Full Citation
Title: Understanding Demographic and Socioeconomic Bias of Geotagged Twitter Users at the County Level
Citation Type: Miscellaneous
Publication Year: 2019
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Abstract: Massive social media data produced from microblog platforms provide a new data source for studying human dynamics at an unprecedented scale. Meanwhile, population bias in geotagged Twitter users is widely recognized. Understanding the demographic and socioeconomic biases of Twitter users is critical for making reliable inferences on the attitudes and behaviors of the population. However, the existing global models cannot capture the regional variations of the demographic and socioeconomic bias. To bridge the gap, we modeled the relationships between different demographic/socioeconomic factors and geotagged Twitter users for the whole contiguous United States, aiming to understand how the demographic and socioeconomic factors relate to the number of Twitter users at county level. To effectively identify the local Twitter users for each county of the U.S., we integrate three commonly used methods and develop a query approach in a high-performance computing environment. The results demonstrate that we can not only identify how the demographic and socioeconomic factors relate to the number of Twitter users, but can also measure and map how the influence of these factors vary across counties.
User Submitted?: No
Authors: Jiang, Yuqin; Li, Zhenlong; Ye, Xinyue
Publisher: Department of Geography, University of South Carolina
Data Collections: IPUMS NHGIS
Topics: Other, Population Data Science
Countries: United States