Researchers say analysis of social media posts can give an early warning about when and where people move in crises. This could help humanitarian agencies respond faster when surveys and field data are hard to collect.
The study appears in EPJ Data Science. The team looked at nearly 2 million posts in three languages on X. They studied three cases: Ukraine, Sudan and Venezuela. Ukraine saw 10.6 million people displaced, Sudan about 12.8 million, and Venezuela about 7 million.
Researchers found that sentiment labels (positive, negative, neutral) were more reliable than emotion labels for predicting movements. Pretrained language models gave the most useful early warning. The authors say the method works best in conflict settings and should be used with traditional data to avoid false alarms.
Difficult words
- predict — To say what will happen in the future.
- displaced — People who have been forced to leave their home.
- information — Facts or details about something.
- important — Having great significance or value.
- traditional — Relating to customs or practices from the past.
Tip: hover, focus or tap highlighted words in the article to see quick definitions while you read or listen.
Discussion questions
- How can social media improve aid delivery during crises?
- What other tools might help in similar situations?
- Why is it important to provide aid to displaced people?
Related articles
Data centers and mining could raise US power costs by 2030
A new study warns that growing electricity use by data centers and cryptocurrency mining could raise power prices and CO2 emissions in the United States by 2030. Researchers modelled hourly power needs across 26 regions to find likely impacts.
Zenica School of Comics: Art and Education for Children
The Zenica School of Comics began during the 1992–95 war and has taught around 200 young artists. The school still runs, faces changes from tablets and AI, and the regional comics scene survives through festivals and cooperation.
