This paper assess how priorities of the IMF's membership have evolved over the past two decades, by using text mining techniques on a unique dataset combining IMFC communiques and constituency statements. Our results reveal significant variation in priorities across time and constituencies....

Background: Researchers in logistics and supply chain management apply a multitude of methods. So far, however, the potential of textual data science has not been fully exploited to automatically analyze large chunks of textual data and to extract relevant insights. Methods: In this paper, we...

There is growing awareness within the economics profession of the important role narratives play in the economy. Even though empirical approaches that try to quantify economic narratives are getting increasingly popular, there is no theory or even a universally accepted definition of economic...

Das Coronavirus hat viele alte Gesetzmäßigkeiten in Frage gestellt. Das gilt auch für die Vermessung ökonomischer Aktivitäten. Verfahren aus der Hochzeit der Industrialisierung werden dem strukturellen Wandel zunächst zu einer Dienstleistungsgesellschaft, später zu einer Digitalwirtschaft...

Using the dictionary-based approach to measure the sentiment of finance-related texts is primarily focused on English-speaking content. This is due to the need for domain-specific dictionaries and the primary availability of those in English. Through the contribution of Bannier et al. (2019b),...

Unprecedented opportunities have been brought by advancements in machine learning in the prediction of the economic success of movies. The analysis of movie title keywords is one promising but rarely investigated direction of study. To address this gap, we performed a text mining and exploratory...