Detecting Migration Trends: A Method for Open Source Data Analysis

Abstract

As migrational events tend to develop together with the societal and technological trends in the modern world, there emerges a need to discover new methods to assist and understand the research about the phenomenon. Evidence presents that modern technological developments, such as smartphones, the internet and social media shape the ways that migrations emerge and develop. This research aims to apply new methods in order to understand these mechanisms deeper. The research applies Mixed Methods Research, combining quantitative and qualitative methods, using the quantitative data as a basis for semantic qualitative analysis. This research’s interest is to study whether applying Open Source Intelligence (OSINT) methods can be utilised for understanding, analysing and even nowcasting contemporary migrational trends. In the quantitative part of the research, data is extracted by using Google Trends Index and Search Engine Optimisation (SEO) tools. The qualitative analysis is executed by filtering the quantitative results through pre-existing theories of migration drivers and push-pull factors. The case presented in this study is the migration event from Iraq via Belarus to other European states, which took place in 2021. Research is done by selecting precise keywords used in Google search queries done in Iraq, extracting additional related keywords, and analysing the results based on factors such as Interest over time, Interest by subregion, Related keywords and SEO analysis. The thesis argues that these Google queries may provide additional insight into the migrational push-pull factors and drivers behind the migration trend and to present further insights into the complex nature of the fragmented and turbulent reality of this migration trend.