The current research chronicles the unfolding of the early psychological impacts of coronavirus disease 2019 (COVID-19) by analyzing Reddit language from 18 U.S. cities (200,000+ people) and large-scale survey data (11,000+ people). Large psychological shifts were found reflecting three distinct phases. When COVID-19 warnings first emerged ("warning phase"), people's attentional focus switched to the impending threat. Anxiety levels surged, and positive emotion and anger dropped. In parallel, people's thinking became more intuitive rather than analytic. When lockdowns began ("isolation phase"), analytic thinking dropped further. People became sadder, and their thinking reflected attempts to process the uncertainty. Familial ties strengthened, but ties to broader social groups weakened. Six weeks after COVID-19's onset ("normalization phase"), people's psychological states stabilized but remained elevated. Most psychological shifts were stronger when the threat of COVID-19 was greater. The magnitude of the observed shifts dwarfed responses to other events that occurred in the previous decade.

Due to the explosion of new sources of human language data and the rapid progression of computational methods for extracting meaning from natural language, language analysis is a promising, though complicated, category of psychological research. In this chapter, we give a modern perspective on language analysis as it applies to psychology, uniting historical context, the diverse range of domains studied in psychology via language, and the methodological rigor of natural language processing (NLP) and machine learning. Top–down methods (e.g., dictionary approaches, text annotation) are presented alongside bottom–up methods (e.g., topic modeling, word embedding, language modeling) in order to give the reader a comprehensive grounding in the tools available and the recommended practices involved in applying them. We conclude with a view of the future of language analysis, specifically the ways in which psychology and NLP will continue to co-develop.

The emotion disgust motivates costly behavioral strategies that mitigate against potentially larger costs associated with pathogens, sexual behavior, and moral transgressions. Because disgust thereby regulates exposure to harm, it is by definition a mechanism for calibrating decision making under risk. Understanding this illuminates two features of the demographic distribution of this emotion. First, this approach predicts and explains sex differences in disgust. Greater female disgust propensity is often reported and discussed in the literature, but, to date, conclusions have been based on informal comparisons across a small number of studies, while existing functionalist explanations are at best incomplete. We report the results of an extensive meta-analysis documenting this sex difference, arguing that key features of this pattern are best explained as one manifestation of a broad principle of the evolutionary biology of risk-taking: for a given potential benefit, males in an effectively polygynous mating system accept the risk of harm more willingly than do females. Second, viewing disgust as a mechanism for decision making under risk likewise predicts that individual differences in disgust propensity should correlate with individual differences in various forms of risky behavior, because situational and dispositional factors that influence valuation of opportunity and hazard are often correlated across multiple decision contexts. In two large-sample online studies, we find consistent associations between disgust and risk avoidance. We conclude that disgust and related emotions can be usefully examined through the theoretical lens of decision making under risk in light of human evolution. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

As ordinary citizens increasingly moderate online forums, blogs, and their own social media feeds, a new type of censoring has emerged wherein people selectively remove opposing political viewpoints from online contexts. In three studies of behavior on putative online forums, supporters of a political cause (e.g., abortion or gun rights) preferentially censored comments that opposed their cause. The tendency to selectively censor cause-incongruent online content was amplified among people whose cause-related beliefs were deeply rooted in or "fused with" their identities. Moreover, six additional identity-related measures also amplified the selective censoring effect. Finally, selective censoring emerged even when opposing comments were inoffensive and courteous. We suggest that because online censorship enacted by moderators can skew online content consumed by millions of users, it can systematically disrupt democratic dialogue and subvert social harmony.

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