Supportive data for the original research article "What Can Location-Based Social Media Reveal on Human Migration Patterns in Europe?" (Kveladze et al., forthcoming).

Data consists of two files:

Facebook_dataset_20210108_20211102.csv
Facebook_dataset_20210108_20211102_recalculated.csv

Each dataset contains information on the number of active online Facebook users living outside of their country of origin within the European Union. The data was collected through standard CSV format via an advertising API platform by using an R Studio code, and the data collection was conducted twice a month from January to November 2021.

CODE			country code based on user's current location	
GENDER			gender-based targeting, 1=male, 2=female
AGE1			minimum age
AGE2			maximum age
previous_country	country of previous residence
estimate_dau		estimated number of users who logged into Facebook on average daily (Daily Active Users, DAU)
estimate_mau		estimated number of users who logged into Facebook within the last 30 days (Monthly Active Users, MAU)
estimate_ready		TRUE=estimate ready
date_time		Date and time when data collection was conducted

recalculated_dau	recalculated DAU by using the method proposed by Gendronneau et al. (2019), to obtain missing estimates
recalculated_mau	recalculated MAU by using the method proposed by Gendronneau et al. (2019), to obtain missing estimates


Gendronneau, C., Wiśniowski, A., Yildiz, D., Zagheni, E., Fiorio, L., Hsiao, Y., Stepanek, M., Weber, I., Abel, G., & Hoorens, S. (2019). Measuring Labour Mobility and Migration Using Big Data: Exploring the potential of social-media data for measuring EU mobility flows and stocks of EU movers. In Ep68038. Publications Office of the European Union. doi.org/doi:10.2767/474282 

