Econometrics meet sentiment: an overview of methodology and applications

Andres Algaba; David Ardia; Keven Bluteau; Samuel Borms; Kris Boudt

doi:10.1111/joes.12370

Econometrics meet sentiment: an overview of methodology and applications

Andres Algaba
, David Ardia
, Keven Bluteau
, Samuel Borms^*
, Kris Boudt

^*Corresponding author for this work

Econometrics and Data Science

Research output: Contribution to Journal › Article › Academic › peer-review

Abstract

The advent of massive amounts of textual, audio, and visual data has spurred the development of econometric methodology to transform qualitative sentiment data into quantitative sentiment variables, and to use those variables in an econometric analysis of the relationships between sentiment and other variables. We survey this emerging research field and refer to it as sentometrics, which is a portmanteau of sentiment and econometrics. We provide a synthesis of the relevant methodological approaches, illustrate with empirical results, and discuss useful software.

Original language	English
Pages (from-to)	512-547
Number of pages	36
Journal	Journal of Economic Surveys
Volume	34
Issue number	3
Early online date	21 May 2020
DOIs	https://doi.org/10.1111/joes.12370
Publication status	Published - Jul 2020

Funding

We thank the Associate Editors (Les Oxley and Stelios Bekiros) and two anonymous Referees, seminar participants at Ca' Foscari University of Venice, the European Commission JRC Ispra ?Big Data and Forecasting Workshop? (Ispra, 2019), Ghent University, HEC Montral, the International Conference on Computational and Financial Econometrics (London, 2019), Skema Business School, University of Delaware, and Vrije Universiteit Brussel for their useful comments. We are also grateful to Francesco Audrino, Leopoldo Catania, Maxime De Bruyn, William Doehler, Nitish Sinha, and Leif Anders Thorsrud for stimulating discussions and feedback. This project benefited from financial support from Innoviris (https://innoviris.brussels), IVADO (https://ivado.ca), swissuniversities (https://www.swissuniversities.ch), and the Swiss National Science Foundation (http://www.snf.ch, grants #179281 and #191730).

Funders	Funder number
Nitish Sinha
SKEMA Business School
William Doehler
University of Delaware
European Commission
Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung	179281, 191730
Universiteit Gent
Higher Education Commission, Pakistan
Innoviris
Università Ca' Foscari di Venezia
Institut de Valorisation des Données

Keywords

Qualitative data
Sentiment analysis
Sentometrics
Survey
Textual analysis

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Econometrics meet sentiment: an overview of methodology and applications

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