Environmental, social, and governance (ESG) criteria are increasingly central to corporate reporting. This study applies natural language processing (NLP) techniques, specifically a RoBERTa-based few-shot model, to conduct aspect-based sentiment analysis (ABSA). Our analysis targets ESG-related...

Innovation is central to models in economics, strategy, management, and finance, yet it remains difficult to measure due to its intangible and knowledge-based na ture. Recent advancements in Natural Language Processing offer new methods to analyze textual artifacts, providing empirical insights...

This article applies simple methods from computational linguistics to analyze unstructured corporate texts for economic surveillance. We apply text-as-data approaches to earnings conference call transcripts, patent texts, and job postings to uncover unique insights into how markets and firms...

Generative Künstliche Intelligenz beschreibt eine Klasse von KI-Systemen, die in der Lage sind, aus großen Datenmengen zu lernen und auf dieser Grundlage neue, bisher nicht gesehene Inhalte zu generieren, wie beispielsweise Texte, Bilder, Musik oder Videos. Dabei wird die...

We develop a novel method for the identification of monetary policy shocks. By applying natural language processing techniques to documents that Federal Reserve staff prepare in advance of policy decisions, we capture the Fed's information set. Using machine learning techniques, we then predict...

As distorted maps may mislead, Natural Language Processing (NLP) models may misrepresent. How do we know which NLP model to trust? We provide comprehensive guidance for selecting and applying NLP representations of patent text. We develop novel validation tasks to evaluate several leading NLP...