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Cambridge Networks Day

CNDay 2017

On 13th June we hosted the fifth edition of the Cambridge Networks Day (CNDay).Photo 6

CNDay brings together researchers with an interest in complex networks from a wide variety of fields, from biology to physics, computer science, sociology and business.

The programme for 13th June was as follows:

9.00- Registration

9.50- Welcome

10.00- Nicholas Christakis, 'Social Network Experiments'

11.00- Coffee

11.20- Jasmin Fisher, 'Deconstructing Cancer Signalling Networks'

12.00- Pietro Panzarasa, 'Network perspectives on social capital, innovation and value creation'

12.40- Poster orals

13.00- Buffet lunch and poster session

14.30- Martin Everett, 'Social networks containing negative ties'

15.10- Suzy Moat, 'Sensing human behaviour with online data'

15.50- Coffee

16.10- Alain Barrat, 'Epidemic risk evaluation from (incomplete) proxies of contact network data'

16.50- Sune Lehmann, 'Fundamental structures of dynamic social networks'

17.30- Poster prize and closing remarks


Nicholas Christakis, Department of Sociology and Medicine, Yale University (Keynote speaker)- Social Network Experiments

Human beings choose their friends, and often their neighbors, and co-workers, and we inherit our relatives; and each of the people to whom we are connected also does the same, such that, in the end, we humans assemble ourselves into face-to-face social networks with particular structures.  Why do we do this?  And how might an understanding of human social network structure and function be used to intervene in the world to make it better?  Here, I review recent research from our lab describing several classes of interventions involving both offline and online networks that can help make the world better, including: (1) interventions that rewire the connections between people, and (2) interventions that manipulate social contagion, facilitating the flow of desirable properties within groups.  I will illustrate what can be done using a variety of experiments in settings as diverse as fostering cooperation in networked groups online, to fostering health behavior change in developing world villages, to facilitating the diffusion of innovation or coordination in groups.  I will also focus on our recent experiments with “heterogenous systems” involving both humans and “dumb AI" bots, interacting in small groups.  By taking account of people's structural embeddedness in social networks, and by understanding social influence, it is possible to intervene in social systems to enhance desirable population-level properties as diverse as health, wealth, cooperation, coordination, and learning.

Alain Barrat, Centre de Physique Théorique, Marseille- Epidemic risk evaluation from (incomplete) proxies of contact network data

Face-to-face contacts between individuals play an important role in social interactions and determine the potential transmission routes of infectious diseases, in particular of respiratory pathogens. An accurate description of these patterns is therefore of interest for the fundamental knowledge and understanding of human behaviour and social networks as well as in epidemiology, in order to identify contagion pathways, to inform models of epidemic spread, and to design and evaluate control measures. 

An increasing number of datasets describing contacts between individuals in different contexts has become available. These datasets have been obtained using either surveys or wearable sensors that can detect contacts or simply co-presence, at varying resolution. Data are however often incomplete or biased, due on the one hand to population sampling and on the other hand to underreporting or bad estimation of contact durations in surveys. Such incomplete data can thus alter the outcome of simulations of epidemic spreading processes. 

In this talk, I will describe results obtained by the SocioPatterns collaboration in this context ( I will briefly describe the SocioPatterns sensing platform and some of the datasets collected in the last years. I will show an example of the use of such datasets to investigate issues of interest in the epidemiology of infectious diseases. I will also discuss recent progresses in the development of methods to compensate for data incompleteness.

Martin Everett, Department of Sociology, University of Manchester- Social Networks Containing Negative Ties

Social network analysts have often collected data on negative relations such as dislike, avoidance, and conflict. Most often, the ties are analyzed in such a way that the fact that they are negative is of no consequence. For example, they have often been used in blockmodeling analyses where many different kinds of ties are used together and all ties are treated the same, regardless of meaning. However, sometimes we may wish to apply other network analysis concepts, such as centrality or cohesive subgroups. The question arises whether all extant techniques are applicable to negative tie data. In this paper, we consider in a systematic way which standard techniques are applicable to negative ties and what changes in interpretation have to be made because of the nature of the ties. We also introduce some new techniques specifically designed for negative ties. Finally we show how one of these techniques for centrality can be extended to networks with both positive and negative ties to give a new centrality measure (PN centrality) that is applicable to directed valued data with both positive and negative ties.

Jasmin Fisher, Department of Biochemistry, University of Cambridge and Microsoft Research- Deconstructing Cancer Signalling Networks

Cancers are pathologies driven by genetic mutations that disrupt a multitude of signalling networks operating across different cell types interacting in highly complex ways. No two cancers, even of the same type, are the same. The holy grail of cancer treatment is to analyse the patient's genome and predict a sequence and combination of therapies that will destroy that patient's cancer with no adverse side effects. By developing executable models of oncogenic signalling networks and simulating cancer tumours at different levels of abstraction, we are on the threshold of being able to deliver on this vision. The state-of-the-art in executable biology is the use of formal methods and software verification to describe biological systems and explore their properties. Using program synthesis methods we can directly build such executable network models from patients' data. This approach has already been used to find new more efficient therapies for Leukaemia in partnership with Astra Zeneca. The next big question, as we collect more and more patient genomic data and history of cancer treatments, is how can we drive therapeutic regimes directly from patients' data? In the talk, I will showcase recent results and share our ambitions in this space.

Sune Lehmann, Department of Applied Mathematics and Computer Science, Technical University of Denmark- Fundamental Structures of Dynamic Social Networks

Social systems are in a constant state of flux, with dynamics spanning from minute-by-minute changes to patterns present on the timescale of years. Accurate models of social dynamics are important for understanding the spreading of influence or diseases, formation of friendships, and the productivity of teams. Although there has been much progress on understanding complex networks over the past decade, little is known about the regularities governing the microdynamics of social networks. Here, we explore the dynamic social network of a densely-connected population of 1,000 individuals and their interactions in the network of real-world person-to-person proximity measured via Bluetooth, as well as their telecommunication networks, online social media contacts, geolocation, and demographic data. These high-resolution data allow us to observe social groups directly, rendering community detection unnecessary. Starting from 5-min time slices, we uncover dynamic social structures expressed on multiple timescales. On the hourly timescale, we find that gatherings are fluid, with members coming and going, but organized via a stable core of individuals. Each core represents a social context. Cores exhibit a pattern of recurring meetings across weeks and months, each with varying degrees of regularity. Taken together, these findings provide a powerful simplification of the social network, where cores represent fundamental structures expressed with strong temporal and spatial regularity. Using this framework, we explore the complex interplay between social and geospatial behavior, documenting how the formation of cores is preceded by coordination behavior in the communication networks and demonstrating that social behavior can be predicted with high precision.

Suzy Moat, Warwick Business School and Alan Turing Institute - Sensing human behaviour with online data

Our everyday usage of the Internet generates huge amounts of data on how humans collect and exchange information worldwide. In this talk, I will outline recent work in which we investigate whether data from sources such as Google, Wikipedia and Flickr can be used to gain new insight into real world human behaviour. I will provide case studies from the economic domain and beyond.

Pietro Panzarasa, School of Business and Management, Queen Mary University of London- Network perspectives on social capital, innovation, and value creation

Social scientists have long agreed on the network signature of social capital by placing emphasis on the advantages that actors can derive from the structure of relationships in which they are embedded. However, network conceptions of social capital abound, and a longstanding controversy over the relative benefits and costs associated with various types of structure still remains unresolved. In this talk, I shall engage with current debates on social capital by illustrating evidence from inter-firm professional networks, scientific collaboration networks, international import-export multi-product networks, and the diffusion of medical innovation. As conduits of knowledge, networks serve as wellsprings of social capital not only to business firms, enabling them to tap entrepreneurial opportunities beyond local neighbourhoods, but to scientists too, who can leverage collaborators’ experience to pursue intellectual diversification into novel disciplinary territories. Moreover, as vehicles for economic exchange and cooperation, networks expose countries to sources of social capital, often disguised as opportunities to gain market power and competitive advantage at the various production stages of the global value chains. Finally, as catalysts for social contagion, networks provide the structural foundations for viral adoption cascades associated with pioneering medical innovations and improvements in the quality of healthcare delivery.

CNDay 2017 is kindly supported by King's College, Cambridge and Cambridge Big Data.


CNDay 2015

CNDay 2015 took place on Friday the 8th of May 2015 at the Sainsbury Laboratory. Speakers for CNDay 2015 included:

Prof Uri Alon (Department of Molecular Cell Biology, Weizmann Institute of Science, Israel) - Uri's keynote talk focussed on Evolutionary trade-offs, Pareto optimality, and the geometry of phenotype space. He also gave a version of his TED talk on why innovative science requires a leap into the unknown.

Prof Peter Csermely (Department of Medical Chemistry, Semmelweis University, Hungary) - slides are available here.

Prof James Bagrow (Department of Mathematics and Statistics, University of Vermont and Vermont Complex Systems Center, USA) - slides are available here and focus on the following paper.

Prof Petter Holme (Department of Energy Science, Sungkyunkwan University, Korea) - slides are available here.

Dr Francesco Iorio (European Bioinformatics Institute, Cambridge, UK) - the talk focused on the following paper.

Dr Daniele Quercia (Yahoo Labs, Barcelona, Spain) - slides are available here.

The full programme is available here.


CNDay 2014

The third Cambridge Networks Day took place on the 23rd of May 2014 at the Sainsbury Laboratory. It brought together 150 researchers (from various institutes across the UK) with an interest in Complex Networks. It would not have been possible without the generous sponsorship of Amadeus Capital, RealVNCCambridge University Press, DueDil, the University of Cambridge and the Sainsbury Laboratory.

The full programme is available here.

CNDay 2014 featured the following speakers - please click on the links next to their names if you would like to see a copy of their slides (we will try to upload all slides in the next couple of weeks):

Prof Mark Newman (Paul Dirac Collegiate Professor of Physics - Department of Physics and Centre for the Study of Complex Systems, University of Michigan and Santa Fe Institute, USA) - Slides

Prof Tom Freeman (Division of Genetics and Genomics, The Roslin Institute, University of Edinburgh) - Slides

Dr Martin Rosvall (Umea University, Sweden) - Slides

Dr Rui Carvalho (DPMMS, University of Cambridge) - Slides

Prof Zoubin Ghahramani (Department of Engineering, University of Cambridge) - Slides

Dr Vittoria Colizza (Inserm, Pierre Louis Institute of Epidemiology and Public Health & Université Pierre et Marie Curie, Paris) - Slides Coming Soon

Dr Fabio Caccioli (Centre for Risk Studies, Judge Business School, University of Cambridge) - Slides

Congratulations once again to Moreno Bonaventura from Queen Mary University of London for winning the poster prize with his work on "Interdisciplinarity and specialisation: Roads to scientific success." 

Like in previous years, we were pleased to see such a great mixture of backgrounds amongst the participants. 


CNDay 2013


The second Cambridge Networks Day took place on the 7th of May 2013 at the Sainsbury Laboratory. It brought together 150 researchers (from various institutes across the UK) with an interest in Complex Networks. The CNDay2013 programme is available here.

CNDay 2013 featured the following speakers - please click on the links next to their names if you would like to see a copy of their slides:

Albert-Lászlo Barabási, Northeastern University, Boston: Slides

Marc Barthelemy, CEA Institut de Physique Theorique, Saclay, France: Slides

Ed Bullmore, Department of Psychiatry, University of Cambridge: Slides

Ginestra Bianconi, Queen Mary University of London: Slides

Jörg Menche, Northeastern University, Boston: Slides

Cecilia Mascolo, Computing Laboratory, University of Cambridge: Slides

Felix Reed-Tsochas, Saïd Business School, Oxford: Slides

Congratulations once again to Marta Sarzynska from the Mathematical Institute, University of Oxford for winning the poster prize with her work on "Community detection on time-dependent correlation networks to study the geographical spread of disease." 

We were particularly pleased to see such a great mixture of backgrounds amongst the participants. See below for some simple demographics.




CNDay 2012

The first Cambridge Networks Day took place on the 18th of May 2012 at the Sainsbury Laboratory and was made possible by the kind support of the Behavioural and Clinical Neuroscience Institute (BCNI) as well as the Cambridgeshire & Peterborough NHS Foundation Trust. It brought together 150 researchers (from various institutes across the UK) with an interest in Complex Networks.

Click on the pictures bleow for further details:


1. Programme                                                                                         2. Photo Gallery

3. Speakers and Slides                                                                              4. Participant Demographics



Cambridge Networks Day 2012