Spatio-temporal patterns of human mobility from geo-social networks for urban computing: Analysis, models & applications

The availability of rich information about fine-grained user mobility in urban environments from increasingly geographically-aware social networking services and the rapid development of machine learning applications greatly facilitate the investigation of urban issues. In this setting, urban computing emerges intending to tackle a variety of challenges faced by cities nowadays and to offer promising approaches to improving our living environment. Leveraging massive amounts of data from geo-social networks with unprecedented richness, we show how to devise novel algorithmic techniques to reveal underlying urban mobility patterns for better policy-making and more efficient mobile applications in this dissertation. Building upon the foundation of existing research efforts in urban computing field and basic machine learning techniques, in this dissertation, we propose a general framework of urban computing with geo-social network data and develop novel algorithms tailored for three urban computing tasks. We begin by exploring how the transition data recording human movements between urban venues from geo-social networks can be aggregated and utilised to detect spatio-temporal changes of local graphs in urban areas. We further explore how this can be used as a proxy to track and predict socio-economic deprivation changes as government financial effort is put in developing areas by supervised machine learning methods. We then study how to extract latent patterns from collective user-venue interactions with the help of a spatio-temporal aware topic modeling approach for the benefit of urban infrastructure planning. After that, we propose a model to detect the gap between user-side demand and venue-side supply levels for certain types of services in urban environments to suggest further policymaking and investment optimisation. Finally, we address a mobility prediction task, the application aim of which is to recommend new places to explore in the city for mobile users. To this end, we develop a deep learning framework that integrates memory network and topic modeling techniques. Extensive experiments indicate that the proposed architecture can enhance the prediction performance in various recommendation scenarios with high interpretability. All in all, the insights drawn and the techniques developed in this dissertation make a substantial step in addressing issues in cities and open the door to future possibilities in the promising urban computing area

Network communities within and across borders

We investigate the impact of borders on the topology of spatially embedded networks. Indeed territorial subdivisions and geographical borders significantly hamper the geographical span of networks thus playing a key role in the formation of network communities. This is especially important in scientific and technological policy-making, highlighting the interplay between pressure for the internationalization to lead towards a global innovation system and the administrative borders imposed by the national and regional institutions. In this study we introduce an outreach index to quantify the impact of borders on the community structure and apply it to the case of the European and US patent co-inventors networks. We find that (a) the US connectivity decays as a power of distance, whereas we observe a faster exponential decay for Europe; (b) European network communities essentially correspond to nations and contiguous regions while US communities span multiple states across the whole country without any characteristic geographic scale. We confirm our findings by means of a set of simulations aimed at exploring the relationship between different patterns of cross-border community structures and the outreach index.Comment: Scientific Reports 4, 201

Geographic Mobility in the European Union: Optimising its Economic and Social Benefits

One of the founding principles of the European Union is the freedom of movement of workers (Article 39 of the Treaty establishing the European Community). The free movement of workers is essential for the creation of an area without internal frontiers, and for the strength-ening of economic and social cohesion and active citizenship.Taking an economic perspective, geographic mobility can have major positive effects by bringing about economic growth in countries with labour deficits and prosperity in countries with labour surplus. Hence, the diffusion of skills through occupational and geographic mo-bility is a central factor to enhance the productive capacity of firms and put regions or na-tional economies on a higher growth path. Taking a social perspective, geographical mobility has the potential of fostering social-cultural integration in the European Union, and strength-ening European identity and inter-cultural networks

Regional territorial cohesion: what indicators for an EU sustainable perspective?

Research on territorial cohesion indicators detects and describes a set of territorial cohesion indicators to be applied in the new programming period 2007-2013. The main aim of the research is to enhance territorial cohesion through the improvement of indicators fit to evaluate and measure the different levels of cohesion at local, national and European level. Thus, the methodological approach has to describe, analyse and detect a set of territorial cohesion indicators and to evaluate the effectiveness and efficiency of the indicators’ systems currently used to measure territorial cohesion. This kind of approach is relevant both to current and new Structural Funds programming period. Moreover, the study proposes a methodological approach to implement an effective management system for the 2007-13 Programmes (STeMA). Sound and efficient indicators’ systems are crucial for monitoring and evaluating Structural Funds Programmes and projects. The 2000-2006 programming period produced a good progress in the quality of such systems which contribute to a more effective Programme management. The current monitoring systems contain inadequacies and the indicator sets can be further developed. In line with the strategic character of the 2007-2013 programming period, more attention must be paid to strengthening the link between Structural Funds Programmes and the Lisbon and Gothenburg Strategy. This paper provides an overview of the indicators’ systems currently used, while featuring also a practical guide to implement an indicators’ system suitable to evaluating territorial cohesion in the new programming period. After a description of the territorial cohesion concept and an in-depth overview of the new programming period objectives, the study analyses the main cohesion indicators used at European level and their effectiveness in monitoring activities. Some indicator systems analysed are: - the 27 indicators concerning employment, innovation and research, economical reforms and social cohesion - the 42 indicators, that are considered more flexible than the previous ones- the 14 indicators, chosen among the 42 indicators because of their relevance - EUROSTAT regional indicators - ESPON 3.3 project indicators. In the framework of Lisbon Strategy for a sustainable economic growth, the key challenge to strengthen territorial cohesion implies the improvement of EU regions’ territorial “capital” and potentials. The enhancement of territorial integration is achieved through the promotion of trans-European synergies and clusters of competitive and innovative activities. The use of a sound and effective system to manage territorial cohesion Programmes is crucial to promote Lisbon and Gothenburg objectives. Within this context the use of adequate tools, such as indicators, is pivotal to measure, monitor and evaluate the Programmes’ impact, result and output. According to the results of the indicator systems analysis, the most effective methodology to measure cohesion levels is the STeMA (Sustainable Territorial environmental/economic Management Approach), used also in ESPON 3.3 project “Territorial Dimension of the Lisbon/Gothenburg Strategy”. This approach pays particular attention to territoriality, economy, employment and the socio-pedagogical sector of intervention. The STeMA process is a multi-disciplinary management system used to calculate territorial capability with regard to competitiveness, sustainability and cohesion. Its standardised methodological approach can be applied at national, regional and sub-regional level by using a dedicated GIS tool. The main cohesion indicators are drawn from ESPON research and aggregated through a qualitative and interactive matrix

Mapping the Evolution of "Clusters": A Meta-analysis

This paper presents a meta-analysis of the “cluster literature” contained in scientific journals from 1969 to 2007. Thanks to an original database we study the evolution of a stream of literature which focuses on a research object which is both a theoretical puzzle and an empirical widespread evidence. We identify different growth stages, from take-off to development and maturity. We test the existence of a life-cycle within the authorships and we discover the existence of a substitutability relation between different collaborative behaviours. We study the relationships between a “spatial” and an “industrial” approach within the textual corpus of cluster literature and we show the existence of a “predatory” interaction. We detect the relevance of clustering behaviours in the location of authors working on clusters and in measuring the influence of geographical distance in co-authorship. We measure the extent of a convergence process of the vocabulary of scientists working on clusters.Cluster, Life-Cycle, Cluster Literature, Textual Analysis, Agglomeration, Co-Authorship

Analysis of Technological Portfolios for CO2 stabilizations and Effects of Technological Changes

In this study, cost-effective technological options to stabilize CO2 concentrations at 550, 500, and 450 ppmv are evaluated using a world energy systems model of linear programming with a high regional resolution. This model treats technological change endogenously for wind power, photovoltaics, and fuel-cell vehicles, which are technologies of mass production and are considered to follow the “learning by doing” process. Technological changes induced by climate policies are evaluated by maintaining the technological changes at the levels of the base case wherein there is no climate policy. The results achieved through model analyses include 1) cost-effective technological portfolios, including carbon capture and storage, marginal CO2 reduction costs, and increases in energy system cost for three levels of stabilization and 2) the effect of the induced technological change on the above mentioned factors. A sensitivity analysis is conducted with respect to the learning rate.Energy systems model, Global warming, Technological portfolios, Technological changes