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Quantifying International Travel Flows Using Flickr.

Barchiesi D, Moat HS, Alis C, Bishop S, Preis T - PLoS ONE (2015)

Bottom Line: In some cases, the fast, cheap measurements of human behaviour gained from these platforms may offer an alternative to gathering such measurements using traditional, time consuming and expensive surveys.Here, we use geotagged photographs uploaded to the photo-sharing website Flickr to quantify international travel flows, by extracting the location of users and inferring trajectories to track their movement across time.We find that Flickr based estimates of the number of visitors to the United Kingdom significantly correlate with the official estimates released by the UK Office for National Statistics, for 28 countries for which official estimates are calculated.

View Article: PubMed Central - PubMed

Affiliation: Department of Mathematics, University College London, London, United Kingdom.

ABSTRACT
Online social media platforms are opening up new opportunities to analyse human behaviour on an unprecedented scale. In some cases, the fast, cheap measurements of human behaviour gained from these platforms may offer an alternative to gathering such measurements using traditional, time consuming and expensive surveys. Here, we use geotagged photographs uploaded to the photo-sharing website Flickr to quantify international travel flows, by extracting the location of users and inferring trajectories to track their movement across time. We find that Flickr based estimates of the number of visitors to the United Kingdom significantly correlate with the official estimates released by the UK Office for National Statistics, for 28 countries for which official estimates are calculated. Our findings underline the potential for indicators of key aspects of human behaviour, such as mobility, to be generated from data attached to the vast volumes of photographs posted online.

No MeSH data available.


Related in: MedlinePlus

Comparison of estimates of the number of visitors to the UK using standard socio-economic indicators, and estimates using Flickr data.We analyse data for all 28 countries of origin depicted in Fig 1, from 2008 to 2013. (A) Estimates of the average number of visitors per year to the UK, generated by a regression model using the detected number of Flickr users visiting the UK only. (B) Estimates generated using five socio-economic indicators, namely whether the country of origin has English as an official language, the population of the country, the GDP per capita of the country, the distance between the largest city in the country and London, and the stringency of UK visa requirements for citizens of the country. (C) Estimates generated by a combined model, using both Flickr data and the socio-economic indicators. We find that the combined Flickr and socio-economic model significantly outperforms both the Flickr model (F(5,21) = 4.75, p < 0.005) and the socio-economic model (F(1,21) = 14.57, p < 0.005). (D) In the combined model, regression coefficients for Flickr, language and distance are significantly different from 0. Error bars indicate 95% confidence intervals.
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pone.0128470.g002: Comparison of estimates of the number of visitors to the UK using standard socio-economic indicators, and estimates using Flickr data.We analyse data for all 28 countries of origin depicted in Fig 1, from 2008 to 2013. (A) Estimates of the average number of visitors per year to the UK, generated by a regression model using the detected number of Flickr users visiting the UK only. (B) Estimates generated using five socio-economic indicators, namely whether the country of origin has English as an official language, the population of the country, the GDP per capita of the country, the distance between the largest city in the country and London, and the stringency of UK visa requirements for citizens of the country. (C) Estimates generated by a combined model, using both Flickr data and the socio-economic indicators. We find that the combined Flickr and socio-economic model significantly outperforms both the Flickr model (F(5,21) = 4.75, p < 0.005) and the socio-economic model (F(1,21) = 14.57, p < 0.005). (D) In the combined model, regression coefficients for Flickr, language and distance are significantly different from 0. Error bars indicate 95% confidence intervals.

Mentions: We investigate how estimates of the average number of visitors to the UK per year derived from Flickr data compare to estimates of the number of visitors using standard socio-economic indicators. We find no significant difference between the performance of a linear regression model generating estimates from the detected number of Flickr users visiting the UK (R2 = 0.74, Fig 2A) and the performance of a linear regression model generating estimates using five key socio-economic indicators, namely whether the country of origin has English as an official language, the population of the country, the GDP per capita of the country, the distance between the largest city in the country and London, and the stringency of UK visa requirements for citizens of the country (R2 = 0.79, Fig 2B; F(4,22) = 1.42, p > 0.05). However, we find that estimates of the average number of visitors to the UK per year derived from a combined model using both Flickr data and the socio-economic indicators (R2 = 0.88, Fig 2C) are significantly more accurate than estimates generated from Flickr data (F(5,21) = 4.75, p < 0.005) or socio-economic data alone (F(1,21) = 14.57, p < 0.005). We find that information on how far away a country is and whether a country has English as an official language is of particular useful in improving Flickr-based estimates (Fig 2D).


Quantifying International Travel Flows Using Flickr.

Barchiesi D, Moat HS, Alis C, Bishop S, Preis T - PLoS ONE (2015)

Comparison of estimates of the number of visitors to the UK using standard socio-economic indicators, and estimates using Flickr data.We analyse data for all 28 countries of origin depicted in Fig 1, from 2008 to 2013. (A) Estimates of the average number of visitors per year to the UK, generated by a regression model using the detected number of Flickr users visiting the UK only. (B) Estimates generated using five socio-economic indicators, namely whether the country of origin has English as an official language, the population of the country, the GDP per capita of the country, the distance between the largest city in the country and London, and the stringency of UK visa requirements for citizens of the country. (C) Estimates generated by a combined model, using both Flickr data and the socio-economic indicators. We find that the combined Flickr and socio-economic model significantly outperforms both the Flickr model (F(5,21) = 4.75, p < 0.005) and the socio-economic model (F(1,21) = 14.57, p < 0.005). (D) In the combined model, regression coefficients for Flickr, language and distance are significantly different from 0. Error bars indicate 95% confidence intervals.
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Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4493158&req=5

pone.0128470.g002: Comparison of estimates of the number of visitors to the UK using standard socio-economic indicators, and estimates using Flickr data.We analyse data for all 28 countries of origin depicted in Fig 1, from 2008 to 2013. (A) Estimates of the average number of visitors per year to the UK, generated by a regression model using the detected number of Flickr users visiting the UK only. (B) Estimates generated using five socio-economic indicators, namely whether the country of origin has English as an official language, the population of the country, the GDP per capita of the country, the distance between the largest city in the country and London, and the stringency of UK visa requirements for citizens of the country. (C) Estimates generated by a combined model, using both Flickr data and the socio-economic indicators. We find that the combined Flickr and socio-economic model significantly outperforms both the Flickr model (F(5,21) = 4.75, p < 0.005) and the socio-economic model (F(1,21) = 14.57, p < 0.005). (D) In the combined model, regression coefficients for Flickr, language and distance are significantly different from 0. Error bars indicate 95% confidence intervals.
Mentions: We investigate how estimates of the average number of visitors to the UK per year derived from Flickr data compare to estimates of the number of visitors using standard socio-economic indicators. We find no significant difference between the performance of a linear regression model generating estimates from the detected number of Flickr users visiting the UK (R2 = 0.74, Fig 2A) and the performance of a linear regression model generating estimates using five key socio-economic indicators, namely whether the country of origin has English as an official language, the population of the country, the GDP per capita of the country, the distance between the largest city in the country and London, and the stringency of UK visa requirements for citizens of the country (R2 = 0.79, Fig 2B; F(4,22) = 1.42, p > 0.05). However, we find that estimates of the average number of visitors to the UK per year derived from a combined model using both Flickr data and the socio-economic indicators (R2 = 0.88, Fig 2C) are significantly more accurate than estimates generated from Flickr data (F(5,21) = 4.75, p < 0.005) or socio-economic data alone (F(1,21) = 14.57, p < 0.005). We find that information on how far away a country is and whether a country has English as an official language is of particular useful in improving Flickr-based estimates (Fig 2D).

Bottom Line: In some cases, the fast, cheap measurements of human behaviour gained from these platforms may offer an alternative to gathering such measurements using traditional, time consuming and expensive surveys.Here, we use geotagged photographs uploaded to the photo-sharing website Flickr to quantify international travel flows, by extracting the location of users and inferring trajectories to track their movement across time.We find that Flickr based estimates of the number of visitors to the United Kingdom significantly correlate with the official estimates released by the UK Office for National Statistics, for 28 countries for which official estimates are calculated.

View Article: PubMed Central - PubMed

Affiliation: Department of Mathematics, University College London, London, United Kingdom.

ABSTRACT
Online social media platforms are opening up new opportunities to analyse human behaviour on an unprecedented scale. In some cases, the fast, cheap measurements of human behaviour gained from these platforms may offer an alternative to gathering such measurements using traditional, time consuming and expensive surveys. Here, we use geotagged photographs uploaded to the photo-sharing website Flickr to quantify international travel flows, by extracting the location of users and inferring trajectories to track their movement across time. We find that Flickr based estimates of the number of visitors to the United Kingdom significantly correlate with the official estimates released by the UK Office for National Statistics, for 28 countries for which official estimates are calculated. Our findings underline the potential for indicators of key aspects of human behaviour, such as mobility, to be generated from data attached to the vast volumes of photographs posted online.

No MeSH data available.


Related in: MedlinePlus