The network structure of visited locations according to geotagged social media photos

TL;DR

This paper reconstructs a large-scale network of tourist locations in Europe using geotagged Flickr photos, revealing the complex structure of tourism systems through network analysis.

Contribution

It introduces a method to build and analyze a detailed network of visited locations from social media data, providing insights into tourism system structures.

Findings

The network has around 180,000 vertices and 32 million edges.

The network exhibits complex structural properties.

Reveals potential for understanding tourism dynamics through social media data.

Abstract

Businesses, tourism attractions, public transportation hubs and other points of interest are not isolated but part of a collaborative system. Making such collaborative network surface is not always an easy task. The existence of data-rich environments can assist in the reconstruction of collaborative networks. They shed light into how their members operate and reveal a potential for value creation via collaborative approaches. Social media data are an example of a means to accomplish this task. In this paper, we reconstruct a network of tourist locations using fine-grained data from Flickr, an online community for photo sharing. We have used a publicly available set of Flickr data provided by Yahoo! Labs. To analyse the complex structure of tourism systems, we have reconstructed a network of visited locations in Europe, resulting in around 180,000 vertices and over 32 million edges. An analysis of the resulting network properties reveals its complex structure.