Abstract
In our increasingly connected world, individuals produce continuous streams of data through their constant interactions with the Internet. This data is opening up opportunities to measure human behaviour that was previously time consuming or expensive to capture. Here, we explore whether data from online photographs can be used to estimate travel statistics on a global scale. We draw on the locations attached to 69 million publicly shared photographs to infer the global travel patterns of almost half a million users of the photo-sharing platform Flickr. We find that our photo-based estimates of tourist arrival statistics for the G7 countries Canada, France, Germany, Italy, Japan, the United Kingdom and the United States correlate with the corresponding official statistics released by those countries. Our results highlight the potential for vast volumes of online data to inform the generation of timely, low-cost indicators of the state of society. We discuss practical considerations that remain before this methodology could be used in the production of official statistics.
Highlights
With the rise of the Internet, many of our everyday activities leave behind traces across a wide range of online platforms
Our analysis focuses on official statistics data for 2014, as corresponding tourist arrival data is available for all G7 countries for that year as detailed in the Data section
We find that our photo-based estimates of tourist arrivals in the G7 countries correlate with the official statistics released by Canada, France, Germany, Italy, Japan, the UK and the US
Summary
With the rise of the Internet, many of our everyday activities leave behind traces across a wide range of online platforms. Publicly available data on what Internet users search for on Google, pages they access on Wikipedia and content they share on Twitter have fuelled the rapidly developing interdisciplinary field of computational social science (Botta et al, 2015; Ginsberg et al, 2009; King, 2011; Lazer et al, 2009, 2014; Preis and Moat, 2014; Vespignani, 2009) These high-speed streams of data reflect the behaviour of humans, often at global scale, and sometimes at low cost. A recent review of economic statistics in the UK stated that better use of such novel forms of data “has the potential to transform the provision of economic statistics” and that the UK Office for National Statistics “will need to build up its capability to handle such data” (Bean, 2016)
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