In the attention economy of social media, moralized commentary spreads widely,15 attracts engagement, and is amplified by algorithms. Yet little is known about temporal trends inmoralization—specifically, whether moralization has steadily increased, a trend that coulddeepen divisions and fuel polarization. Using natural language processing, we analyzed 9.7MTwitter/X posts and found a sharp rise in moralized language from 2013-2021. This trendgeneralized to Reddit (2.1B comments) and outpaced changes in two traditional media corpora20 (4.9M and 115K texts). Two processes explained this moralizing shift: (1) within-user increasesin moral language over time, and (2) selection effects, whereby highly moralized users becamemore active while less moralized users disengaged. These findings reveal how user dynamics cancreate highly moralized discourse; understanding this process is crucial for fostering healthierdigital ecosystems.
Puryear et al. (Tue,) studied this question.