What can location-based social media reveal on human migration patterns in Europe?
Numerous visualisation methods have been proposed, including Origin-Destination maps to represent movement patterns gathered from social media; however, visual clutter remains a persistent issue due to complex data dimensionality. Besides, most Origin-Destination maps fail to illustrate the temporal...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2024-12-01
|
| Series: | Journal of Maps |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/17445647.2024.2329168 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841557270995927040 |
|---|---|
| author | Irma Kveladze Johanna Carolina Jokinen Carlos Tapia Henning Sten Hansen |
| author_facet | Irma Kveladze Johanna Carolina Jokinen Carlos Tapia Henning Sten Hansen |
| author_sort | Irma Kveladze |
| collection | DOAJ |
| description | Numerous visualisation methods have been proposed, including Origin-Destination maps to represent movement patterns gathered from social media; however, visual clutter remains a persistent issue due to complex data dimensionality. Besides, most Origin-Destination maps fail to illustrate the temporal dimension of social network phenomena within the geographical environment. To tackle this issue, we propose the visualisation method for geo-located Facebook social-media data while emphasising the time aspect. Based on the citizen-generated data for the European Union (EU), we estimated the EU citizens’ residing or travelling across the EU member states as a means of current and previous destinations to reveal the extent of the hypothetical human migration. The proposed methodology consists of Origin-Destination maps implemented within the time geography framework as a model to support the process of analysis for decision-making. The generated visualisation allows comprehension of the scale of human movement distribution internally within the EU from a space–time perspective. |
| format | Article |
| id | doaj-art-e33f26672028460a9bcce37819fdc832 |
| institution | Kabale University |
| issn | 1744-5647 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Journal of Maps |
| spelling | doaj-art-e33f26672028460a9bcce37819fdc8322025-01-06T14:32:05ZengTaylor & Francis GroupJournal of Maps1744-56472024-12-0120110.1080/17445647.2024.2329168What can location-based social media reveal on human migration patterns in Europe?Irma Kveladze0Johanna Carolina Jokinen1Carlos Tapia2Henning Sten Hansen3Department of Sustainability and Planning, Aalborg University, Copenhagen, DenmarkDepartment of Human Geography, Uppsala University, Uppsala, SwedenNordregio – Nordic Centre for Spatial Development, Stockholm, SwedenDepartment of Sustainability and Planning, Aalborg University, Copenhagen, DenmarkNumerous visualisation methods have been proposed, including Origin-Destination maps to represent movement patterns gathered from social media; however, visual clutter remains a persistent issue due to complex data dimensionality. Besides, most Origin-Destination maps fail to illustrate the temporal dimension of social network phenomena within the geographical environment. To tackle this issue, we propose the visualisation method for geo-located Facebook social-media data while emphasising the time aspect. Based on the citizen-generated data for the European Union (EU), we estimated the EU citizens’ residing or travelling across the EU member states as a means of current and previous destinations to reveal the extent of the hypothetical human migration. The proposed methodology consists of Origin-Destination maps implemented within the time geography framework as a model to support the process of analysis for decision-making. The generated visualisation allows comprehension of the scale of human movement distribution internally within the EU from a space–time perspective.https://www.tandfonline.com/doi/10.1080/17445647.2024.2329168Social mediatime geographyhuman migrationflow mapping |
| spellingShingle | Irma Kveladze Johanna Carolina Jokinen Carlos Tapia Henning Sten Hansen What can location-based social media reveal on human migration patterns in Europe? Journal of Maps Social media time geography human migration flow mapping |
| title | What can location-based social media reveal on human migration patterns in Europe? |
| title_full | What can location-based social media reveal on human migration patterns in Europe? |
| title_fullStr | What can location-based social media reveal on human migration patterns in Europe? |
| title_full_unstemmed | What can location-based social media reveal on human migration patterns in Europe? |
| title_short | What can location-based social media reveal on human migration patterns in Europe? |
| title_sort | what can location based social media reveal on human migration patterns in europe |
| topic | Social media time geography human migration flow mapping |
| url | https://www.tandfonline.com/doi/10.1080/17445647.2024.2329168 |
| work_keys_str_mv | AT irmakveladze whatcanlocationbasedsocialmediarevealonhumanmigrationpatternsineurope AT johannacarolinajokinen whatcanlocationbasedsocialmediarevealonhumanmigrationpatternsineurope AT carlostapia whatcanlocationbasedsocialmediarevealonhumanmigrationpatternsineurope AT henningstenhansen whatcanlocationbasedsocialmediarevealonhumanmigrationpatternsineurope |