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Recently, there have been considerable efforts to use online data toinvestigate international migration. These efforts show that Web data arevaluable for estimating migration rates and are relatively easy to obtain.However, existing studies have only investigated flows of people alongmigration corridors, i.e. between pairs of countries. In our work, we use dataabout "places lived" from millions of Google+ users in order to study migration"clusters", i.e. groups of countries in which individuals have lived. For thefirst time, we consider information about more than two countries people havelived in. We argue that these data are very valuable because this type ofinformation is not available in traditional demographic sources which recordcountry-to-country migration flows independent of each other. We show thatmigration clusters of country triads cannot be identified using informationabout bilateral flows alone. To demonstrate the additional insights that can begained by using data about migration clusters, we first develop a model thattries to predict the prevalence of a given triad using only data about itsconstituent pairs. We then inspect the groups of three countries which are moreor less prominent, compared to what we would expect based on bilateral flowsalone. Next, we identify a set of features such as a shared language orcolonial ties that explain which triple of country pairs are more or lesslikely to be clustered when looking at country triples. Then we select andcontrast a few cases of clusters that provide some qualitative informationabout what our data set shows. The type of data that we use is potentiallyavailable for a number of social media services. We hope that this first studyabout migration clusters will stimulate the use of Web data for the developmentof new theories of international migration that could not be testedappropriately before.

From Migration Corridors to Clusters: The Value of Google+ Data for Migration Studies