Geo-localized social media data to improve characterization of international travelers

Abstract

The motivation for traveling across political borders might be influenced by the socio-economic condition and the educational level of the traveler. Ecuador is both a highly popular touristic destination and the home country of at least 1 million migrants. The relatively high availability and low cost of online social network data may be a complement to migration data in the study of traveler's economical means and motivations. Such travel variables are relevant for countries as Ecuador in which the economy partly relies on the tourism industry and remittances. In this empirical study, we collected 63 millions of tweets, extracted the modal country for each user and studied the tweets generated. We first demonstrated, that the volume of local travelers leaving a country grouped by destination, as well as the volume of foreign travelers visiting the same country and grouped by provenance origin location, can be accurately estimated (r = 0.85) from geo-located records extracted from Twitter. Next, we characterized each group of travelers and computed spatial clusters, revealing popular locations of national and foreign travelers while in Ecuador. Finally, we showed that Ecuadorians with higher educational level have more chances to travel abroad, validating such findings with official data.