2019 EMNLP EMNLP 2019

A Time Series Analysis of Emotional Loading in Central Bank Statements

Abstract

AbstractWe examine the affective content of central bank press statements using emotion analysis. Our focus is on two major international players, the European Central Bank (ECB) and the US Federal Reserve Bank (Fed), covering a time span from 1998 through 2019. We reveal characteristic patterns in the emotional dimensions of valence, arousal, and dominance and find—despite the commonly established attitude that emotional wording in central bank communication should be avoided—a correlation between the state of the economy and particularly the dominance dimension in the press releases under scrutiny and, overall, an impact of the president in office.

🌉 Interdisciplinary Bridge — Data Science & Analytics and Natural Language Processing
🧭 Keyword Pioneer — central bank
🐣 Hot Topic Early Bird — time series analysis
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio