/ecb

Text Mining Project: Analyse ECB's official press statements

Primary LanguagePython

Text Mining Project

Title: Analyse ECB's official press statements
Author: Hans-Peter Hoellwirth
Date: 06.2017

Data

Web scrapping official press statements published at https://www.ecb.europa.eu/press/pressconf/2017/html/index.en.html for the years 1998-2017.

Text Analysis

Latent Dirichlet Allocation (LDA) and Structural Topic Model (STM) for 3 and 10 topics

Main Result(s)

3 topics: Topics are mainly associated to presidencies
10 topics: Most topics are associated to major events and policies in ECB's history

Code Instructions

Run in the following order:

  • 01_web_scraping.py: Creates file data/combined.csv (optional if already existing)
  • 02_pre_processing.py: Requires file data/combined.csv to exist
  • 03_lda.py: Takes output of previous step (text_process) as input
  • 04_stm.R: Requires file data/combined.csv to exist. Independently executable from steps 2 and 3

Note: Before execution, update the working directory in each code file.