Human Mobility

FROM UKRAINE TO THE WORLD: USING LINKEDIN DATA TO MONITOR PROFESSIONAL MIGRATION FROM UKRAINE

From Ukraine to the World: Using LinkedIn Data to Monitor Professional Migration from Ukraine. 

In Proceedings of the 2023 ACM Conference on Information Technology for Social Good (pp. 213-222).

Berte M., Paolotti D. Kalimeri K. 

The forced migration of highly skilled professionals from Ukraine, accelerated by the 2014 conflict and the 2022 Russian invasion, has been analyzed using LinkedIn data and official statistics from the World Bank and UN Refugee Agency. This study highlights the significant migration to Poland and Germany, driven by pre-existing networks. Findings show a strong link between educated Ukrainian migrants' destinations and LinkedIn and UN data, emphasizing the importance of support networks over geographical distance in choosing a host country. The research reveals that migration patterns of Ukraine's skilled workforce are shaped by established connections, offering insights for addressing economic impacts and optimizing benefits for both Ukraine and host countries.

MICROMOBILITY NETWORK PLANNING

“Data-driven micromobility network planning for demand and safety”, Environment and Planning B: Urban Analytics and City Science. 2022. 

Folco P, Gauvin L, Tizzoni M,  Szell M

Developing safe infrastructure for cycling and micromobility is an efficient pathway towards climate-friendly, sustainable, and livable cities. However, urban cycling infrastructure is typically planned ad-hoc and at best informed by survey data.

For a systematic, data-driven planning process here we develop an automated planning framework using data of the existing network and of empirical e-scooter trips and bicycle crashes as proxies for demand and safety, to generate a cohesive network. We introduce a parameter that tunes the focus between demand-based and safety-based development, and investigate systematically this trade off 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.

VULNERABLE ROAD USERS SAFETY

“Identifying urban features for vulnerable road user safety in Europe”, EPJ data science, 2022. 

Klanjčić M, Gauvin L, Tizzoni M, Szell M

One  of  the  targets  of  the  UN  Sustainable  Development  Goals  is  to  substantially  reduce  the  number of  global  deaths  and  injuries  from  road  traffic  collisions.   To  this  aim,  European  cities  adopted  various urban mobility policies, which has led to a heterogeneous number of injuries across Europe.  Monitoring the

discrepancies in injuries and understanding the most efficient policies are keys to achieve the objectives of Vision Zero, a multi-national road traffic safety project that aims at zero fatalities or serious injuries linked to road traffic.  Here, we identify urban features that are determinants of vulnerable road user safety through the analysis of inter-mode collision data across European cities.  

ANTI-IMMIGRATION FACEBOOK AD TARGETING 

“Clandestino or Rifugiato? Anti-immigration Facebook Ad Targeting in Italy” ACM CHI Conference on Human Factors in Computing Systems. 2021. Best Paper Award

Capozzi A, De Francisci Morales G, Mejova Y, Monti C, Panisson A, Paolotti D

Monitoring advertising around controversial issues is an important step in ensuring accountability and transparency of political processes. Here, we use the Facebook Ads Library to collect 2,312 migration-related advertising campaigns in Italy over one year. Our pro- and anti-immigration classifier reveals a partisan divide among the major Italian political parties, with anti-immigration ads accounting for nearly 15M impressions.  We estimate that about two thirds of all captured campaigns use some kind of demographic targeting by location, gender, or age. Our study has policy implications for political communication: since the Facebook Ads Library does not allow to distinguish between advertisers intentions and algorithmic targeting, we argue that more details should be shared by platforms regarding the targeting configuration of socio-political campaigns.

NEWS AND INTERNAL DISPLACEMENT

“Developing Annotated Resources for Internal Displacement Monitoring”  .

WWW '21: Companion Proceedings of the Web Conference 2021

Poletto F, Zhang Y, Panisson A, Mejova Y, Paolotti D, Ponserre S

In this study we designed and developed a novel annotation framework and of annotated resources for Internal Displacement, as the outcome of a collaboration with the Internal Displacement Monitoring Centre, aimed at improving the accuracy of their monitoring platform IDETECT. The schema includes multi-faceted description of the events, including cause, quantity of people displaced, location and date. Higher-order facets aimed at improving the information extraction, such as document relevance and type, are proposed. We also report a case study of machine learning application to the document classification tasks. Finally, we discuss the importance of standardized schema in dataset benchmark development and its impact on the development of reliable disaster monitoring infrastructure.