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CaGIS Publication Led by Binbin Lin on Mitigating Demographic Biases in Social Media for Sentiment Analysis

One Covid-19 research led by Gear Lab member Ms. Binbin Lin, a Ph.D. student, is recently accepted by Cartography and Geographic Information Science Journal! Big Congratulations!


The manuscript is entitled "Sensing the pulse of the pandemic: unveiling the geographical and demographic disparities of public sentiment toward COVID-19 through social media," This study explores solutions to pinpoint and alleviate the demographic biases in social media analysis through a case study estimating the public sentiment about COVID-19 using Twitter data. We analyzed the pandemic-related Twitter data in the U.S. during 2020–2021. The results show higher proportions of female and adolescent Twitter users expressing negative emotions to COVID-19. The SAD index unveils that the public sentiment toward COVID-19 was most negative in January and February 2020 and most positive in April 2020. Vermont and Wyoming were the most positive and negative states toward COVID-19.


For more:

Lin, B., Zou, L., Zhao, B., Huang, X., Cai, H., Yang, M. and Zhou, B., 2024. Sensing the pulse of the pandemic: unveiling the geographical and demographic disparities of public sentiment toward COVID-19 through social media. Cartography and Geographic Information Science, pp.1-19.



(a) spatial pattern of Twitter Users (b) Spatial pattern of sentiments

a: Numbers and ratios of Twitter users who tweeted about COVID-19 by gender and age at the state level in the U.S. during the period of 2020 to 2021 (circle diameter signifies the number of Twitter users); b: Percentages of negative Twitter users toward COVID-19 within various social groups at the state level across the U.S. during the period of 2020 to 2021.


Congratulations! We look forward to hearing more achievements from GEAR Lab! Gig'em!

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