Speakers

Dr Luca Aiello  
Computational Social Science research,
​Bell Labs​, Cambridge
Dr Elsa Arcaute  
Spatial Modelling and Complexity,
​CASA, UCL
Prof Giulia Iori
School of Arts and Social Sciences, 
​City University
Dr Felix Reed-Tsochas  
Director of the Oxford Martin Programme on Complexity, Risk and Resilience

Program
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​15:00 - 15:05                  Opening

15:05 - 15:50                  Dr. Luca Aiello
                                          ​Th​e quest for a Good City Life

15:50 - 16:35                  Dr. Elsa Arcaute
                                          ​Retrieving territorial boundaries using percolation theory
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16:35 - 16:50                  Coffee break

​16:50 - 17:35                  Prof. Giulia Iori
                                          Expectation formation in Agent Based Models  of financial, credit and goods markets

17:35 - 18:20                  Dr. Felix Reed-Tsochas  
                                          How simulations using simple social mechanisms can help explain puzzles in collective online behaviour

18:20                                Refreshments!

The talks

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Th​e quest for a Good City Life

Urbanization is an irreversible, ever-growing trend. To effectively cope with it we need not only to make our cities more efficient but also more livable. To do that, it is crucial to understand how people perceive urban places with all their senses (sight, smell, sound...). We develop a methodology to measure that at scale through social media data and we validate our approach with orthogonal datasets from crowdsourcing, epidemiology studies, and open city data. Our sensory mapping enables a wide range of applications including routing, city monitoring, and next-generation urban planning. The GoodCityLife.org initiative provides a collaborative platform for all researchers in urban informatics to gather and build new technologies to make our cities happier.
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​Retrieving territorial boundaries using percolation theory

Territorialism is one of the oldest animal instincts that had led humans to draw boundaries of all sorts to represent differentiated communities, wealth, regions and countries. We explore using percolation theory, the role of proximity in the delimitation of these territories, from the spatial configuration of anglo-saxon settlements to the contemporary infrastructure of Britain. We discuss the hierarchical structure obtained through this method as a means to identify regions and communities embedded in the physical space, despite the fuzzy boundaries that could be drawn in the globalised cyber-space. 
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Expectation formation in Agent Based Models of financial, credit, and goods markets

Unlike conventional economic models which stress forward looking behaviour by far-sighted and rational, often representative, agents at the expense of the “plumbing” (i.e. the inter-connections) of an actual economy, ABMs have the advantage of simplifying behavior at the individual level by assuming that agents follow given but evolving rules-of-thumb, and this allows them to explore the multiplicity of agent types and their set of inter-connections in far greater detail.  ABM typically assume large populations of heterogeneous agents, specifying agents  individual behaviour, the environment, and modes of interaction. Agents are not only heterogenous and interacting but also adaptive; they have different circumstances, different histories and adapt continuously to the overall situation they create. To handle real-world features, it is essential to permit agents to engage in comprehensive forms of learning that include inductive reasoning (experimentation with new ideas) as well as aspects of reinforcement learning, social mimicry, and forecasting of future events. In ABM, agents can range from passive automatons with no cognitive function, to active data-gathering decision makers with sophisticated learning capabilities. In this talk I will review some  mechanisms of agents learning and expectation formation that provide  the micro-fundation of economic and financial ABMs,  focusing on the stabilizing/destabilizing effects on the  resulting macro-dynamics  of financial, credit and goods markets.
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How simulations using simple social mechanisms can help explain puzzles in collective online behaviour

Human activities increasingly take place in online environments, providing novel opportunities for relating individual behaviours to population-level outcomes. In my talk I will consider a simple generative model for the collective behaviour of millions of social networking site users who make choices between different software applications that they can install. The proposed model incorporates two distinct social mechanisms: (1) imitative behaviour reflecting the influence of recent installation activities of other users; (2) rich-get-richer popularity dynamics where users are influenced by the cumulative popularity of each application. Interestingly, although various combinations of the two mechanisms yield long-time behaviour that is consistent with data, the only models that reproduce the observed temporal dynamics well are those that strongly emphasize the recent installation activities of other users over their cumulative popularity. Hence social imitation seems to be especially important in this information rich environment. More generally this demonstrates that even when using purely observational data, as opposed to experimental research designs, temporal data-driven modelling can in fact effectively distinguish between competing microscopic mechanisms, providing novel insights into collective online behaviour.
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Event organizers