When danger strikes: A linguistic tool for tracking America's collective response to threats

Enhancing local governments' environmental attention through open government data: evidence from China

Environmental conservation has ascended to a prominent position on the global agenda, and China, recognizing the urgent need for environmental protection, has implemented nationwide measures. However, varying levels of environmental attentiveness among local governments have resulted in uneven implementation of these national directives across regions. Therefore, it is crucial to investigate the factors that drive local governments' environmental attention. Our study explores the impact of open government data (OGD) on local governments' environmental attention. Utilizing city-level data from 2010 to 2020, we employ a staggered difference-in-differences (DID) model for empirical analysis. The results reveal that OGD significantly and positively influences local governments' environmental attention. This influence is partly attributed to OGD's role in promoting government digitization, mitigating fiscal pressures, and increasing energy demand. Further analysis, including heterogeneity assessments, demonstrates that OGD has a more pronounced positive effect on environmental attention in cities with higher online political participation activity and a larger internet user base. Such empirical insights underscore the imperative for an integrative policy framework that accentuates the refinement of OGD platform in tandem with strategic enhancements in political participatory mechanisms and digital infrastructure investments, thereby fostering robust local environmental stewardship paradigms.

Norm Dynamics: Interdisciplinary Perspectives on Social Norm Emergence, Persistence, and Change

Social norms are the glue that holds society together, yet our knowledge of them remains heavily intellectually siloed. This article provides an interdisciplinary review of the emerging field of norm dynamics by integrating research across the social sciences through a cultural-evolutionary lens. After reviewing key distinctions in theory and method, we discuss research on norm psychology-the neural and cognitive underpinnings of social norm learning and acquisition. We then overview how norms emerge and spread through intergenerational transmission, social networks, and group-level ecological and historical factors. Next, we discuss multilevel factors that lead norms to persist, change, or erode over time. We also consider cultural mismatches that can arise when a changing environment leads once-beneficial norms to become maladaptive. Finally, we discuss potential future research directions and the implications of norm dynamics for theory and policy.

Evaluating the long-term portrayal of antibiotic resistance in major U.S. newspapers

BACKGROUND

Popular media play a critical role in informing the public about antibiotic resistance, which has remained a health concern for over seven decades. Media attention increases the notoriety of antibiotic resistance and shapes the public's perception of its severity, causes, and solutions. Therefore, it is critical the media accurately portray scientific knowledge that may shape personal and policy responses to antibiotic resistance.

METHODS

We analyzed articles from two major U.S. newspapers, The New York Times and Los Angeles Times, from 1940 to 2019 to assess trends in sentiment and lexicon surrounding antibiotic and antimicrobial resistance.

RESULTS

We observed a gradual increase in the number of relevant articles about resistance, although far fewer than other topics with comparable mortality rates. We found a consistently threatening portrayal of antibiotic resistance as a crisis, reflected in the usage of terms such as "superbug" to refer to some pathogens. Governmental agencies responsible for determining antibiotic usage policies were infrequently mentioned in articles. Blame for resistance was almost exclusively attributed to inappropriate antibiotic use, mainly in animals, rather than appropriate uses of antibiotics.

CONCLUSIONS

Collectively, our results provide insights into how popular media can more accurately inform the public about antibiotic resistance. Potential changes include increasing news coverage, avoiding fear-mongering, and adequately conveying the multiple uses of antibiotics that can potentiate resistance.

Historical Psychology

A growing body of evidence suggests that many aspects of psychology have evolved culturally over historical time. A combination of approaches, including experimental data collected over the past 75 years, cross-cultural comparisons, and studies of immigrants, points to systematic changes in psychological domains as diverse as conformity, attention, emotion, morality, and olfaction. However, these approaches can go back in time only for a few decades and typically fail to provide continuous measures of cultural change, posing a challenge for testing deeper historical psychological processes. To tackle this challenge most directly, computational methods emerging from natural language processing can be adapted to extract psychological information from large-scale historical corpora. Here, we first review the benefits of psychology as a historical science and then present three useful classes of text-analytic techniques for historical psychological inquiry: dictionary-based methods, distributed-representational methods, and human-annotation-based methods. These represent an excellent suite of methodologies that can be used to examine the record of “dead minds.” Finally, we discuss the importance of going beyond English-centric text analysis in historical psychology to foster a more generalizable and inclusive science of human behavior. We propose that historical psychology should incorporate and further develop a variety of text-analytic approaches to reliably quantify the historical processes that gave rise to contemporary social, political, and psychological phenomena.

Dehumanization and mass violence: A study of mental state language in Nazi propaganda (1927–1945)

Dehumanization is frequently cited as a precursor to mass violence, but quantitative support for this notion is scarce. The present work provides such support by examining the dehumanization of Jews in Nazi propaganda. Our linguistic analysis suggests that Jews were progressively denied the capacity for fundamentally human mental experiences leading up to the Holocaust. Given that the recognition of another’s mental experience promotes moral concern, these results are consistent with the theory that dehumanization facilitates violence by disengaging moral concern. However, after the onset of the Holocaust, our results suggest that Jews were attributed a greater capacity for agentic mental states. We speculate this may reflect a process of demonization in which Nazi propagandists portrayed the Jews as highly capable of planning and intentionality while nonetheless possessing a subhuman moral character. These suggestive results paint a nuanced portrait of the temporal dynamics of dehumanization during the Holocaust and provide impetus for further empirical scrutiny of dehumanization in ecologically valid contexts.

Three families of automated text analysis

Since the beginning of this millennium, data in the form of human-generated text in a machine-readable format has become increasingly available to social scientists, presenting a unique window into social life. However, harnessing vast quantities of this highly unstructured data in a systematic way presents a unique combination of analytical and methodological challenges. Luckily, our understanding of how to overcome these challenges has also developed greatly over this same period. In this article, I present a novel typology of the methods social scientists have used to analyze text data at scale in the interest of testing and developing social theory. I describe three "families" of methods: analyses of (1) term frequency, (2) document structure, and (3) semantic similarity. For each family of methods, I discuss their logical and statistical foundations, analytical strengths and weaknesses, as well as prominent variants and applications.