9 Sep 2020 Using Social Media Advertising Data: Recent Applications - Ingmar G. Weber скачать в хорошем качестве

9 Sep 2020 Using Social Media Advertising Data: Recent Applications - Ingmar G. Weber

Presenter: Ingmar G. Weber - Research Director for Social Computing, Qatar Computing Research Institute Abstract: Most of the big internet companies, such as Facebook, Google, or Twitter, generate their revenue from targeted advertising. To offer advertisers 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 New York City who are aged 25-44, who used to live in India, and who primarily use an Apple iPhone 11, Pro Max, 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 this talk, Ingmar will describe how we can tap into these audience estimates to (i) monitor international migration, (ii) track digital gender gaps, and (iii) map wealth inequalities. Bio: Ingmar G. Weber is the Research Director for Social Computing at the Qatar Computing Research Institute. His interdisciplinary research uses large amounts of online data from social media and other sources to study human behavior. Particular topics of interest include quantifying international migration using digital methods, tracking digital gender gaps, mapping social inequalities, and precision public health. Before joining the Qatar Computing Research Institute he studied and worked at the University of Cambridge, the Max Planck Institute for Computer Science, Ecole Polytechnique Fédérale de Lausanne, and Yahoo Research. Ingmar’s research has been cited over 7000 times and he serves as an ACM Distinguished Speaker. Additional resources: For Facebook, we’re using their Graph API. Details here:   / advanced-targeting   The particular method used:   / ad-campaign-delivery-estimate   A wrapper library in Python: https://github.com/maraujo/pySocialWa... And one in R (with some how-to documentation): https://github.com/SofiaG1l/Using_Fac... The data visualizations I showed (and some more): https://fb-nyc.qcri.org/ https://fb-doha.qcri.org/ https://fb-lagos.qcri.org/ https://fb-accra.qcri.org/ https://fb-nairobi.qcri.org/ The project on Digital Gender Gaps: https://www.digitalgendergaps.org/ Lead PI for this at the University of Oxford is Ridhi Kashyap. https://www.nuffield.ox.ac.uk/people/... The recent article on combining Google and Facebook advertising data: Monitoring global digital gender inequality using the online populations of Facebook and Google, in Demographic Research https://www.demographic-research.org/...