Using user-generated content data to analyze tourist mobility between hotels and attractions in cities/
Cheng, Jin
Using user-generated content data to analyze tourist mobility between hotels and attractions in cities/ - Sage, 2020. - Vol. 47, Issue 5, 2020, ( 826–840 p.)
Attractions and hotels are the two most important elements in tourism activities. However, there is a lack of in-depth analysis of tourist mobility between hotels and attractions. Meanwhile, new means of data collection are opening up opportunities for disclosing the mobility patterns between hotels and attractions. This paper aims at analyzing the network structures and mobility models of tourist mobility from attractions to hotels (TMAH) and tourist mobility from hotels to attractions (TMHA), by using the user-generated content data collated from an open tourism web service. Then the differences between the two tourist mobilities are compared. Through the empirical study of Nanjing, it is found that the influence of distance on the two mobilities is different. The distance has a significant influence on TMAH, and the mobility conforms to the power law distribution. TMHA is more influenced by the ranks of hotels and attractions, and the mobility confirms to the gravity model. The highlight of this paper is to use the new network data to reveal the network structure and mobility laws of the special tourist mobility between hotels and attractions from the perspective of difference comparison.
Using user-generated content data to analyze tourist mobility between hotels and attractions in cities/ - Sage, 2020. - Vol. 47, Issue 5, 2020, ( 826–840 p.)
Attractions and hotels are the two most important elements in tourism activities. However, there is a lack of in-depth analysis of tourist mobility between hotels and attractions. Meanwhile, new means of data collection are opening up opportunities for disclosing the mobility patterns between hotels and attractions. This paper aims at analyzing the network structures and mobility models of tourist mobility from attractions to hotels (TMAH) and tourist mobility from hotels to attractions (TMHA), by using the user-generated content data collated from an open tourism web service. Then the differences between the two tourist mobilities are compared. Through the empirical study of Nanjing, it is found that the influence of distance on the two mobilities is different. The distance has a significant influence on TMAH, and the mobility conforms to the power law distribution. TMHA is more influenced by the ranks of hotels and attractions, and the mobility confirms to the gravity model. The highlight of this paper is to use the new network data to reveal the network structure and mobility laws of the special tourist mobility between hotels and attractions from the perspective of difference comparison.