Building a model-based personalised recommendation approach for tourist attractions from geotagged social media data

2018 ◽  
Vol 12 (6) ◽  
pp. 661-678 ◽  
Author(s):  
Xiaoyu Sun ◽  
Zhou Huang ◽  
Xia Peng ◽  
Yiran Chen ◽  
Yu Liu
Keyword(s):  
Social Media ◽  
Social Media Data ◽  
Tourist Attractions ◽  
Model Based ◽  
Media Data

Discovering New Tourist Attractions Through Social Media Data: A Case Study in Sabah Malaysia

2018 ◽  
Author(s):  
Maisarah Abdul Halim ◽  
Noraain Mohamed Saraf ◽  
Nur Idzhainee Hashim ◽  
Abdul Rauf Abdul Rasam ◽  
Ahmad Norhisyam Idris ◽  
...  
Keyword(s):  
Social Media ◽  
Social Media Data ◽  
Tourist Attractions ◽  
Media Data

scholarly journals Coastal Tourism Spatial Planning at the Regional Unit: Identifying Coastal Tourism Hotspots Based on Social Media Data

2021 ◽  
Vol 10 (3) ◽  
pp. 167
Author(s):  
Gang Sun Kim ◽  
Joungyoon Chun ◽  
Yoonjung Kim ◽  
Choong-Ki Kim
Keyword(s):  
Social Media ◽  
Spatial Planning ◽  
Regional Scale ◽  
Coastal Tourism ◽  
Spatial Unit ◽  
Social Media Data ◽  
Tourist Attractions ◽  
Distribution Maps ◽  
Media Data ◽  
Spatial Hotspots

There is an increasing need for spatial planning to manage coastal tourism, and applying social media data has emerged as an effective strategy to support coastal tourism spatial planning. Researchers and decision-makers require spatially explicit information that effectively reveals the current visitation state of the region. The purpose of this study is to identify coastal tourism hotspots considering appropriate spatial units in the regional scale using social media data to examine the advantages and limitations of applying spatial hotspots to spatial planning. Data from Flickr and Twitter with 30″ spatial resolution were obtained from four South Korean regions. Coastal tourism hotspots were then derived using Getis-Ord Gi. Comparing the derived hotspot maps with the visitation rate distribution maps, the derived hotspot maps sufficiently identified the spatial influences of visitors and tourist attractions applicable for spatial planning. As the spatial autocorrelation of social media data differs based on the spatial unit, coastal tourism hotspots according to spatial unit are inevitably different. Spatial hotspots derived from the appropriate spatial unit using social media data are useful for coastal tourism spatial planning.

Do social media data indicate visits to tourist attractions? A case study of Shanghai, China

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Huilin Liang ◽  
Qingping Zhang
Keyword(s):  
Social Media ◽  
Survey Data ◽  
Systematic Research ◽  
Social Media Data ◽  
Content Type ◽  
Tourist Attractions ◽  
Cost Efficient ◽  
Positive Correlations ◽  
Use Studies ◽  
Media Data

PurposeCan Chinese social media data (SMD) be used as an alternative to traditional surveys used to understand tourists' visitation of attractions in Chinese cities? The purpose of this paper is to explore this question.Design/methodology/approachPopular tourism SMD sources in China, such as Ctrip, Weibo and Dazhong Dianping (DZDP), were used as data source, and the relationships between these sources and traditional data sources were studied with statistical methods. Data from Shanghai were used in this study since it is rich in tourism resources and developed in information.FindingsA systematic research method was followed and led to the following conclusions: There were positive correlations for attraction visitation between Chinese SMD and traditional survey data; Chinese SMD source could temporally indicate visits to Shanghai tourist attractions; Ctrip SMD generally performed less well than Weibo or DZDP, and different SMD performed differently depending on the specific attractions and time units in the visitation calculation process; and factors including visitation, distance from the city center and the grade of attractions might affect the prediction performance based on data from the SMD. The findings suggest that Chinese SMD could be used as a cost-efficient and reliable proxy for traditional survey data to predict Chinese attraction visitation.Originality/valueThis study applies and improves the methods of SMD reliability in attraction use studies, supplies the gap for premise, basis and foundation for the large amounts of tourism researches using SMD in China and could promote and inspire more efficient and advanced measures in tourism management and urban development.

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