The impact of German-speaking online media on tourist arrivals in popular tourist destinations for Europeans

Kejo Starosta, Sonia Budz and Michael Krutwig

Applied Economics, 2019, vol. 51, issue 14, 1558-1573

Abstract: This empirical study analyzes the relationship between the sentiments in online media with regard to travel destinations and corresponding tourist arrivals. We expect the media reports on political and economic instability and turmoil to enhance tourist arrival nowcasts and forecasts, as they can probably complement them with information on disruptions and shocks. Therefore, we believe this research will help to build better models for tourism demand nowcasting and forecasting. We use the sentiment in the German-speaking online media because the German-speaking region is the most populated in Europe and has the largest group of travelers visiting destinations in and around Europe.An artificial neural network is used to analyze the mood of the media. The software classifies news items regarding potential tourist destinations with either positive or negative labels. The number of positive and negative news items is used to build sentiment indices for popular tourist destinations for Europeans.Our results show strong correlations between the mood concerning tourist destinations and tourist arrivals in these countries. Indeed, disruptions and shocks prevalent in the news are reflected in similar ratios in both tourist arrivals and sentiment indices. These results can be used as a new explanatory variable for tourism demand modelling.

Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
http://hdl.handle.net/10.1080/00036846.2018.1527463 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:applec:v:51:y:2019:i:14:p:1558-1573

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAEC20

DOI: 10.1080/00036846.2018.1527463

Access Statistics for this article

Applied Economics is currently edited by Anita Phillips

More articles in Applied Economics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().