This project has two objectives. First, it studies data mining and statistical methods for collecting and analyzing online longitudinal data for media coverage and public attention. In this project, web scraping algorithms are developed based on Python. Statistical methods required for longitudinal data are also studied. Once these web scraping programs and statistical methods are established, they will be used not only for academic research but also for the advanced data analytics courses at CMU-Q, including Data Mining and Business Analytics and Methods for Statistical Data Science. Second, this project uses online longitudinal data for media coverage and public attention to conduct original academic research. This project aims to produce two research papers concerned with the Qatar-Gulf diplomatic crisis and the gun control issue in the United States, respectively. Exploiting the longitudinal data that provide repeated measures for a variety of geographical regions, this project’s two papers examine 1) whether and how the Qatar-Gulf diplomatic crisis drew international attention to Qatar, and 2) how public attention to gun control evolves over time in the U.S., with a focus on how quickly such attention fades away.