This thesis examines the emotional response of consumers to the Patient Protection and Affordable Care Act. Utilizing mixed methodology, Twitter tweets are collected, analyzed, and mapped to highlight spatial trends and distributions. Further analysis in the form of regression follows. Variables such as age, gender, income, type of health insurance, and education are compared against the database of tweets to analyze correlation. This study contributes to the literature on Twitter and geography by continuing research on tweets as a form of volunteered geographic information and how they represent the emotions of individuals. No correlations were found in the results, however, this thesis demonstrates that the use of social media as a data collection platform is a powerful alternative to classic survey studies.
|Commitee:||Ban, Hyowon, Thien, Deborah|
|School:||California State University, Long Beach|
|School Location:||United States -- California|
|Source:||MAI 56/01M(E), Masters Abstracts International|
|Subjects:||Geography, Geographic information science, Demography|
|Keywords:||Big data, GIS, PPACA, Regression, Twitter|
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