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social media data and official labour force statistics can help to assess the social integration of migrants in destination countries.
examples include the following: • Mobile phone Call Detail Records (CDRs) have been used to track internal displacement following natural disasters, such as the Nepal earthquake, or the spread of diseases, such as COVID-19 (Wilson et.al., 2016; Flowminder & Ghana Statistical Services, 2020, Pepe et.al., 2020). While CDR data are usually more helpful to identify internal migration patterns, they could also be used to measure international migration at the subregional level, particularly when combined with other sources. For instance, the combination of CDR with satellite data can help to map movements between crossborder communities (Sorichetta, 2017); CDRs coupled with census statistics can contribute to understanding patterns of refugee integration (Boy et.al., 2019); and CDRs combined with geolocated
• Geo-located social media activity, such as on Twitter and Facebook, have been used to infer international migration flows and stocks, also disaggregated by age, sex as well as skill levels or sector of occupation, based on user selfreported information (Zagheni, Kiran and State, 2014; Patel, 2017; Gendronneau, 2019). For instance, during the COVID-19 pandemic, Facebook’s Disease Prevention Maps provided data on population distribution and movement on a daily basis, available for further analysis of the disease outbreak (Maas et.al., 2020). Overall, the number of active social media users globally in April 2020 reached 3.8 billion (We Are Social and Hootsuite, 2020), of which 2.6 million were Facebook users alone (Statista, 2020). The popularity of these platforms, together with the geotagged information that can be extracted from them, can be leveraged to study mobility patterns. • Social media data can also be used for providing information as in a “real-time census” at the national or global level at a certain point in time (Zagheni, Weber and Gummadi, 2017; Spyratos et.al., 2019). Data from the Facebook advertising platform, for instance, can yield information on a number of characteristics of users, such as their (self-reported) age, sex, their “home country” and current country of residence, educational
Border Security Report | July/August 2020
background, sector of occupation and personal interests. In early 2018, Spyratos et al. were able to accurately identify the increase in the number of Venezuelan migrants (the number of active monthly users classified by Facebook as ‘expats’) in Spain, a trend confirmed in the Spanish official statistics. Additionally, social media content can also be used to analyse public sentiments toward migrants and refugees, and how opinions on social media can become polarized (Natale, 2017; UN Global Pulse and UNHCR, 2017). • Repeated logins to the same website and IP addresses from e-mail sending activity have been used to estimate international mobility patterns and users’ likelihood to move to another country (Zagheni and Weber, 2012; State et.al., 2013). Self-reported information on sex and age of users also allowed to estimate migration rates by sex and age group. Online search data may also be helpful to forecast (forced) migration, as shown in projects that compare Google Trends data with numbers of arrivals of asylum-seekers and migrants in Europe and in Australia (Connor, 2017; UN Global Pulse, 2014). Similarly, the Google Trends Index (GTI) – derived from the Google search engine, used by over a billion people worldwide – for migration-related search terms can be exploited to measure migration intentions from a certain country and predict subsequent emigration flows (Böhme, Gröger and Stöhr, 2018). The European Asylum Support Office’s Early
