The asymmetric impact of Twitter Sentiment and emotions: Impulse response analysis on European tourism firms using micro-data

Document Type

Article

Source of Publication

Tourism Management

Publication Date

10-1-2024

Abstract

This paper examines the characteristics that drive conflicting outcomes on the impact of Twitter data on firm returns using financial micro data. Using 314 European tourism firms as a case study and a sample of 63 million Tweets, we build sentiment and emotion (anger, fear, joy) data series and use them to compute impulse response functions for firm returns. Our results indicate that firm size and popularity are the most important firm features that explain the asymmetric impact of Twitter sentiment and of the anger emotion, while debt explains the variations in the impact of the fear emotion. We also find that the impact of the joy emotion is more evident before the COVID-19 pandemic and more muted after the outbreak. Our findings reconcile varied research on Twitter's impact on tourism industry returns and provide insights to practitioners on using Twitter to gauge online users' collective knowledge of real outcomes.

ISSN

0261-5177

Publisher

Elsevier BV

Volume

104

Disciplines

Business

Keywords

Local projections, Micro-data, Sentiment analysis, Tourism share returns, Twitter

Scopus ID

85188184824

Indexed in Scopus

yes

Open Access

no

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