• Media type: E-Book
  • Title: Computing consumer sentiment in Germany via social media data
  • Contributor: Karaman Örsal, Deniz Dilan [VerfasserIn]; Sturm, Silke [VerfasserIn]
  • imprint: Hamburg: University of Hamburg, Chair of International Economics, [2021]
  • Published in: Hamburg discussion paper in international economics ; 7
  • Issue: Preliminary draft
  • Extent: 1 Online-Ressource (circa 13 Seiten); Illustrationen
  • Language: English
  • Identifier:
  • Keywords: consumer sentiment ; consumer confidence ; Twitter ; sentiment analysis ; Graue Literatur
  • Origination:
  • Footnote:
  • Description: Survey-based consumer confidence indicators are mostly reported with adelay and are a result of time consuming and expensive consumer surveys.In this study, to measure the current consumer confidence in Germany, wedevelop an approach, in which we compute the consumer sentiment usingpublicTweetsfrom Germany. To achieve this goal we develop a new sentimentscore. To measure the consumer sentiment, we use text-mining tools and publicTweetsfrom May 2019 to August 2020. Our findings indicate that there is ahigh correlation between the consumer confidence indicator based on surveydata, and the consumer sentiment that we compute using data from Twitterplatform. With our approach, we are even able to forecast the change in nextmonth's consumer confidence.
  • Access State: Open Access