Coffee Hour: Social media: an emerging data source for human mobility studies

Friday, January 29, 2016 - 3:30pm
Refreshments are offered in 319 Walker Building at 3:30 p.m. The lecture begins in 112 Walker Building at 4:00 p.m.

About the talk

While most previous studies relied heavily on the expensive travel-diary type data, social media now emerges as a new data source to describe human daily activity patterns and population dynamics. Despite the various appealing aspects of social media data, including a much larger numbers of “subjects," low acquisition cost and relatively wide geographical and international coverage, these data also have many limitations, including sparseness and irregularity of sampling points over space and time, and the lack of background information of users, such as home locations and socioeconomic status (SES). A major objective of this talk is to explore challenges, solutions and the extent that Twitter data can be used to support human mobility studies. A method to model and visualize regular human mobility patterns using online trajectories with uncertainty will be presented. I will also introduce an approach to determine users’ home and work locations in order to examine the activity patterns of individuals. To infer the SES of individuals, I then incorporate the American Community Survey (ACS) data. As a case study, I analyze the activity patterns of Twitter users with different SESs using data for Washington, DC.

About the speaker

Qunying HuangQunying Huang is currently an assistant professor in the Department of Geography at University of Wisconsin-Madison (UW-Madison). She holds a B.S. from Central South University (2004), M.S. from Peking University (2007) and Ph.D. from George Mason University (2011).Her fields of expertise are geographic information science (GIScience), Cyberinfrastucture, spatiotemporal big data mining, and large-scale environmental modeling and simulation. She is very interested in applying different computing models, such as cluster, grid, GPU, citizen computing, and especially cloud computing to address contemporary big data and computing challenges in the GIScience. Most recently, she is leveraging and mining social media data for various applications, such as emergency response, disaster coordination, and human mobility. She published over 50 scientific articles, and edited two books.  Huang is a fellow for Next Generation of Hazards & Disasters Researchers, and CyberGIS. Huang serves as chair for AAG Cyberinfrastructure Specialty Group (CISG). She helped start the cloud computing cluster within the Earth Science Information Partnership (ESIP).


Suggested reading

1) Huang Q., Wong D., 2015. Modeling and Visualizing Regular Human Mobility Patterns with Uncertainty: An Example Using Twitter Data. Annals of the Association of American Geographers, 105(6): 1179-1197.

2) Huang Q., Cao G., Wang C., 2014. From Where Do Tweets Originate? - A GIS Approach for User Location Inference. In Proceedings of the 7th ACM SIGSPATIAL International Workshop on Location-Based Social Networks (LBSN '14), ACM SIGSPATIAL 2014, Nov 6-9, Dallas, TX.        

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