Our main goal was to determine communities of
tourists based on information collected on some
social network. The tourists under studies are
those who visit the UNESCOs heritage. "How data collected on the
social networks
could be useful for the analysis of UNESCO s heritage ?"
"How to spotlight the links between the
UNESCOs sites depending on the tourists behaviors ?"
Extraction and Characterization of French World Heritage Sites
from 3 social Networking Websites
World Heritage are important travel destinations, that if
managed properly, have
great potential impact for local economic development, and
long-term
sustainability.
Thanks to social networking sites, tourists can share easily
opinions and holiday
photographs with their friends.
In order to study this type of tourism, we used geolocalized
data coming from
Flickr, Instagram and Panoramio.
Introduction
In the project team, we are four ESILVs students, in third year
engineering. Three of us are studying Financial Engineering, the
last one studying informatics and
Numerical Sciences.
We will be working closely with our teachers Mrs Berengre
Branchet, Mrs Sairi
Tatianna Pieros, Mr Gal Chareyron, Mr Jerme Da Rugna and our
partner EIREST
laboratory (Interdisciplinary Research Team on Tourism) from the
University of
Paris I Panthon-Sorbonne. The EIREST is one of the laboratories
associated with
Labex Dynamite, interdisciplinary project (geography, economics,
sociology, history
and archeology) devoted to the study of future territories by
combining
urbanization, sustainable development and new social
dynamics.
Problematic
Extraction of French World Heritage Sites
Strasbourg - Grande le Historic Fortified City of
Carcassonne
#users: 16920
Overlap region :73,59%
Size area aggregated :
87,94%
#users: 19874
Overlap region :80,08%
Size area aggregated :
112,87%
#users: 4961
Overlap region :100%
Size area aggregated :
284,66%
#users: 4957
Overlap region :90,43%
Size area aggregated :
112,62%
First algorithm which follows group of tourists
Second algorithm which uses density of pictures
and occurence of tourists
Outline of the zone of UNESCO
Overall, cluster aggregation is
better than the tracking algorithm
to characterize the UNESCO
heritage, but some sites can not be
aggregated because of the lack of
photographs.
Connections between French World Heritage Sites
We carried out a clustering of the French
sites based on the number of photographs,
the ratio of local and international users on
each UNESCO sites.
Sites which have common particularities are
classified in the same cluster. For instance
all the religious sites are classified in the
same cluster. Likewise, all the roman sites
are classified together and so have strong
links between them. We could deduce that
they are frequented by the same profile of
users.
Key figures for 2013
1007 sites
39 sites
335.842
10.620
4.272.940
645.260
996.442
30.385
Team
