We are on an urban planning streak, publishing two new papers in Environment and Planning B:

1. Urban form and COVID-19 cases and deaths in Greater London: An urban morphometric approach, by A. Venerandi, L.M. Aiello, and S. Porta, published in Environment and Planning B
   
   The COVID-19 pandemic generated a considerable debate in relation to urban density. Many urban planners have advocated for rethinking our cities in ways that can decrease built-up density, in order to curb the spreading of future epidemics. In this work, we show that would be a bad idea. We used urban morphometrics to quantify built-up density in Greater London, and studied its relationship with COVID-19 cases and deaths at the level of MSOAs (small neighborhoods with an average population of ~8000). We found that urban density weakly and negatively correlates with both deaths and cases. The picture above (the low-density areas that some think could save us from contagion) shows the typical area in London with highest occurrence of COVID cases. The widespread belief that COVID cases scale with built-up density was supported mostly by city-level studies. The picture changes when comparing different areas within a city, which has been done for the first time in our study. The moral of the story is that built-up density is different from crowding. Let’s keep that in mind before worsening the urban sprawl of our cities. 
2. Data-driven micromobility network planning for demand and safety, by P. Folco, L. Gauvin, M. Tizzoni, and M. Szell, published in Environment and Planning B
   
   In this paper we study how data of micromobility trips and crashes can shape and automatize infrastructure network planning processes. We introduce a parameter that tunes the focus between demand-based and safety-based development, and investigate systematically this tradeoff for the city of Turin. We find that a full focus on demand or safety generates different network extensions in the short term, with an optimal tradeoff in-between. In the long term, our framework improves overall network quality independent of short-term focus. Thus, we show how a data-driven process can provide urban planners with automated assistance for variable short-term scenario planning while maintaining the long-term goal of a sustainable, city-spanning micromobility network.
   See the interactive visualization: http://www.datainterfaces.org/projects/biketracks/#turin

We have a new NERDS paper out by our Postdoc Sandro Sousa. This paper marks his main work from his PhD at Queen Mary University of London, published now:

1. Quantifying ethnic segregation in cities through random walks by S. Sousa and V. Nicosia, published in Nature Communications
   
   We propose here a family of non-parametric measures for spatial distributions, based on the statistics of the trajectories of random walks on graphs associated to a spatial system. These quantities provide a consistent estimation of segregation in synthetic spatial patterns, and we use them to analyse the ethnic segregation of metropolitan areas in the US and the UK. We show that the spatial diversity of ethnic distributions, as measured through diffusion on graphs, allow us to compare the ethnic segregation of urban areas having different size, shape, or peculiar microscopic characteristics, and exhibits a strong association with socio-economic deprivation.

Two new NERDS papers are out – this time both in Scientific Reports:

1. Heterogeneous rarity patterns drive price dynamics in NFT collections, by A. Mekacher, A. Bracci, M. Nadini, M. Martino, L. Alessandretti, L.M. Aiello & A. Baronchelli, published in Scientific ReportsWe quantify Non Fungible Token (NFT) rarity and investigate how it impacts market behaviour. We show that, on average, rarer NFTs: (i) sell for higher prices, (ii) are traded less frequently, (iii) guarantee higher returns on investment, and (iv) are less risky, i.e., less prone to yield negative returns. The dataset used for the work has been presented as part of a beautiful art exhibition at the MEET Digital Culture Center in Milano.
2. Posts on central websites need less originality to be noticed, by M. Coscia and C. Vandeweerdt, published in Scientific Reports
   In this paper we study how originality and centrality interact in a nontrivial way, which might explain why originality by itself is not a good predictor of success. We collected data from Reddit on users sharing hyperlinks. We estimated the originality of each post title and the centrality of the website hosting the shared link. We show that the interaction effect exists: if users share content from a central website, originality no longer increases the odds of receiving at least one upvote.
   See more info in Michele’s blogpost: https://www.michelecoscia.com/?p=2205

We published two more papers over the last weeks!

1. 1. A potential mechanism for low tolerance feedback loops in social media flagging systems, by C.J. Westermann and M. Coscia, published in PLOS ONE

      In this paper we simulate a scenario in which users on one side of the polarity spectrum have different tolerance levels for the opinions of the other side. We create a model based on some assumptions about online news consumption, including echo chambers, selective exposure, and confirmation bias. When studying a model of social media flagging, we see that intolerance is attractive: news sources are nudged to move their polarity to the side of the intolerant users.
      See more info on Michele’s blogpost: https://www.michelecoscia.com/?p=2179

   2. Multimodal urban mobility and multilayer transport networks, by L. Alessandretti, L.G. Natera Orozco, M. Saberi, M. Szell, F. Battiston, published in Environment and Planning B
      

      This is a comprehensive overview of the emerging research areas of multilayer transport networks and multimodal urban mobility, focusing on contributions from the interdisciplinary fields of complex systems, urban data science, and science of cities. First, we present an introduction to the mathematical framework of multilayer networks. We apply it to survey models of multimodal infrastructures, as well as measures used for quantifying multimodality, and related empirical findings. We review modelling approaches and observational evidence in multimodal mobility and public transport system dynamics, focusing on integrated real-world mobility patterns, where individuals navigate urban systems using different transport modes. We then provide a survey of freely available datasets on multimodal infrastructure and mobility, and a list of open source tools for their analyses. Finally, we conclude with an outlook on open research questions and promising directions for future research.