Nuevas fuentes de información geográfica en turismo: las oportunidades de sightsmap.com

La producción de información geográfica ha cobrado un ritmo antes insospechado, gracias a instituciones y empresas, pero especialmente a las acciones voluntarias (Web 2.0). Uno de los campos en los que se abren mayores posibilidades para el uso de la nueva información geolocalizada es el turismo, ya que sus actividades son fácilmente monitorizables. Una de las fuentes más conocidas, Panoramio exhibe fotografías de lugares tomadas y georreferenciadas por usuarios. Esta comunicación presenta las oportunidades que tienen, para el análisis del turismo, la información de Panoramio y la explotación que hace de ella la herramienta Sightsmaps, a diferentes escalas

Challenges When Identifying Migration from Geo-Located Twitter Data

Given the challenges in collecting up-to-date, comparable data on migrant populations the potential of digital trace data to study migration and migrants has sparked considerable interest among researchers and policy makers. In this paper we assess the reliability of one such data source that is heavily used within the research community: geolocated tweets. We assess strategies used in previous work to identify migrants based on their geolocation histories. We apply these approaches to infer the travel history of a set of Twitter users who regularly posted geolocated tweets between July 2012 and June 2015. In a second step we hand-code the entire tweet histories of a subset of the accounts identified as migrants by these methods. Upon close inspection very few of the accounts that are classified as migrants appear to be migrants in any conventional sense or international students. Rather we find these approaches identify other highly mobile populations such as frequent business or leisure travellers, or people who might best be described as “transnationals”. For demographic research that draws on this kind of data to generate estimates of migration flows this high mis-classification rate implies that findings are likely sensitive to the adjustment model used. For most research trying to use these data to study migrant populations, the data will be of limited utility. We suspect that increasing the correct classification rate substantially will not be easy and may introduce other biases

Applying Concepts and Tools in Demography for Estimating, Analyzing, and Forecasting Forced Migration

Among demographic events (birth, death, and migration), migration is notably the most volatile component to forecast accurately. Accounting for forced migration is even more challenging given the difficulty in collecting forced migration data. Knowledge of trends and patterns of forced migration and its future trajectory is, however, highly relevant for policy planning for migrant sending and receiving areas. This paper aims to review existing methodological tools to estimate and forecast migration in demography and explore how they can be applied to the study of forced migration. It presents steps towards estimation of forced migration and future assessments, which comprise: (1) migration flows estimation methods using both traditional and nontraditional data; (2) empirical analysis of drivers of migration and migration patterns; and (3) forecasting migration based on multidimensional population projections and scenarios approach. The paper then discusses how these demographic methods and tools can be applied to estimate and forecast forced migration

The Big Data of International Migration: Opportunities and Challenges for States under International Human Rights Law

This is the author accepted manuscript. The final version is available via HeinOnline.Technology, as the epitome of our contemporary society, permeates the realm of international migration. Migrants and refugees are increasingly using mobile phones and digital features available online to prepare for migration and while on the move. Concurrently, advances in computer science allow for progressively more accurate analysis of the data generated by mobile devices and online searches. In particular, big data can be used to determine specific behavioural patterns, geolocation and human interactions. This article investigates the implications of these technological advances for States under international human rights law. It argues that big data can and should be used as a tool for the protection of migrants’ human rights by enhancing both decision-making and measures to prevent unnecessary deaths at sea, ill-treatment and human trafficking of migrants. Consequently, the article examines whether the development of new technologies can affect States’ capabilities for the identification of individuals in need of protection. It posits that to the extent that protection is mandated by human rights instruments, States may have a positive obligation to use available technologies to identify and assist vulnerable migrants. It evaluates this possibility against the protection of migrants’ right to life, the prohibition of torture, inhuman and degrading treatment, and the prohibition of slavery and forced labour. In doing so, the article also emphasizes the limits and risks posed by the unrestrained use of new technologies, notably with respect to the protection of migrants’ right to privacy and data protection

Análisis de la movilidad espacial de la población asociada a huracanes a partir de la sombra digital geoespacial derivada de Twitter

Múltiples investigadores creen que el estudio del comportamiento y movilidad espacial de la población ha alcanzado un cuello de botella debido a la rigidez de los métodos tradicionales de investigación en el campo y a la dificultad de acceso a información relevante y de confianza. La sombra digital geoespacial es una de las oportunidades más prometedoras para poder desarrollar y probar nuevas hipótesis en el estudio del comportamiento espacial, pero la aplicación de estos nuevos métodos todavía no ha sido suficientemente explorada en el campo de los riesgos y desastres. Este artículo recoge los últimos avances en este ámbito centrándose en la capacidad de la sombra digital geoespacial de redes sociales (Twitter) como un método innovador para el estudio del comportamiento espacial humano durante emergencias. Esta investigación rastrea las localizaciones de usuarios de Twitter durante el periodo pre-desastre para producir estimaciones del número de evacuados, y en los meses posteriores al desastre para estimaciones de desplazados y del impacto del evento en el turismo