April
10

PAA2025

Introduction to Digital Trace Data for Migration Studies

Asli Ebru Sanlitürk and Daniela Perrotta
Population Association of America 2025 Annual Meeting, Washington D.C., April 10, 2025

© istockphoto.com / mustafaU

You can register for the workshop while registering for the PAA 2025 conference in Washington D.C. or, if you already have signed up for the conference, add it to your registration on the PAA portal.

Registration Deadline: February 3, 2025

When: 1:00 PM – 5:00 PM

About the workshop

Main sources of data in the study of demography have usually been collected from traditional data, i.e., census, survey, and register data. Although they provide useful information, they come with some limitations. First of all, the cost associated with collecting traditional data is high. It is also time consuming and provides low quality information on some of the important demographic information such as seasonal migrants and short-term stays, and studies show evidence that migrants are prone to higher non-response rates in surveys. Asylum seekers are also mostly absent from national surveys, unless they are specifically targeted for surveys aiming to help refugee policies, yet they are known to use social media channels extensively. Migrants benefit from online communication and information platforms, which in turn transform migrant networks, making it necessary for social scientists to study digital networks with a closer focus.

Today, we are provided with innovative and novel data from social media and search platforms, where the data comes in various formats such as text, audio, image, and video. The amount of data that is produced by individual users is increasing significantly, often referred to as big data. In recent years, many researchers have taken advantage of such data to study various types of social phenomena such as migration, public health, gender gaps, political polarization, and much more. Digital trace data can provide researchers information on hard-to-reach populations that is relatively easy and less costly to collect. Such data can be collected both in real time and retrospectively, offering the opportunity for the analysis of more recent (or real time) events with a comparative perspective to the past. Digital trace data also include detailed information and allow for monitoring the mobility with geo-tagging features. However, these innovative data also come with different types of limitations, biases and challenges, requiring researchers to be equipped with different types of skills and approaches to deal with these types of data. 

In this fourth edition of the workshop we aim to introduce the fundamentals of digital trace data in migration studies and utilizing such data to gain insights into migration patterns. We focus specifically on three data sources; LinkedIn, Google Trends and Wikipedia. We plan to begin the session by introducing the data format, data collection methods, related literature, and empirical findings. While we use LinkedIn, Google Trends and Wikipedia as the exemplary cases, we consider other sources (e.g. Facebook) also part of the workshop program, to introduce and discuss the general challenges, opportunities and biases of digital trace data.

This workshop will be presenting methods using R and Python. The participants are welcome to choose freely depending on their preferences.

The Max Planck Institute for Demographic Research (MPIDR) in Rostock is one of the leading demographic research centers in the world. It's part of the Max Planck Society, the internationally renowned German research society.