You are perusing an article from the archives. Lately, we have gone through major updates. Therefore, it is possible that you will experience minor quirks in layout when reading older articles. To provide you an improved reading experience, we have started to clean our pearls from the past. Just keep reading.


Google search activity for asylum (red) and asylum applications (blue) in Germany 2013-2016 from Syria. Sources: UNHCR and Google Trends.

The refugee crisis of 2015 could have been predicted with a method developed by Joonas Tuhkuri, a Finnish researcher in Massachusetts Institute of Technology in the US.

“The refugee crisis was a real surprise but it wouldn’t have had to be. According to the search data provided by Google, it shows that people started to look for information on how to seek asylum from Europe three months before [the crisis],” Tuhkuri said in an interview with EVA.

For example, Syrians used search terms “asylum in Germany.” In Iraq, similar words were used to seek asylum from Germany and Sweden; Afghans used equivalent words in the Persian language.

Big data

Tuhkuri analyzes big data in his research.

According to Tuhkuri, by using Google’s data we could have forecast the number of refugees arriving at our borders. “If we would have been able to have a look at the data beforehand, we would have had a better picture of the number of the arrivals,” he said.

In 2016, he presented his method to the European Commission. “They were really interested in my method. They asked me to speak about how to forecast unemployment with the aid of big data, and I also spoke about other opportunities to use it,” he said.