Brazil Around the World: Characterizing and Detecting Brazilian Emigrants Using Google+

Abstract

Currently available data about people whose left their home country to live in a foreign country does not adequately capture the standards of contemporary global migration flows. A new trend for migration studies is to study the data from the Internet, either by Social Networks or other data in the WEB. In this study, we collected users data from the social network Google+ to investigate which features of Brazilian users are relevant to classify them as a possible emigrant. Our study uses machine learning techniques, SVM. We selected some features to compose our dataset. Our results show that the network features were the ones that had greater capacity for discrimination. The most relevant for the prediction of Brazilian emigrants users are, in order: reciprocity, PageRank, in-degree, clustering coefficient and ratio of incoming foreigners.