This study examines the relationship between vaccine mandates and public sentiment toward vaccines and health officials on Twitter. I analyzed 6.6 million vaccine-related tweets from July 2021 to February 2022 in the United States. Leveraging a large language model, BERT, I identified tweets discussing vaccine mandates even when lacking explicit keywords. Compared to non-mandate tweets, those mentioning mandates exhibit greater negativity, anger, and freedom-related language. Furthermore, increased state-level discussion of mandates correlates with rising levels of negativity and anger toward both vaccines and public health officials. Finally, greater disparity in vaccination progress across counties within a state is associated with increased anger in tweets directed toward both.

Climate change mitigation has been one of the world’s most salient issues for the past three decades. However, global policy attention has been partially diverted to address the COVID-19 pandemic for the past two years. Here, we explore the impact of the pandemic on the frequency and content of climate change discussions on Twitter for the period of 2019 – 2021. Consistent with the “finite pool of worry” hypothesis, both at the annual level and on a daily basis, a larger number of COVID-19 cases and deaths is associated with a smaller number of “climate change” tweets. Climate change discussion on Twitter decreased despite (a) a larger Twitter daily active usage in 2020 and 2021, (b) greater coverage of climate change in traditional media in 2021, (c) a larger number of North Atlantic ocean hurricanes, and (d) a larger wildland fires area in the United States in 2020 and 2021. Further evidence supporting the finite pool of worry is the significant relationship between daily COVID-19 cases/deaths on the one hand and the public sentiment and emotional content of “climate change” tweets on the other. In particular, increasing COVID-19 numbers decrease negative sentiment in climate change tweets and the emotions related to worry and anxiety, such as fear and anger.

During the COVID-19 pandemic, online hostility toward U.S. public health officials surged. This study analyzed English-language tweets (X) referencing the Centers for Disease Control and Prevention (CDC) and Dr. Anthony Fauci between October 2019 and December 2022. Political DEBATE (DeBERTa Algorithm for Textual Entailment), a natural language inference classifier fine-tuned to detect hate speech, was used to identify attacks and advocacy of violence. Aggressive content increased following the national emergency declaration. Approximately 30% of tweets attacked public health officials, and 1% advocated violence. Anger and disgust were expressed in 80% of attacking tweets, while non-attacking tweets displayed a more diverse range of emotions. Using zero-inflated negative binomial models, I found that tweets attacking the CDC and those advocating violence against Fauci were more popular and widely shared, while tweets attacking Fauci were more viral but received fewer likes. These findings suggest that online aggression toward public health officials was widespread during the pandemic, with important implications for public health institutions. While policies should remain open to debate and critique, personal attacks risk deterring professionals from public service and weakening public health institutions.

Whether the COVID-19 pandemic has diverted public attention away from the issue of climate change is a topic that has ignited scholarly debate in recent years. Two competing theories have surfaced: the ‘finite pool of worry’, which asserts that concerns over the pandemic have overshadowed those for climate change, and the ‘finite pool of attention’, which argues that although attention to climate change has waned, worry has remained steady or even intensified, in line with affect generalization theory. Survey research seems to support the latter hypothesis more strongly. In our study, we investigate this theoretical discourse and revisit these conclusions by conducting an emotional content analysis on a novel dataset of nearly 24 million Twitter posts related to climate change, spanning from 2018 to 2022. Employing three distinct lexicons—LIWC, NRC Lex, and VADER—we find that climate change tweets exhibit a decline in expressions of fear, anxiety, and other negative emotions concurrent with COVID-19 surges. Our daily-level analysis incorporates controls such as media coverage of climate change, the occurrence of climate-related disasters like hurricanes and wildfires, and the impact of major political events, including the 2020 presidential election. The association between COVID-19 severity and climate change concern was most marked in 2020, diminishing progressively in 2021 and 2022.

Economic sanctions have become a major instrument of international politics. However, the effectiveness of economic sanctions depends on both public opinions in the targeted country and the country that imposes sanctions. We explored whether certain emotions—anxiety and anger—were associated with specific attitudes towards the sanctions against Russia in 2022. Existing literature in psychology and political science has demonstrated that anxiety and anger provoke different risk perceptions and risk attitudes and, in turn, change political attitudes, such as support for a war. Therefore, we proposed that the fear of the consequences of the economic sanctions, such as inflation and shortage, resulted in negative attitudes toward the sanctions among Americans and negative attitudes toward the invasion among Russians. In contrast, the American citizens angered by the invasion were more likely to support the sanctions, and the Russian citizens angered by the sanctions were more likely to support the invasion. Using the data from Twitter and VKontakte, we applied emotion analysis and automated text classification to measure the emotions and attitudes toward the sanctions in Americans and Russians. In the preliminary analysis, we found that the pro-sanction tweets were angrier than the anti-sanction tweets. In contrast, the anti-sanction tweets were more anxious than the pro-sanction tweets.

Building on the deservingness heuristic–evaluating recipients based on need and effort–from evolutionary psychology, this study integrates it with the conditional altruism model from political science and economics to understand individual similarities and differences in redistributive preferences. We found that, when a recipient’s effort is known, most participants’ choices could be explained by the need and effort effect derived from the model. Furthermore, participants mainly fall into three categories: highly responsive to effort, less responsive, and self-interested. These categories reflect how much weight individuals place on recipient effort in the utility function. However, when effort information is indirect and partial, income becomes the primary factor, even if effort can be partially inferred.

Many societal challenges, such as climate change and epidemics, require collective mitigation efforts. Whether coercive policies should be used to mandate cooperative behaviors remains a longstanding debate. While research empirically shows that individuals value their own autonomy, few studies examine whether they also have a procedural preference for others’ freedom. This study investigates whether individuals discount coercive measures. To test this, I designed an incentivized experiment in which players exerted real labor effort to cooperate in a prisoner’s dilemma. One player could choose to implement either a voluntary rule—where they played with a voluntary cooperator—or a mandatory rule—where both players were required to cooperate. Both rules ensured the same outcome distribution. If individuals intrinsically valued others’ freedom beyond instrumental values, they would choose voluntary cooperation. The results do not indicate a general aversion to coercing others , even when both rules produce the same outcome. However, participants who selected voluntary cooperation and those who opted for mandatory cooperation differed in their views on the government’s role when freedom and social welfare are at odds, their trust in government, and their support for COVID-19 mask mandates. These findings suggest heterogeneity in preferences for others’ freedom.

As income differences become more disparate, researchers need to study behavior and preferences under extreme inequality. We use an incentivized experiment to test for differences in redistributive behavior on two distinct samples: one online sample (N = 797) and one laboratory sample (N = 488). In our experiment, players are given an initial distribution of tokens and can propose redistribution. We manipulate the level of inequality experienced as well as the source of inequality. For some of our players, the distribution of tokens is performance-based (merit). For the rest, tokens are randomly-generated (luck). We find that people care about merit even at extreme inequality—those who experience merit-based inequality prefer equality less than those who experience luck-based inequality. Most players that experience any inequality redistribute to create equal outcomes, but those exposed to extreme inequality want more equality overall. In other words, people who experience extreme inequality, even when merit-based, still want more equality than those who experience non-extreme types of inequality.

Approximately one-third of global greenhouse gas emissions are attributed to food systems, and adopting a plant-rich diet is an effective way to mitigate climate change by individuals. Nevertheless, the entire population will benefit from this individual’s efforts to adopt a plant-rich diet, resulting in an incentive for individuals to free-ride. Despite the fact that adopting a plant-rich diet is effective in reducing greenhouse gas emissions, it remains unpopular with Americans. In the current proposal, we design a vignette experiment to examine how others’ behavior and perceptions of reciprocity influence Americans’ willingness to adopt plant-rich diets and support policies that promote plant-rich diets, such as federal diet guidelines, meat taxes, the proposed PLANT Act, and school meals. Our pilot study found that the dynamic trend treatment and the reciprocity cue influenced several policy attitudes promoting a plant-rich diet.

While Americans increasingly recognize differences between the major parties, it remains unclear whether they agree on each party’s ideological image. Using cumulative ANES data from 1972 to 2020, this study finds that partisan bias in perceptions of party ideology was moderate before 2008 but became dominant thereafter. First, voter agreement on party ideology peaked in 2000, declined sharply by 2008, and rose again in subsequent years. Second, consistent with research on asymmetric ideological clarity, partisans in both camps agreed more on the Republican Party’s ideology than on the Democratic Party’s from 1978 to 2004. Since 2008, however, partisans have shown greater agreement on the opposing party’s ideology than on their own. Third, although the partisan gap in perceived extremity has persisted, it remained moderate before 2000 but has grown steadily since 2008—doubling by 2020. These findings suggest that partisan bias has intensified, increasingly outweighing shared perceptions across party lines.

Over the past decade, populism has surged globally, shaping public attitudes toward scientists and public health officials. Rooted in anti-elitism and a Manichean worldview that divides society into “the good people” and “the corrupt elites,” populists often target individuals while undermining the institutions that hold them accountable. Using data from the 2020 American National Election Studies, this study finds that Americans with stronger populist attitudes expressed more negative feelings toward both the Centers for Disease Control and Prevention (CDC) and Dr. Anthony Fauci, even after controlling for anti-intellectualism, partisanship, ideology, education, sex, race, and income. Populist attitudes emerged as the strongest predictor of negative feelings toward both the CDC and Dr. Fauci, surpassing or equaling the effects of party identification and ideological self-placement. Consistent with the literature on populism’s Manichean worldview, populist respondents rated Dr. Fauci more negatively than the CDC, while individuals with higher levels of education viewed the CDC more negatively but showed no significant difference in their views of Dr. Fauci. These findings underscore the connection between populist attitudes and negative perceptions of public health officials, highlighting populists’ focus on individual figures while disregarding institutions.

Building on the deservingness heuristic–evaluating recipients based on need and effort–from evolutionary psychology, this study integrates it with the conditional altruism model from political science and economics to understand individual similarities and differences in redistributive preferences. We found that, when a recipient’s effort is known, most participants’ choices could be explained by the need and effort effect derived from the model. Furthermore, participants mainly fall into three categories: highly responsive to effort, less responsive, and self-interested. These categories reflect how much weight individuals place on recipient effort in the utility function. However, when effort information is indirect and partial, income becomes the primary factor, even if effort can be partially inferred.