We apply moral foundations theory (MFT) to explore how the public conceptualizes the first eight months of the conflict between Ukraine and the Russian Federation (Russia). Our analysis includes over 1.1 million English tweets related to the conflict over the first 36 weeks. We used linguistic inquiry word count (LIWC) and a moral foundations dictionary to identify tweets’ moral components (care, fairness, loyalty, authority, and sanctity) from the United States, pre- and post-Cold War NATO countries, Ukraine, and Russia. Following an initial spike at the beginning of the conflict, tweet volume declined and stabilized by week 10. The level of moral content varied significantly across the five regions and the five moral components. Tweets from the different regions included significantly different moral foundations to conceptualize the conflict. Across all regions, tweets were dominated by loyalty content, while fairness content was infrequent. Moral content over time was relatively stable, and variations were linked to reported conflict events.

This preregistered study replicates and extends studies concerning emotional response to wartime rally speeches and applies it to U.S. President Donald Trump’s first national address regarding the COVID-19 pandemic on March 11, 2020. We experimentally test the effect of a micro-expression (ME) by Trump associated with appraised threat on change in participant self-reported distress, sadness, anger, affinity, and reassurance while controlling for followership. We find that polarization is perpetuated in emotional response to the address which focused on portraying the COVID-19 threat as being of Chinese provenance. We also find a significant, albeit slight, effect by Trump’s ME on self-reported sadness, suggesting that this facial behavior served did not diminish his speech, instead serving as a form of nonverbal punctuation. Further exploration of participant response using the Linguistic Inventory and Word Count software reinforces and extends these findings.