Computing Consumer Sentiment in Germany via Social Media Data - Deniz Dilan Karaman Örsal; Silke Sturm (University of Hamburg, Chair of International Economics, 2021)
Survey-based consumer confidence indicators are mostly reported with a delay and are a result of time consuming and expensive consumer surveys. In this study, to measure the current consumer confidence in Germany, we develop an approach, in which we compute the consumer sentiment using public Tweets from Germany. To achieve this goal we develop a new sentiment score. To measure the consumer sentiment, we use text-mining tools and public Tweets from May 2019 to August 2020. Our findings indicate that there is a high correlation between the consumer confidence indicator based on survey data, and the consumer sentiment that we compute using data from Twitter platform. With our approach, we are even able to forecast the change in next month's consumer confidence.
Keywords: 330; consumer sentiment; consumer confidence; Twitter; sentiment analysis