- Social media profiles are a valuable source of information in case processing, complementing the asylum interview; Information from Facebook and other social media platforms is used in some countries as evidence in immigration cases, in particular, to validate claims of identity, sexual orientation, networks and geographical origin;
- Geolocation of online content for situational awareness; For example, using Google Earth Pro (including Historical Imagery) to collect more information on stranded migrants;
- Use social media statistics to estimate and study ‘expat communities’. For example, in Europe, Syrians have set up Facebook groups and pages that arguably function as a ‘Trip advisor for refugees’; these digital communities are important for discounting rumours, informal language learning, and interacting with fellow members of the host society;
- Use quantitative pattern detection of web data, in this case the ‘places lived’ section of Google+ social media profiles to develop ‘new theories of international migration’;
- Monitor patterns of migration in country of arrival, as in many cases (specifically in the case of vulnerable people who do not have links to the country of destination) decisions on choice of the city are made based on social media information;
- Use Twitter to infer international and national migration patterns;
- Use social media applications to estimate stocks of international migrants, based on the number of users who are classified as ‘expats.’ In the European context, it can be used for quantifying intra-EU mobility patterns of specific demographic groups, such as students, as well as for measuring migration movements that may not be captured in as timely a fashion by official statistics;
- Use social media data to gather insights into socio-economic indicators that are not collected yet by statistical offices. For example, personal interests, skills, educational attainment, and sector of employment disaggregated by country of the previous residence, gender and age among other attributes;
- Monitor the digital trace of Internet searches in certain languages to predict forced migration events;
- Cross-country migration trends can potentially be predicted by analysing information on friendship networks across countries, as provided by Facebook;
- Existing data sets on migratory flows are flawed as it is impossible to really count the irregular migrants who arrive to Europe. Some of them may never apply for asylum and will end up in the EU without appearing in any stats. Therefore, OSINT can be employed as a useful resource to correct/improve official statistics;
- Detect migration-related events and address the security implications in the real-word. A good example is the Caravan for Hope, when as a result of a Facebook post in February 2019 announcing a march from Greece through the Western Balkan Route, more than a thousand people gathered near the refugee camp of Diavatain Thessaloniki with the purpose of marching to the northern border of Greece. This event was identified through the monitoring of social media.
Resources
Andreassen, R. (2020). Social media surveillance, LGBTQ refugees and asylum: How migration authorities use social media profiles to determine refugees as ‘genuine’ or fraudulent’. First Monday, Volume 26, Number 1 – 4 January 2021. Available at: https://journals.uic.edu/ojs/index.php/fm/article/view/10653/10031 [accessed on 9 June 2022].
Brekke, J.P., & Balke Staver A. (2019). Social media screening: Norway’s asylum. Forced Migration Review: the ETHICS issue, 61.
Expert contribution, MIRROR conference ‘Migration in Focus: Addressing Informational Challenges in Humanitarian Actions’, 15-16th December 2021, Valletta (Malta).
Juric, T. (2022). Predicting refugee flows from Ukraine with an approach to Big (Crisis) Data: a new opportunity for refugee and humanitarian studies. medRxiv.
Leurs, K., & Prabhakar, M. (2018). Doing Digital Migration Studies: Methodological Considerations for an Emerging Research Focus. Qualitative Research in European Migration Studies, DOI: 10.1007/978-3-319-76861-8_14.
Messias, J., Benvenuto, F., Weber, I., & Zagheni, E. (2016). From Migration Corridors to Clusters: The Value of Google+ Data for Migration Studies. IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM’16).
Peyroux, O. (2020). Mineurs migrants et traite des êtres humains. hommes & migrations, 1328/2020.
Sanchez, G., Arrouche, K., Capasso, M., Dimitriadi, A., Fakhry, A. (2021). Beyond Networks, Militias and Tribes: Rethinking EU Counter-smuggling Policy and Response. European Institute of the Mediterranean. Available at: https://www.euromesco.net/wp-content/uploads/2021/05/RETHINKING-EU-COUNTER-SMUGGLING-POLICY-AND-RESPONSE-1.pdf [accessed on 9 June 2022].
Spyratos, S., Vespe, M., Natale, F., Ingmar, W., Zagheni, E., & Rango, M. (2018). Migration Data using Social Media: a European Perspective. Publications Office of the European Union, EUR 29273 EN, ISBN 978-92-79-87989-0.
Teunissen, P. (2021). Mapping Migration Infrastructures; Epistemological reflection on digital methods. Available at: http://projectmoves.eu/wp-content/uploads/2021/10/Peter-Teunissen_Mapping-Migration-Infrastructures_MOVES-Summer-School.pdf [accessed on 3 May 2022].
Tjaden, J. (2021). Measuring migration 2.0: a review of digital data sources. CMS 9, 59 (2021). Available at: https://doi.org/10.1186/s40878-021-00273-x [accessed on 9 June 2022].
Urchs, S., Wendlinger, L., Mitrovic, J., & Granitzer, M. (2019). MMoveT15: A Twitter Dataset for Extracting and Analysing Migration-Movement Data of the European Migration Crisis 2015. 2019 IEEE 28th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE), pp.146-149.
