Live Q&A for 
UN World Data 
Forum session 
on
Innovative use of Social Media for
Remote Sensing and SDG Monitoring

 

Monday 19 October 2020
15:00 - 16:00 UTC

11:00 - 12:00 New York | 17:00 - 18:00 Paris | 18:00 - 19:00 Doha

 

The IUSSP hosted a live Q&A webinar for the session on "Innovative use of Social Media for Remote Sensing and SDG Monitoring" that was held as part of the UN World Data Forum on 19 October 2020. 

  • To watch the prerecorded session at the UN World Data Forum click here

This prerecorded session was followed by a live Q&A webinar organized by Kiran Garimella, Ingmar Weber, and Emilio Zagheni on behalf of the IUSSP Panel on Digital Demography. The five panelists were Stefano Cresci, Katherine Hoffman Pham, Ridhi Kashyap, Setia Pramana, and Lisa Singh. The Q&A webinar started with brief statements by the panelists summarizing their work. 

  • See full programme below and introductory video here.

 

Video of the Q&A session

 

ORGANIZERS

Kiran Garimella 
- MIT Institute for Data, Systems, and Society (IDSS)

Ingmar Weber 
Qatar Computing Research Institute (QCRI)

Emilio Zagheni  
- Max Planck Institute for Demographic Research (MPIDR) 

 

PANELISTS

Stefano Cresci 
Institute of Informatics and Telematics, National Research Council (IIT-CNR), Pisa, Italy

"Timely and Targeted Information Acquisition from Witnesses via Hybrid Crowdsensing"

Katherine Hoffman Pham
NYU Stern School of Business & UN Global Pulse

"Survey Sampling in the Global South Using Facebook Advertisements"

Ridhi Kashyap
Oxford University

"Using Social Media Advertising Data to Measure the Global Digital Gender Divide"

Setia Pramana
Politeknik Statistika STIS Indonesia & Sub-Directorate Statistical Model Development, BPS Statistics Indonesia

"Innovative Use of Social Media for Remote Sensing and SDGs Monitoring in Indonesia"

Lisa Singh
Massive Data Institute (MDI) & Institute for the Study of International Migration (ISIM), Georgetown University

"Blending Noisy Social Media Signals with Traditional Movement Variables to Predict Forced Migration"