This article provides an overview of the methods used for algorithmic text analysis in
economics, with a focus on three key contributions. First, we introduce methods for …

The advent of massive amounts of textual, audio, and visual data has spurred the
development of econometric methodology to transform qualitative sentiment data into …

In this study, we attempt to revisit how dependent the US stock market returns are on climate
change related risks (CCRR). In this regard, we use a spillover and connectedness network …

We formulate a dynamic no-arbitrage asset pricing model for equities and corporate bonds,
featuring time variation in both risk aversion and economic uncertainty. The joint dynamics …

This study empirically tests the role of news discourse in forecasting tourist arrivals by
examining Hong Kong. It employs structural topic modeling to identify key topics and their …

This work describes a chronological (2000–2019) analysis of sentiment and emotion in 23
million headlines from 47 news media outlets popular in the United States. We use …

The pandemic catalyzed an enduring shift to remote work. To measure and characterize this
shift, we examine more than 250 million job vacancy postings across five English-speaking …

We develop a classification methodology for the context and content of news articles to
predict risk and return in stock markets in 51 developed and emerging economies. A …

Humans in hospitality areas are being replaced by robot concierges, delivery robots,
chatbots, and information assistants through a variety of devices, for example, mobile apps …

This paper studies the use of emotion and reason in political discourse. Adopting
computational-linguistics techniques to construct a validated text-based scale, we measure …