Can big data deliver its promises in migration research?
| Published date | 01 April 2022 |
| Author | Albert Ali Salah |
| Date | 01 April 2022 |
| DOI | http://doi.org/10.1111/imig.12984 |
252
|
International Migration. 2022;60:252–255.
wileyonlinelibrary.com/journal/imig
Received: 2 Febr uary 2022
|
Accepted: 3 Febru ary 2022
DOI: 10.1111/imig.12984
COMMENTARY
Can big data deliver its promises in migration
research?
Albert Ali Salah1,2
1Information a nd Computing Scie nces, Utrecht Uni versity, Utrecht, t he Netherlands
2Departm ent of Computer Engin eering, Boğaziç i University, Istan bul, Turkey
Correspondence
Albert Al i Salah, Buys Ballo t Gebouw, Utrecht Uni versity, Princeton plein 5, 3584CC Utre cht, the Netherl ands.
Email: a.a.salah@uu.nl
Funding information
This articl e was funded by H2020 Re search and Innovat ion Programme, Gr ant/Award Number: 8706 61.
As a computer scie ntist working on algorithm s and applications for human b ehaviour analysis since the 90 s, I was
able to witness the rise of "big data," which was jokingly defined by one of my university professors as "data that
would not fit on your computer". Indeed, such is the volume of data constantly generated by humans moving about
with mo bile phones in their pockets, using devices and services that create, store and share informat ion about
such usage , contributing and propagatin g content on social media, that it becom es difficult to organise, classify
and interpret these d igital traces with traditiona l computational approaches. A dd to this the devices and systems
that observe humans, such as surveillance cameras, smart infrastructure elements that log users, remote sensing
and satellite s ystems, an d the picture becomes even more complex. Yet, wit h ample opportunit ies for mone-
tisation, approaches and syst ems were quickly devel oped to process big data. In particul ar, companies quickly
recognised that bi g data collected from custo mers could provide valuab le insights for marketing and o ptimisation
tasks, for content custo misation, user adaptation and mod elling. But such data were also valuable to governmen ts
for decisi on- making and po licy, and for many researchers interested i n human behavi our, including th ose in the
field of migrati on research, looking fo r reliable and granular in dicators of human movement s over the globe.
The main premise of compu tational social science (or social computing) is that large- scale and complex human
behavioural da ta, typically stor ed by companies that benefi t from it for the mentioned pur poses, can be analyse d
and re- purposed to ad dress research questi ons from the social sciences (L azer et al., 2020). In this new par adigm,
carefully cons tructed samples a nd in- depth questions were r eplaced by numbers of subje cts greater by orders of
magnitude, and simple indicators t hat were samp led across much greater temporal and spatial resol utions than
the traditional "snapshots". In addition, these were analysed in an aggregated fashion to provide proxy variables.
For exa mple, in a seminal study rel ated to m igration rese arch, Blumens tock et al. (2015) illustrated that a p er-
son's mobile phone usage his tory could be used to create a wealth indicator. Th ey used mobile p hone call deta il
This is an open ac cess article und er the terms of the Crea tive Commons Attr ibution- NonCommercial License , which permits
use, distri bution and reprod uction in any medium , provided the orig inal work is properl y cited and is not used fo r commercial
purposes.
© 2022 The Auth ors. International Migration published by John W iley & Sons Ltd on behalf o f International Or ganization for
Migration
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