DS/CSS Seminar: Ingmar Weber

Using Advertising Data to Monitor International Development

Abstract:

Most of the big internet companies, such as Facebook, Google or Twitter, generate their revenue from targeted advertising. To offer advertisers with advanced targeting capabilities, these companies collect large amounts of user data to build elaborate profiles. Based on these profiles an advertiser can then choose to target only, say, female Facebook users living in Doha, Qatar who are aged 25-29, who used to live in the Philippines, who have a self-declared university degree, and who use an iOS device to access Facebook.

To help advertisers in planning their advertising campaigns and the related budget needs, the advertising platforms provide so-called audience estimates on how many of their users match the provided targeting criteria. In the example above, Facebook estimates that there are 3,100 monthly active matching users (as of January 23, 2021). In this talk I’ll describe how, in close collaboration with different UN agencies, we’re tapping into these audience estimates to (i) monitor international migration, (ii) track digital gender gaps, and (iii) map wealth inequalities. We consistently find that, despite fake profiles, and noise in the inference algorithms, data derived from the advertising platforms can provide valuable information that is complementary to other data sources. At the same time, our work shows the risk of identifying vulnerable groups, rather than individuals, which is often not adequately considered in discussions focused on individual privacy.

Speaker Bio:

Ingmar Weber is a German computer scientist known for his research on Computational Social Science in which he uses online data to study population behavior. He is the Research Director for Social Computing at the Qatar Computing Research Institute. He serves as editor-in-chief for the International Conference on Web and Social Media. Weber is also an ACM Distinguished Speaker. Weber's research has been widely covered in the media.

The University of Michigan Data Science / Computational Social Science faculty host a seminar series that features invited talks, research presentations and informal work-in-progress discussions. A list of the scheduled speakers for Winter 2021 (January-April) is available here.