 3: Romualdo Pastor-Satorras - Effects of Social Influence on Collective Motion

17:30 - 19:00 O3A: Network Models - O3B: Multilayer Networks - O3C: Social Networks

20:00 - 22:00 Welcome Reception

DAY 2 - DECEMBER 12, 2018

08:00 - 08:45 Registration

08:45 - 09:20 Speaker 4: H. Harrington - Topological data analysis for investigation of dynamics and biological networks

09:20 - 10:15 L2: Social Networks - Diffusion, Resilience and Control

10:15 - 10:50 Speaker 5: Hernan Makse - Essential nodes and keystone species in the brain, ecosystems and social systems

10:50 - 11:30 P3: Dynamics on/of Networks - Multilayer Networks - Network Neuroscience (Coffee Break)

11:30 - 13:15 O4A: Network Models - O4B: Machine Learning and Networks- O4C: Networks in Finance & Economics

13:15 - 14:45 Lunch

14:45 - 16:15 O5A: Diffusion and Epidemics- O5B: Community Structure - O5C: Modeling Human Behavior

16:15 - 16:55 P4: Network Analysis - Resilence and Control - Urban Systems and Networks (Coffee Break)

16:55 - 17:30 Speaker 6: Markus Strohmaier - Modeling minorities in social networks

17:30 - 19:00 O6A: Structural Network Measures - O6B: Urban Systems & Networks - O6C:Resilience & Control

20:00 - 22:00 Dinner Banquet

DAY 3 - DECEMBER 13, 2018

08:00 - 08:45 Registration

08:45 - 09:20 Speaker 7: Donald Towsley - Motifs in Social Networks

09:20 - 10:15 L3: Machine Learning and Networks - Network Models

10:15 - 11:00 P5: Network Models - Networks in Finance and Economics - Social Networks (Coffee Break)

11:00 - 13:00 O7A: Diffusion & Epidemics - O7B: Community Structure - O7C: Biological Networks

13:00 - 14:30 Lunch

14:30 - 16:00 O8A: Modeling Human Behavior - O8B: Resilience and Control - O8C: Link Analysis and Ranking

16:00 - 16:25 Coffee Break

16:25 - 17:00 Speaker 8: Sune Lehmann - Measuring Social Networks with High Resolution: What have we learned?

17:00 - 18:30 O9A: Dynamics on/of Networks - O9B: Social Networks - O9C: Network Analysis

18:30 - 18:45 Closing 1

The 7th International Conference on Complex Networks and Their Applications December 11 - 13, 2018 - Cambridge, United Kingdom www.complexnetworks.org