Sentiment analysis from unstructured text has witnessed a boom in interest in recent years, due to the sheer volume of online reviews and news corpora available in digital form. An accurate method for predicting sentiments could enable us, for instance, to extract opinions from the Internet and...

Social media data presents challenges for forecasters since one must convert text into data and deal with issues related to these measures being collected at different frequencies and volumes than traditional financial data. In this paper, we use a deep learning algorithm to measure sentiment...

Social media data presents challenges for forecasters since one must convert text into data and deal with issues related to these measures being collected at different frequencies and volumes than traditional financial data. In this paper, we use a deep learning algorithm to measure sentiment...

Changes in the sentiment of Dutch public social media messages were compared with changes in monthly consumer confidence over a period of three-and-a-half years, revealing that both were highly correlated (up to r = 0.9) and that both series cointegrated. This phenomenon is predominantly...

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...

This paper studies the effect of digitalization on consumption inequality. We assemble a novel dataset of digital technology in the consumption basket of US households and establish a new stylized fact: High-income households have a higher consumption share of digital products than low-income...