Touristic site attractiveness seen through Twitter
Touristic site attractiveness seen through Twitter
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DOI：
10.1140/epjds/s13688-016-0073-5
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发表时间：
2016-03-25
期刊：
影响因子：
3.6
通讯作者：
Ramasco, Jose J.
中科院分区：
文献类型：
--
作者：
Bassolas, Aleix;Lenormand, Maxime;Ramasco, Jose J.
在日益全球化的世界中，旅游业正在成为中长期旅行的重要贡献者。休闲旅游对当地和全球经济以及环境都有重要影响。因此，对旅游的研究引起了相当大的兴趣。在这项工作中，我们采用一种方法来评估20个最受欢迎的旅游景点的吸引力，全球使用地理定位的推文作为人类流动性的代理。我们首先根据游客居住地的空间分布对旅游景点进行排名。泰姬陵、比萨斜塔和埃菲尔铁塔在这些排名中一直排在前5位。然后，我们进入一个更粗略的尺度，并按居住国对旅行者进行分类。旅游网站的访问数字，然后研究居住国显示，埃菲尔铁塔，时代广场和伦敦塔欢迎每个国家的大多数游客。最后，我们建立了一个网络链接的网站，每当一个用户已被检测到在一个以上的网站。这使我们能够揭示旅游景点之间的关系，并发现哪些景点之间的联系更紧密。
Tourism is becoming a significant contributor to medium and long range travels in an increasingly globalized world. Leisure traveling has an important impact on the local and global economy as well as on the environment. The study of touristic trips is thus raising a considerable interest. In this work, we apply a method to assess the attractiveness of 20 of the most popular touristic sites worldwide using geolocated tweets as a proxy for human mobility. We first rank the touristic sites based on the spatial distribution of the visitors' place of residence. The Taj Mahal, the Pisa Tower and the Eiffel Tower appear consistently in the top 5 in these rankings. We then pass to a coarser scale and classify the travelers by country of residence. Touristic site's visiting figures are then studied by country of residence showing that the Eiffel Tower, Times Square and the London Tower welcome the majority of the visitors of each country. Finally, we build a network linking sites whenever a user has been detected in more than one site. This allow us to unveil relations between touristic sites and find which ones are more tightly interconnected.