A bi-directional approach to comparing the modular structure of networks

Here we propose a new method to compare the modular structure of a pair of node-aligned networks. The majority of current methods, such as normalized mutual information, compare two node partitions derived from a community detection algorithm yet ignore the respective underlying network topologies. Addressing this gap, our method deploys a community detection quality function to assess the fit of each node partition with respect to the other network’s connectivity structure. Specifically, for two networks A and B, we project the node partition of B onto the connectivity structure of A. By evaluating the fit of B’s partition relative to A’s own partition on network A (using a standard quality function), we quantify how well network A describes the modular structure of B. Repeating this in the other direction, we obtain a two-dimensional distance measure, the bi-directional (BiDir) distance. The advantages of our methodology are three-fold. First, it is adaptable to a wide class of community detection algorithms that seek to optimize an objective function. Second, it takes into account the network structure, specifically the strength of the connections within and between communities, and can thus capture differences between networks with similar partitions but where one of them might have a more defined or robust community structure. Third, it can also identify cases in which dissimilar optimal partitions hide the fact that the underlying community structure of both networks is relatively similar. We illustrate our method for a variety of community detection algorithms, including multi-resolution approaches, and a range of both simulated and real world networks

Productive Ecosystems and the arrow of development

Economic growth is associated with the diversification of economic activities, which can be observed via the evolution of product export baskets. Exporting a new product is dependent on having, and acquiring, a specific set of capabilities, making the diversification process path-dependent. Taking an agnostic view on the identity of the capabilities, here we derive a probabilistic model for the directed dynamical process of capability accumulation and product diversification of countries. Using international trade data, we identify the set of pre-existing products, the product Ecosystem, that enables a product to be exported competitively. We construct a directed network of products, the Eco Space, where the edge weight corresponds to capability overlap. We uncover a modular structure, and show that low- and middle-income countries move from product communities dominated by small Ecosystem products to advanced (large Ecosystem) product clusters over time. Finally, we show that our network model is predictive of product appearances

What drives the creation of green jobs, products and technologies in cities and regions? Insights from recent research on green industrial transitions

Given the global imperative to meet ‘net zero’, and growing interest in the potential for green jobs growth, there is an urgent need to better understand the drivers and processes underlying green structural economic transitions. How should we in fact define ‘green’ products, jobs and technologies? How do local economies transition into greener jobs – is this generally an incremental process or does it require more radical innovation? Building on nascent green definitions, recent work emerging from the literature in Evolutionary Economic Geography suggests that there is a degree of path dependency to green transitions, with regions benefiting from existing capabilities which are somehow related to newer green tasks and technologies. On the other hand, having diverse, frequently unrelated, skills and competencies also helps local economies to make the recombinations necessary for the emergence of new green activities. These drivers are moderated by factors such as the local institutional environment, IT skills and the degree of maturity of the local industrial base. This article summarises the recent literature in order to provide an overview of emerging findings of relevance to local policy delivery, while also highlighting future research directions

Is academia becoming more localised? The growth of regional knowledge networks within international research collaboration

It is well-established that the process of learning and capability building is core to economic development and structural transformation. Since knowledge is ‘sticky’, a key component of this process is learning-by-doing, which can be achieved via a variety of mechanisms including international research collaboration. Uncovering significant inter-country research ties using Scopus co-authorship data, we show that within-region collaboration has increased over the past five decades relative to international collaboration. Further supporting this insight, we find that while communities present in the global collaboration network before 2000 were often based on historical geopolitical or colonial lines, in more recent years they increasingly align with a simple partition of countries by regions. These findings are unexpected in light of a presumed continual increase in globalisation, and have significant implications for the design of programmes aimed at promoting international research collaboration and knowledge diffusion

Uncovering the internal structure of Boko Haram through its mobility patterns

Boko Haram has caused nearly 40,000 casualties in Nigeria, Niger, Cameroon and Chad, becoming one of the deadliest Jihadist organisations in recent history. At its current rate, Boko Haram takes part in more than two events each day, taking the lives of nearly 11 people daily. Yet, little is known concerning Boko Haram’s internal structure, organisation, and its mobility. Here, we propose a novel technique to uncover the internal structure of Boko Haram based on the sequence of events in which the terrorist group takes part. Data from the Armed Conflict Location & Event Data Project (ACLED) gives the location and time of nearly 3,800 events in which Boko Haram has been involved since the organisation became violent 10 years ago. Using this dataset, we build an algorithm to detect the fragmentation of Boko Haram into multiple cells, assuming that travel costs and reduced familiarity with unknown locations limit the mobility of individual cells. Our results suggest that the terrorist group has a very high level of fragmentation and consists of at least 50–60 separate cells. Our methodology enables us to detect periods of time during which Boko Haram exhibits exceptionally high levels of fragmentation, and identify a number of key routes frequently travelled by separate cells of Boko Haram where military interventions could be concentrated

The future of the future city? The new urban sciences and a PEAK Urban interdisciplinary disposition

In many domains we see a proliferation of claims made about how we can predict and measure the future city, how we make visible its form and shape its settlement. This paper synthesises contemporary debates in data analytics, anthropology, geography and the history of urban thought to consider the context of such claims making around urban futures and the promise (and promises) of attempts to make visible the urban as a ‘lab’ or ‘observatory’ through which we might ‘see like a city’. Building on a ‘systems of systems approach’ the paper develops an original PEAK Urban conceptual framing of this new subdiscipline and addresses the potential for academic research to inform the capacity of cities to anticipate and reshape the challenges that characterise 21st century urban life through interdisciplinary and transdisciplinary engaged scholarship that situates the new urban sciences within a context of an experimental urbanism that makes visible the trade offs and the ethical dilemmas of the future city