In today's vast digital landscape, people are constantly exposed to threatening language, which attracts attention and activates the human brain's fear circuitry. However, to date, we have lacked the tools needed to identify threatening language and track its impact on human groups. To fill this gap, we developed a threat dictionary, a computationally derived linguistic tool that indexes threat levels from mass communication channels. We demonstrate this measure's convergent validity with objective threats in American history, including violent conflicts, natural disasters, and pathogen outbreaks such as the COVID-19 pandemic. Moreover, the dictionary offers predictive insights on US society's shifting cultural norms, political attitudes, and macroeconomic activities. Using data from newspapers that span over 100 years, we found change in threats to be associated with tighter social norms and collectivistic values, stronger approval of sitting US presidents, greater ethnocentrism and conservatism, lower stock prices, and less innovation. The data also showed that threatening language is contagious. In all, the language of threats is a powerful tool that can inform researchers and policy makers on the public's daily exposure to threatening language and make visible interesting societal patterns across American history.
Keywords: collective threats; historical change; language; mass communication; socioecology.
Copyright © 2022 the Author(s). Published by PNAS.