How are decisions made to move to China? An analysis of information and migration via Google Trends
International migration affects the socio-economic and spatial development of a country. However, mainly due to data limitations, less attention has been given to the specific group of expatriates in China. Specifically, academia does not have a clear understanding of the factors that influence expatriates’ migration to China, and it is unable to predict the size of the expatriate population correctly and accurately. To address these issues, in this study, we used the keyword search index related to “China” on the Google Trends search engine to reflect the mobility intentions, information, and aspirations of the expatriate population based on the migration theory from a psychological perspective and compared the index with the actual number of expatriates according to China’s Seventh Census data. Correlation and regression analyses were performed to reveal the interaction between expatriates’ migration intentions and migration behaviors. This study demonstrates that the information collection of China’s political situation is the primary factor indicating the expatriate population to China, whereas factors such as travel and climate can further predict expatriates’ decision to move to China. In addition, the study demonstrates that Google Trends data can be used as an effective data source for studying expatriate population relocation in China. This paper can provide a reference for formulating many policies in China, such as economic and trade policies, population policies, and social integration policies.
Authors
- Yue Gong (ORCID: https://orcid.org/0000-0002-5630-528X)
- Xinlei Wang (ORCID: https://orcid.org/0000-0002-2065-1105)
- Yu Le (ORCID: https://orcid.org/0009-0002-6343-9961)
Institutions
- Wuhan University (CN)
- Guangdong Urban & Rural Planning and Design Institute (CN)
Publication Details
- Journal
- Transactions in Planning and Urban Research
- Published
- 2025-09-21
- DOI
- https://doi.org/10.1177/27541223251367866
- Primary Topic
- Migration and Labor Dynamics
- Type
- article
- Field-Weighted Citation Impact
- 0.00