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Mapping Cilento: Using geotagged social media data to characterize tourist flows in southern Italy

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  • Chua, Alvin
  • Servillo, Loris
  • Marcheggiani, Ernesto
  • Moere, Andrew Vande

Abstract

New sources of geotagged information derived from social media like Twitter show great promise for geographic research in tourism. This paper describes an approach to analyze geotagged social media data from Twitter to characterize spatial, temporal and demographic features of tourist flows in Cilento - a regional tourist attraction in southern Italy. It demonstrates how the analysis of geotagged social media data yields more detailed spatial, temporal and demographic information of tourist movements, in comparison to the current understanding of tourist flows in the region. The insights obtained from our case study illustrate the potential of the proposed methodology yet attention should be paid to biases in the data as well as methodological limitations when drawing conclusions from analytical results.

Suggested Citation

  • Chua, Alvin & Servillo, Loris & Marcheggiani, Ernesto & Moere, Andrew Vande, 2016. "Mapping Cilento: Using geotagged social media data to characterize tourist flows in southern Italy," Tourism Management, Elsevier, vol. 57(C), pages 295-310.
  • Handle: RePEc:eee:touman:v:57:y:2016:i:c:p:295-310
    DOI: 10.1016/j.tourman.2016.06.013
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    References listed on IDEAS

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    1. Walter Christaller, 1964. "Some Considerations Of Tourism Location In Europe: The Peripheral Regions‐Underdeveloped Countries‐Recreation Areas," Papers in Regional Science, Wiley Blackwell, vol. 12(1), pages 95-105, January.
    2. Daniele Barchiesi & Helen Susannah Moat & Christian Alis & Steven Bishop & Tobias Preis, 2015. "Quantifying International Travel Flows Using Flickr," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-8, July.
    3. Camille Roth & Soong Moon Kang & Michael Batty & Marc Barthélemy, 2011. "Structure of Urban Movements: Polycentric Activity and Entangled Hierarchical Flows," PLOS ONE, Public Library of Science, vol. 6(1), pages 1-8, January.
    4. Robert Schlich & Kay Axhausen, 2003. "Habitual travel behaviour: Evidence from a six-week travel diary," Transportation, Springer, vol. 30(1), pages 13-36, February.
    5. P R Thornton & A M Williams & G Shaw, 1997. "Revisiting Time—Space Diaries: An Exploratory Case Study of Tourist Behaviour in Cornwall, England," Environment and Planning A, , vol. 29(10), pages 1847-1867, October.
    6. Xiang, Zheng & Gretzel, Ulrike, 2010. "Role of social media in online travel information search," Tourism Management, Elsevier, vol. 31(2), pages 179-188.
    7. Marta C. González & César A. Hidalgo & Albert-László Barabási, 2009. "Understanding individual human mobility patterns," Nature, Nature, vol. 458(7235), pages 238-238, March.
    8. Vu, Huy Quan & Li, Gang & Law, Rob & Ye, Ben Haobin, 2015. "Exploring the travel behaviors of inbound tourists to Hong Kong using geotagged photos," Tourism Management, Elsevier, vol. 46(C), pages 222-232.
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