How well can we estimate immigration trends using Google data?
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How well can we estimate immigration trends using Google data? Philippe Wanner1 Accepted: 25 September 2020 The Author(s) 2020
Abstract For a country to efficiently monitor international migration, quick access to information on migration flows is helpful. However, traditional data sources fail to provide immediate information on migration flows and do not facilitate the correct anticipation of these flows in the short term. To tackle this issue, this paper evaluates the predictive capacity of big data to estimate the current level or to predict short-term flows. The results show that Google Trends can provide information that reflects the attractiveness of Switzerland for to immigrants from different countries and predict, to some extent, current and future (shortterm) migration flows of adults arriving from Spain or Italy. However, the predictions appear not to be satisfactory for other flows (from France and Germany). Additional studies based on alternative approaches are needed to validate or overturn our study results. Keywords Big data Forecasting Immigration trends Migration estimates Switzerland
1 Introduction The emergence of alternative data derived from the operations of internet companies or communication providers as well as individual data (or microdata) from scientific collections has introduced a new era of quantitative research in the social sciences. Researchers have progressively gained access to a large amount of data, allowing them to think outside the box, transcend traditional approaches and develop new tools. In demography, the issue of data availability refers to two main areas. First, individual data (or microdata) gathered using scientific standards are increasingly available (for instance, through the IPUMS project; see Ruggles 2014), which has facilitated the rapid development of (spatial or temporal) comparative studies. Second, researchers have begun to use other non-traditional or alternative data (mobile phone records, social media, satellite maps, internet-based platforms, also commonly called ‘‘big data’’, IOM 2015), particularly to understand migration and mobility in light of new methodological approaches. However, scepticism and uncertainty remain regarding the feasibility of using alternative data & Philippe Wanner [email protected] 1
Institute of Demography and Socioeconomics, University of Geneva, Pont dArve 40, 1211 Gene`ve 4, Switzerland
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sources to measure migration-related dimensions (Rango and Vespe 2017), and more research is necessary to test the value of using big data for such research. This paper is an attempt to measure the extent to which internet activities can predict people’s intentions to migrate and, consequently, future migration trends. In contrast to most comparable studies that address long-distance flows, this study focuses on migration flows from industrialized countries close to Switzerland. To efficiently monitor migration flows, defined as the arrival in the country of
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