Computing Consumer Sentiment in Germany via Social Media Data
Publikation: Arbeits- oder Diskussionspapiere und Berichte › Arbeits- oder Diskussionspapiere
Authors
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.
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.
Originalsprache | Englisch |
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Erscheinungsort | Hamburg |
Verlag | Universität Hamburg |
Anzahl der Seiten | 12 |
Publikationsstatus | Erschienen - 2021 |
- Volkswirtschaftslehre