An analysis of The Central Bank of The Republic of Türkiye (CBRT)'s monetary policy communication with text mining

In the last twenty years, most of the central banks have started to use short term interest rates as a main monetary policy tool to control inflation. Moreover, communication strategy has become one of their most important policy tools through time. Especially, after the 2008 Global Financial Crisis, when the nominal interest rates hit the zero lower bound, central banks have used communication policy very effectively to form expectations. As a result of these developments, there is a growing body of literature examining the communication strategies of central banks. Advances in text mining literature also enables to analyze central bank texts by using alternative methods. Under this background, this thesis analyses the Central Bank of the Republic of Türkiye's (CBRT) Monetary Policy Committee decision announcements for the period 2006-2020. In the analysis, different text mining techniques, data cleaning and preprocessing, descriptive text statistics and sentiment analysis of announcements, and machine learning applications are used and contributions to policy making process are discussed.