Media bias and the intolerance of media outlets and citizens to deal with opposing points of
view pose a threat to the proper functioning of democratic processes. In this respect, we …

The creation, dissemination, and consumption of disinformation and fabricated content on
social media is a growing concern, especially with the ease of access to such sources, and …

Large language models (LLMs) are capable of successfully performing many language
processing tasks zero-shot (without training data). If zero-shot LLMs can also reliably classify …

Recent advancements in artificial intelligence, particularly with the emergence of large
language models (LLMs), have sparked a rethinking of artificial general intelligence …

An ever-increasing share of human interaction, communication, and culture is recorded as
digital text. We provide an introduction to the use of text as an input to economic research …

Over the past few years, neural networks have re-emerged as powerful machine-learning
models, yielding state-of-the-art results in fields such as image recognition and speech …

Convolutional Neural Networks (CNNs) have recently achieved remarkably strong
performance on the practically important task of sentence classification (kim 2014 …

Many existing deep learning models for natural language processing tasks focus on
learning the compositionality of their inputs, which requires many expensive computations …

This review presents machine learning (ML) approaches from an applied economist's
perspective. We first introduce the key ML methods drawing connections to econometric …

Automatic political orientation prediction from social media posts has to date proven
successful only in distinguishing between publicly declared liberals and conservatives in the …