Processing and analysis steps used in MSc thesis "Understanding Functional Cross-border Regions from Twitter Data in the Nordics".
Data used in this thesis is not availble in this repo. The Twitter data are collected using the Twitter API, to collect this data, look at the tool tweetsearcher created by Tuomo Väisänen: https://github.com/DigitalGeographyLab/tweetsearcher.
Data pre-processing and cleaning is found in nordic_line_creation.py, nordic_data_cleaning.py, and regions are assigned in nordic_assign_regions.py.
The Jupyter Notebook nordic_cross_border_mobility.ipynb lists out the steps of data exploration, temporal analyis, correlation analysis, and connectedness explorations.
General maps are created with all_points_maps.py and all_lines_maps.py. The calculations of functional cross-border regions can be found in functional_area_maps.py.
Images from the thesis is found in the imgs folder.
The thesis and tools are developed in cooperation with the Digital Geography Lab at the University of Helsinki and as a part of the BORDERSPACE -- Tracing Interactions and Mobilities Beyond State Borders: Towards New Transnational Spaces project.
Collection of data is based upon the tool tweetsearcher created by Tuomo Väisänen: https://github.com/DigitalGeographyLab/tweetsearcher
Methodology builds upon the work of Samuli Massinen and his repo: https://github.com/DigitalGeographyLab/cross-border-mobility-twitter