Symposium on Human Dynamics Research: Uncovering the Bias in Big Data: Who is under-represented and how can we help#1
The session recording will be archived on the site until June 25th, 2023
This session was streamed but not recorded
Date: 3/23/2023
Time: 2:40 PM - 4:00 PM
Room: Centennial Ballroom C, Hyatt Regency, Third Floor
Type: Paper,
Theme: Toward More Just Geographies
Curated Track: AAG's GeoEthics Initiative and Related Effort
Sponsor Group(s):
No Sponsor Group Associated with this Session
Organizer(s):
Jiaxin Du Texas A&M University
Yunhe Cui University of Connecticut
Diya Li Texas A&M University
Huan Ning University of South Carolina
Xinyue Ye Texas A&M University
Chair(s):
Description:
Geospatial big data, including check-in data, mobile phone GPS trajectories, ride-sharing records, social media data, and remote sensing data are the foundation of much spatial data research. Although they served as the foundation for crucial insights into human activity patterns or public opinion, the most mentioned limitation of such research are the sampling bias embedded in the data acquisition and pre-processing and the uncertainty of the models that performance could be different due to the inconsistency of usage. For example, certain groups without digital access or social media literacy are systematically left behind in such research. Often, those groups are minorities, low-income groups, and socially marginalized groups. Any research would be prone to bias and raise social injustice if the data sampling issue is not properly addressed. This session welcomes presentations identifying or addressing the potential bias in spatial-temporal big data (such as social media data, VGI, sensor data, GPS tracks, transaction data, street view images, and remote sensing).
Presentations (if applicable) and Session Agenda:
Ruowei Liu, University of Georgia |
Understand and Evaluate the Sampling Bias in Geotagged Social Media Data |
Sterling Quinn, Central Washington University |
How well do online maps include Latino-oriented local businesses? A study in the Inland Northwest of the United States |
Ofir Klein, University of Kentucky |
Centering the researcher in big data: a topical analysis of Covid-19 tweets |
Romeo Joe Quintero |
Whose Lives Do We Honour in Map Making? |
Kejin Wang, Louisiana State University |
Mining Social Media for Improved Fairness: A Case Study of Hurricane Harvey |
Non-Presenting Participants
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Symposium on Human Dynamics Research: Uncovering the Bias in Big Data: Who is under-represented and how can we help#1
Description
Type: Paper,
Date: 3/23/2023
Time: 2:40 PM - 4:00 PM
Room: Centennial Ballroom C, Hyatt Regency, Third Floor
Contact the Primary Organizer
Jiaxin Du Texas A&M University
jiaxin.du@tamu.edu
Session Sponsored By
