# 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.

## Key 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.

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Source: https://tomesphere.com/paper/1704.04739