Course Code: CS529 Course Name: Topics and Tools in Social Media Data Mining Syllabus: Preamble: Social media have transformed the way people interact, influence, and perform business. This course aims to introduce research topics in social media mining and discuss relevant theoretical foundations, methods, and tools. The Lab component of the couse will engage students with various state-of-the-art big data analytical framework for mining social media content. The class will involve reading papers, presentations, and team projects/assignments. Course contents: Content mining: Topics on social media content mining including retrieval, ranking, trends detection, event detection, event forecasting, opinion mining, and any other relevant topics. Link mining: Topics on social media link analysis including centrality, community, link prediction, influence analysis and any other relevant topics. Log analysis: Topics related to user's behavioral analysis, personlization, recommendation, and any other relevant topics. Lab Component: Various state-of-the-art big data analytics tools for mining social media data. Texts: 1. C.D. Manning, P.Raghavan and H.Schutze, Introduction to Information Retrieval, Cambridge University Press. 2008. 2. M.A. Russell, Mining the Social Web, 2nd Edn., O'Reilly Media, 2013. 3. R.Zafarani, M.A.Abbasi and H.Liu, Social Media Mining: An Introduction, Cambridge University Press, 2014 |