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Aggregating Twitter Text Through Generalized Linear Regression Models For Tweet Popularity Prediction And Automatic Topic Classification, Chen Mo, Jingjing Yin, Isaac Chun-Hai Fung, Zion Tse
Aggregating Twitter Text Through Generalized Linear Regression Models For Tweet Popularity Prediction And Automatic Topic Classification, Chen Mo, Jingjing Yin, Isaac Chun-Hai Fung, Zion Tse
Department of Biostatistics, Epidemiology, and Environmental Health Sciences Faculty Publications
Social media platforms have become accessible resources for health data analysis. However, the advanced computational techniques involved in big data text mining and analysis are challenging for public health data analysts to apply. This study proposes and explores the feasibility of a novel yet straightforward method by regressing the outcome of interest on the aggregated influence scores for association and/or classification analyses based on generalized linear models. The method reduces the document term matrix by transforming text data into a continuous summary score, thereby reducing the data dimension substantially and easing the data sparsity issue of the term matrix. To …
Bios 6331: Regression Analysis In Biostatistics, Jingjing Yin
Bios 6331: Regression Analysis In Biostatistics, Jingjing Yin
Jiann-Ping Hsu College of Public Health Syllabi
This course introduces the methods for analyzing biomedical and health related data using linear regression models. The course will introduce the student to some basic theories in linear models but would mainly focus on applied linear model fitting, regression parameter estimation and hypothesis testing. The course will involve model selection, diagnosis and remedial techniques to correct for assumption violations. The students will learn how to apply SAS procedures PROC REG, PROC CORR, and PROC GLM and interpret the results of analysis. Emphasis will also be placed on the development of critical thinking skills.