This will be listed as an option for the new BSc in Politics and Data Science.
This will be listed as an option for the new BSc in Politics and Data Science.
16 hours and 40 minutes of lectures and 13 hours and 30 minutes of classes in the LT. A combination of classes and lectures totalling 33.5 hours across Lent Term (counting the 50 mins as an hour). This course has a Reading Week in Week 6 of LT.
Students will work on weekly, structured problem sets in the staff-led class sessions. Five of these will be for formative assessment. Example solutions will be provided at the end of each week.
Benoit, Kenneth. 2020. ?Text as Data: An Overview.? In Curini, Luigi and Robert Franzese, eds. Handbook of Research Methods in Political Science and International Relations. Thousand Oaks: Sage. pp461-497. Grimmer, Justin and Brandon M. Stewart. 2013. ?Text as Data: The Promise and Pitfalls of Automatic Content Analysis Methods for Political Texts.? Political Analysis 21(3):267?297. Loughran, Tim and Bill McDonald. 2011. ?When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10-Ks.? The Journal of Finance 66(1, February): 35?65. Evans, Michael, Wayne McIntosh, Jimmy Lin and Cynthia Cates. 2007. ?Recounting the Courts? Applying Automated Content Analysis to Enhance Empirical Legal Research.? Journal of Empirical Legal Studies 4(4, December):1007?1039. quanteda: An R package for quantitative text analysis. http://kbenoit.github.io/quanteda/
Take-home assessment (60%) and problem sets (40%) in the LT. Five summative problem sets will be marked in five of the weeks. These will constitute 40% of the final overall mark.?The take-home assessment (60%) will be submitted in the week following the end of the Lent Term.