{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,14]],"date-time":"2026-03-14T11:18:30Z","timestamp":1773487110326,"version":"3.50.1"},"reference-count":69,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2021,7,23]],"date-time":"2021-07-23T00:00:00Z","timestamp":1626998400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Federal Ministry of Agriculture, Regions and Tourism","award":["865697"],"award-info":[{"award-number":["865697"]}]},{"DOI":"10.13039\/501100002428","name":"Austrian Science Fund","doi-asserted-by":"publisher","award":["DK W 1237-N23"],"award-info":[{"award-number":["DK W 1237-N23"]}],"id":[{"id":"10.13039\/501100002428","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>In 2015, within the timespan of only a few months, more than a million people made their way from Turkey to Central Europe in the wake of the Syrian civil war. At the time, public authorities and relief organisations struggled with the admission, transfer, care, and accommodation of refugees due to the information gap about ongoing refugee movements. Therefore, we propose an approach utilising machine learning methods and publicly available data to provide more information about refugee movements. The approach combines methods to analyse the textual, temporal and spatial features of social media data and the number of arriving refugees of historical refugee movement statistics to provide relevant and up to date information about refugee movements and expected numbers. The results include spatial patterns and factual information about collective refugee movements extracted from social media data that match actual movement patterns. Furthermore, our approach enables us to forecast and simulate refugee movements to forecast an increase or decrease in the number of incoming refugees and to analyse potential future scenarios. We demonstrate that the approach proposed in this article benefits refugee management and vastly improves the status quo.<\/jats:p>","DOI":"10.3390\/ijgi10080498","type":"journal-article","created":{"date-parts":[[2021,7,23]],"date-time":"2021-07-23T10:31:44Z","timestamp":1627036304000},"page":"498","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Spatio-Temporal Machine Learning Analysis of Social Media Data and Refugee Movement Statistics"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0390-5094","authenticated-orcid":false,"given":"Clemens","family":"Havas","sequence":"first","affiliation":[{"name":"Department of Geoinformatics, University of Salzburg, 5020 Salzburg, Austria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lorenz","family":"Wendlinger","sequence":"additional","affiliation":[{"name":"Department of Data Science, University of Passau, 94032 Passau, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5710-9240","authenticated-orcid":false,"given":"Julian","family":"Stier","sequence":"additional","affiliation":[{"name":"Department of Data Science, University of Passau, 94032 Passau, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2952-5519","authenticated-orcid":false,"given":"Sahib","family":"Julka","sequence":"additional","affiliation":[{"name":"Department of Data Science, University of Passau, 94032 Passau, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Veronika","family":"Krieger","sequence":"additional","affiliation":[{"name":"Department of Geoinformatics, University of Salzburg, 5020 Salzburg, Austria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1721-0453","authenticated-orcid":false,"given":"Cornelia","family":"Ferner","sequence":"additional","affiliation":[{"name":"Information Technology and Systems Management, Salzburg University of Applied Sciences, 5412 Puch, Austria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5029-2425","authenticated-orcid":false,"given":"Andreas","family":"Petutschnig","sequence":"additional","affiliation":[{"name":"Department of Geoinformatics, University of Salzburg, 5020 Salzburg, Austria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3566-5507","authenticated-orcid":false,"given":"Michael","family":"Granitzer","sequence":"additional","affiliation":[{"name":"Department of Data Science, University of Passau, 94032 Passau, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stefan","family":"Wegenkittl","sequence":"additional","affiliation":[{"name":"Information Technology and Systems Management, Salzburg University of Applied Sciences, 5412 Puch, Austria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2233-6926","authenticated-orcid":false,"given":"Bernd","family":"Resch","sequence":"additional","affiliation":[{"name":"Department of Geoinformatics, University of Salzburg, 5020 Salzburg, Austria"},{"name":"Center for Geographic Analysis, Harvard University, Cambridge, MA 02138, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,7,23]]},"reference":[{"key":"ref_1","unstructured":"Eurostat (2020, March 12). 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