Tourism Trend Analysis Using Big Data (2020)
[Customer]
- Public Institutions in the Cultural and Tourism Administration Sector
[Key Objectives]
- Leverage social media big data and tourist movement data to analyze travel trends over the past three years and forecast future patterns.
- Social Media Big Data Analysis: Investigate public perceptions and discussions around travel.
- Tourist Movement Pattern Analysis: Examine trends and changes in tourist mobility.
[Key Activities]
Tasks | Social Media Big Data Analysis | Tourist Population Movement Pattern Analysis |
Data Collection | - Data from major social media platforms (Facebook, YouTube, Twitter, Instagram) | - Telecom data - Navigation destination search data - Credit card transaction data |
Data Progressing | - Social Media Data Filtering • Review of analysis suitability • Removal of spam • Exclusion of irrelevant SNS - Keyword Refinement • Natural language processing • Dictionary construction | - Tourist population movement network modeling - Setting movement volume threshold |
Data Analysis | - Topic Analysis • Extraction of subtopics → Extraction of mega topics • Analysis of topic trends by year - Keyword Network Analysis | - Tourist population movement network analysis • Analysis of temporal changes in tourist population movement • Extraction of tourist hub areas and tourism regions (clusters) through network structure visualization |
* Data Collection: Use of NetMiner Extension Program (SNS Data Collector)
* Data Analysis: Use of NetMiner
[Utilization of Results]
- Understanding social media trends in travel
- Identification of tourist hub areas and tourism regions (Clusters)
ð Deriving Implications
Photo: Unsplash by Cyprien Delaporte