The Network Structure of Visited Locations According to Geotagged Social Media Photos

被引:2
作者
Junker, Christian [1 ]
Akbar, Zaenal [2 ]
Cuquet, Marti [2 ]
机构
[1] Fanlens Io, Baumkirchen, Austria
[2] Univ Innsbruck, Technikerstr 21a, A-6020 Innsbruck, Austria
来源
COLLABORATION IN A DATA-RICH WORLD | 2017年 / 506卷
关键词
Complex networks; Social media; Collaborative tourism; YFCC100M dataset; Travelling patterns; Social networks; BIG-DATA; TOURISM; SCIENCE;
D O I
10.1007/978-3-319-65151-4_26
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:276 / 283
页数:8
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