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Immigration Trends Using Google Data

Authors: Wanner, Philippe;

Immigration Trends Using Google Data

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 (short-term) 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. Data and codebook along DDI standard

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Keywords

Migration Flows, Google Trends

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
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1
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6