Social scientists have become increasingly interested in how narratives -- the stories in fiction, politics, and life -- shape beliefs, behavior, and government policies. This paper provides an unsupervised method to quantify latent narrative structures in text documents. Our pipeline identifies...

Network models are one of the methods used by linguists, psychologists and cognitive scientists to represent the semantic organization structure. In order to understand the semantic organization development of Chinese preschool children in their actual use of language, this paper constructs...

This paper studies economic determinants of semantic similarity in executive compensation disclosures and its implications for compensation peer selection. We employ a novel measure based on a natural language processing algorithm with machine learning---document embeddings---to capture nuanced...

Studies on health insurance coverage often rely on measures self-reported by respondents, but the accuracy of such measures has not been thoroughly validated. This paper is the first to use linked Australian National Health Survey and administrative population tax data to explore the accuracy of...

The landscape of ICOs and its underlying Blockchain technology needs more clarity, given that several overlapping and opposing views exist from governmental institutions, institutional investors, economists, and academia. Those positions stem from confusion, bias, and vested interest. Having...

We describe a context-sensitive model of choice, in which the selection process is shaped not only by the attractiveness of items but also by their semantics (‘salience’). Items are ranked according to a binary relation of salience, and a linear order is associated to each item. The...