The predictive utility of word familiarity for online engagements and funding.

Metacognitive frameworks such as processing fluency often suggest people respond more favorably to simple and common language versus complex and technical language. It is easier for people to process information that is simple and nontechnical compared to complex information, therefore leading to more engagement with targets. In two studies covering 12 field samples (total n = 1,064,533), we establish and replicate this simpler-is-better phenomenon by demonstrating people engage more with nontechnical language when giving their time and attention (e.g., simple online language tends to receive more social engagements). However, people respond to complex language when giving their money (e.g., complex language within charitable giving campaigns and grant abstracts tend to receive more money). This evidence suggests people engage with the heuristic of complex language differently depending on a time or money target. These results underscore language as a lens into social and psychological processes and computational methods to measure text patterns at scale.

Political ideology shapes risk and benefit judgments of COVID-19 vaccines.

In April 2021, the use of the Johnson & Johnson COVID-19 vaccine was paused to investigate whether it had caused serious blood clots to a small number of women (six out of 6.8 million Americans who had been administered that vaccine). As these events were unfolding, we surveyed a sample of Americans (N = 625) to assess their reactions to this news, whether they supported the pausing of the vaccine, and potential psychological factors underlying their decision. In addition, we employed automated text analyses as a supporting method to more classical quantitative measures. Results showed that political ideology influenced the support for the pausing of the vaccine; liberals were more likely to oppose it than conservatives. In addition, the effect of political ideology was mediated by the difference between perceived benefit and risk and the language style used to produce reasons in support (or against) the decision to pause the vaccine. Liberals perceived the benefit of vaccines higher than the risk, used a more analytic language style when stating their reasons, and had a more positive attitude toward the vaccine. We discuss the implications of our findings considering vaccine hesitancy and risk perception during the COVID-19 pandemic.

Can generative AI infer thinking style from language? Evaluating the utility of AI as a psychological text analysis tool.

Generative AI, short for Generative Artificial Intelligence, a class of artificial intelligence systems, is not currently the choice technology for text analysis, but prior work suggests it may have some utility to assess dynamics like emotion. The current work builds upon this empirical foundation to consider how analytic thinking scores from a large language model chatbot, ChatGPT, were linked to analytic thinking scores from dictionary-based tools like Linguistic Inquiry and Word Count (LIWC). Using over 16,000 texts from four samples and tested against three prompts and two large language models (GPT-3.5, GPT-4), the evidence suggests there were small associations between ChatGPT and LIWC analytic thinking scores (meta-analytic effect sizes: .058 < rs < .304; ps < .001). When given the formula to calculate the LIWC analytic thinking index, ChatGPT performed incorrect mathematical operations in 22% of the cases, suggesting basic word and number processing may be unreliable with large language models. Researchers should be cautious when using AI for text analysis.

Social, psychological, and demographic characteristics of dehumanization toward immigrants.

This study extends the current body of work on dehumanization by evaluating the social, psychological, and demographic correlates of blatant disregard for immigrants. Participants (n = 468) were randomly assigned to read a scenario where 1) an immigrant or 2) an immigrant and their child were caught illegally crossing the southern border of the United States, and then rated how long they should spend in jail if convicted. Participants reported that they would sentence the immigrant to more jail time than the immigrant and child. Those who sent immigrants to jail for more time also viewed them as socially distant and less human, described immigration in impersonal terms, and endorsed other social harms unrelated to immigration (e.g., the death penalty for convicted murderers). Crucially, endorsed social harms accounted for explained variance beyond simply holding conservative views. We position these data within the current literature on dehumanization theory and immigration issues.

Virtuous violence from the war room to death row.

How likely is it that someone would approve of using a nuclear weapon to kill millions of enemy civilians in the hope of ending a ground war that threatens thousands of American troops? Ask them how they feel about prosecuting immigrants, banning abortion, supporting the death penalty, and protecting gun rights and you will know. This is the finding from two national surveys of Democrats and Republicans that measured support for punitive regulations and policies across these four seemingly unrelated issues, and a fifth, using nuclear weapons against enemy civilians (in survey 1) or approving of disproportionate killing with conventional weapons (in survey 2). Those who support these various policies that threaten harm to many people tend to believe that the victims are blameworthy and it is ethical to take actions or policies that might harm them. This lends support to the provocative notion of "virtuous violence" put forth by Fiske and Rai [A. P. Fiske, T. S. Rai, Virtuous Violence: Hurting and Killing to Create, Sustain, End, and Honor Social Relationships (2014)], who assert that people commit violence because they believe it is the morally right thing to do. The common thread of punitiveness underlying and connecting these issues needs to be recognized, understood, and confronted by any society that professes to value fundamental human rights and wishes to prevent important decisions from being affected by irrelevant and harmful sociocultural and political biases.

Examining the Examiners: How Medical Death Investigators Describe Suicidal, Homicidal, and Accidental Death.

This study describes differences in medicolegal death investigators' written descriptions for people who died by homicide, suicide, or accident. We evaluated 17 years of death descriptions from a midsized metropolitan midwestern county in the United States to assess how death investigators psychologically respond to different manners of death (N = 10,408 cases). Automated text analyses suggest investigators describe accidental deaths with more immediacy relative to homicides, while they also described suicidal deaths in less emotional terms than homicides as well. These data suggest medicolegal death investigators have different psychological reactions to circumstances and manners of death as indicated by their professional writing. Future research may surface context-specific psychological reactions to vicarious trauma that could inform the design or personalization of workplace-coping interventions.

Psychological trauma and emotional upheaval as revealed in academic writing: The case of COVID-19.

The current paper used a preregistered set of language dimensions to indicate how scientists psychologically managed the COVID-19 pandemic and its effects. Study 1 evaluated over 1.8 million preprints from arXiv.org and assessed how papers written during the COVID-19 pandemic reflected patterns of psychological trauma and emotional upheaval compared to those written before the pandemic. The data suggest papers written during the pandemic contained more affect and more cognitive processing terms to indicate writers working through a crisis than papers written before the pandemic. Study 2 (N = 74,744 published PLoS One papers) observed consistent emotion results, though cognitive processing patterns were inconsistent. Papers written specifically about COVID-19 contained more emotion than those not written about COVID-19. Finally, Study 3 (N = 361,189 published papers) replicated the Study 2 emotion results across more diverse journals and observed papers written during the pandemic contained a greater rate of cognitive processing terms, but a lower rate of analytic thinking, than papers written before the pandemic. These data suggest emotional upheavals are associated with psychological correlates reflected in the language of scientists at scale. Implications for psychology of language research and trauma are discussed.

Ability-related political polarization in the COVID-19 pandemic.

In two large-scale longitudinal datasets (combined N = 5761), we investigated ability-related political polarization in responses to the COVID-19 pandemic. We observed more polarization with greater ability in emotional responses, risk perceptions, and product-purchase intentions across five waves of data collection with a diverse, convenience sample from February 2020 through July 2020 (Study 1, N = 1267). Specifically, more liberal participants had more negative emotional responses and greater risk perceptions of COVID-19 than conservative participants. Compared to conservatives, liberal participants also interpreted quantitative information as indicating higher COVID-19 risk and sought COVID-related news more from liberal than conservative news media. Of key importance, we also compared verbal and numeric cognitive abilities for their independent capacity to predict greater polarization. Although measures of numeric ability, such as objective numeracy, are often used to index ability-related polarization, ideological differences were more pronounced among those higher in verbal ability specifically. Similar results emerged in secondary analysis of risk perceptions in a nationally representative longitudinal dataset (Study 2, N = 4494; emotions and purchase intentions were not included in this dataset). We further confirmed verbal-ability-related polarization findings on non-COVID policy attitudes (i.e., weapons bans and Medicare-for-all) measured cross-sectionally. The present Study 2 documented ability-related polarization emerging over time for the first time (rather than simply measuring polarization in existing beliefs). Both studies demonstrated verbal ability measures as the most robust predictors of ability-related polarization. Together, these results suggest that polarization may be a function of the amount and/or application of verbal knowledge rather than selective application of quantitative reasoning skills.

From complexity to clarity: How AI enhances perceptions of scientists and the public's understanding of science.

This article evaluated the effectiveness of using generative AI to simplify science communication and enhance the public's understanding of science. By comparing lay summaries of journal articles from PNAS, yoked to those generated by AI, this work first assessed linguistic simplicity differences across such summaries and public perceptions in follow-up experiments. Specifically, study 1a analyzed simplicity features of PNAS abstracts (scientific summaries) and significance statements (lay summaries), observing that lay summaries were indeed linguistically simpler, but effect size differences were small. Study 1b used a large language model, GPT-4, to create significance statements based on paper abstracts and this more than doubled the average effect size without fine-tuning. Study 2 experimentally demonstrated that simply-written generative pre-trained transformer (GPT) summaries facilitated more favorable perceptions of scientists (they were perceived as more credible and trustworthy, but less intelligent) than more complexly written human PNAS summaries. Crucially, study 3 experimentally demonstrated that participants comprehended scientific writing better after reading simple GPT summaries compared to complex PNAS summaries. In their own words, participants also summarized scientific papers in a more detailed and concrete manner after reading GPT summaries compared to PNAS summaries of the same article. AI has the potential to engage scientific communities and the public via a simple language heuristic, advocating for its integration into scientific dissemination for a more informed society.

Self and other-perceived deception detection abilities are highly correlated but unassociated with objective detection ability: Examining the detection consensus effect.

Subjective lying rates are often strongly and positively correlated. Called the deception consensus effect, people who lie often tend to believe others lie often, too. The present paper evaluated how this cognitive bias also extends to deception detection. Two studies (Study 1: N = 180 students; Study 2: N = 250 people from the general public) had participants make 10 veracity judgments based on videotaped interviews, and also indicate subjective detection abilities (self and other). Subjective, perceived detection abilities were significantly linked, supporting a detection consensus effect, yet they were unassociated with objective detection accuracy. More overconfident detectors-those whose subjective detection accuracy was greater than their objective detection accuracy-reported telling more white and big lies, cheated more on a behavioral task, and were more ideologically conservative than less overconfident detectors. This evidence supports and extends contextual models of deception (e.g., the COLD model), highlighting possible (a)symmetries in subjective and objective veracity assessments.

Verbal behavior and the future of social science.

Natural language processing (NLP)-previously the domain of a select few language and computer scientists-is undergoing an unprecedented surge in popularity across disciplines. The ubiquity of language data, alongside extremely rapid methodological innovations, has magnetized the field, attracting researchers with the promise of measuring, forecasting, and understanding the most central questions in business, psychology, biology, sociology, the humanities, and beyond. The power of language analysis to reveal insights into human thought, feeling, and behavior has become a core interest emerging from recent technological advances, which are being probed to unearth deeply embedded truths about the human condition. However, NLP research has reached a critical juncture, sitting at the cusp of societal transformation in many aspects of daily life. The details of how NLP research develops over the next 3-5 years will define this transformation. In this emerging, near-infinite space of NLP-driven research, we provide a critical frame of reference for how, when, and why these technologies should evolve in a particularly transdisciplinary manner. Specifically, we discuss (a) the urgency of pairing existing and emerging NLP research with existing scientific knowledge, theory, and principles from the behavioral sciences; (b) the coevolution of NLP technologies; and (c) the practical implications and ethical consequences of expanding language analysis using broader psychosocial theories of the human condition. While our discussion focuses principally on using language as a window in the individual mind, this topic holds substantial implications for other disciplines and lines of inquiry, including the dynamics of social interaction and beyond. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Reading dies in complexity: Online news consumers prefer simple writing.

Over 30,000 field experiments with The Washington Post and Upworthy showed that readers prefer simpler headlines (e.g., more common words and more readable writing) over more complex ones. A follow-up mechanism experiment showed that readers from the general public paid more attention to, and processed more deeply, the simpler headlines compared to the complex headlines. That is, a signal detection study suggested readers were guided by a simpler-writing heuristic, such that they skipped over relatively complex headlines to focus their attention on the simpler headlines. Notably, a sample of professional writers, including journalists, did not show this pattern, suggesting that those writing the news may read it differently from those consuming it. Simplifying writing can help news outlets compete in the competitive online attention economy, and simple language can make news more approachable to online readers.

Numeric social-media posts engage people with climate science.

Innumeracy (lack of math skills) among nonscientists often leads climate scientists and others to avoid communicating numbers due to concerns that the public will not understand them and may disengage. However, people often report preferring to receive numbers; providing them also can improve decisions. Here, we demonstrated that the presence vs. absence of at least one Arabic integer in climate-related social-media posts increased sharing up to 31.7% but, counter to hypothesis, decreased liking of messages 5.2% in two preregistered observational studies (climate scientists on Twitter, N  > 8 million Tweets; climate subreddit, N  > 17,000 posts and comments). We speculated that the decreased liking was due, not to reduced engagement, but to more negative feelings towards climate-related content described with numeric precision. A preregistered within-participant experiment (N = 212) then varied whether climate consequences were described using Arabic integers (e.g. "90%") or another format (e.g. verbal terms, "almost all"). The presence of Arabic integers about consequences led to more sharing, wanting to find out more, and greater trust and perceptions of an expert messenger; perceived trust and expertise appeared to mediate effects on sharing and wanting to find out more. Arabic integers about consequences again led to more negative feelings about the Tweets as if numbers clarified the dismaying magnitude of climate threats. Our results indicate that harnessing the power of numbers could increase public trust and concern regarding this defining issue of our time. Communicators, however, should also consider counteracting associated negative feelings-that could halt action-by providing feasible solutions to increase people's self-efficacy.

Instrumental goal activation increases online petition support across languages.

Research on processing fluency and instrumental goal activation suggests people often perceive complex information positively when effort in a task is valued. The current article evaluates this idea in five online petition samples (total N = 1,047,655 petitions and over 200 million words), assessing how the linguistic fluency of a petition associates with support. Consistent with prior work, petitions with lower rates of lexical fluency (fewer common words) associated with more signatures and an increased probability of petitions making a concrete change than those with higher rates of lexical fluency (more common words). Exploratory results suggest other forms of linguistic complexity also associated with petition support: petitions with more analytic writing (e.g., more formal and complex writing patterns) and with less structural fluency (less readable writing) received more signatures than those with less analytic writing and more structural fluency. Controlling for the political leaning of the petition writers as inferred by their language patterns revealed consistent effects. Crucially, the lexical fluency results were maintained across eight languages as well. Various types of linguistic complexity are therefore instrumental to get people to support online causes. Contributions to fluency theory and the psychology of giving are discussed. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Contextual considerations for deception production and detection in forensic interviews.

Most deception scholars agree that deception production and deception detection effects often display mixed results across settings. For example, some liars use more emotion than truth-tellers when discussing fake opinions on abortion, but not when communicating fake distress. Similarly, verbal and nonverbal cues are often inconsistent predictors to assist in deception detection, leading to mixed accuracies and detection rates. Why are lie production and detection effects typically inconsistent? In this piece, we argue that aspects of the context are often unconsidered in how lies are produced and detected. Greater theory-building related to contextual constraints of deception are therefore required. We reintroduce and extend the Contextual Organization of Language and Deception (COLD) model, a framework that outlines how psychological dynamics, pragmatic goals, and genre conventions are aspects of the context that moderate the relationship between deception and communication behavior such as language. We extend this foundation by proposing three additional aspects of the context - individual differences, situational opportunities for deception, and interpersonal characteristics - for the COLD model that can specifically inform and potentially improve forensic interviewing. We conclude with a forward-looking perspective for deception researchers and practitioners related to the need for more theoretical explication of deception and its detection related to the context.

Cross-checking journalistic fact-checkers: The role of sampling and scaling in interpreting false and misleading statements.

Professional fact-checkers and fact-checking organizations provide a critical public service. Skeptics of modern media, however, often question the accuracy and objectivity of fact-checkers. The current study assessed agreement among two independent fact-checkers, The Washington Post and PolitiFact, regarding the false and misleading statements of then President Donald J. Trump. Differences in statement selection and deceptiveness scaling were investigated. The Washington Post checked PolitiFact fact-checks 77.4% of the time (22.6% selection disagreement). Moderate agreement was observed for deceptiveness scaling. Nearly complete agreement was observed for bottom-line attributed veracity. Additional cross-checking with other sources (Snopes, FactCheck.org), original sources, and with fact-checking for the first 100 days of President Joe Biden's administration were inconsistent with potential ideology effects. Our evidence suggests fact-checking is a difficult enterprise, there is considerable variability between fact-checkers in the raw number of statements that are checked, and finally, selection and scaling account for apparent discrepancies among fact-checkers.

Gender and ethnicity bias in medicine: a text analysis of 1.8 million critical care records.

Gender and ethnicity biases are pervasive across many societal domains including politics, employment, and medicine. Such biases will facilitate inequalities until they are revealed and mitigated at scale. To this end, over 1.8 million caregiver notes (502 million words) from a large US hospital were evaluated with natural language processing techniques in search of gender and ethnicity bias indicators. Consistent with nonlinguistic evidence of bias in medicine, physicians focused more on the emotions of women compared to men and focused more on the scientific and bodily diagnoses of men compared to women. Content patterns were relatively consistent across genders. Physicians also attended to fewer emotions for Black/African and Asian patients compared to White patients, and physicians demonstrated the greatest need to work through diagnoses for Black/African women compared to other patients. Content disparities were clearer across ethnicities, as physicians focused less on the pain of Black/African and Asian patients compared to White patients in their critical care notes. This research provides evidence of gender and ethnicity biases in medicine as communicated by physicians in the field and requires the critical examination of institutions that perpetuate bias in social systems.

An unusual cutaneous manifestation of Crohn's disease.

A 61-year-old man with a 12-year history of quiescent Crohn's disease on mesalamine presented to his gastroenterologist in April 2009, complaining of abdominal cramping, diarrhea, and a 25-lb weight loss over 6 weeks. He did not respond to prednisone 50 mg and 6-mercaptopurine 100 mg daily. Abdominal computed tomography findings revealed diffuse submucosal edema consistent with extensive colitis. Colonoscopy demonstrated diffuse inflammation with erythema, friability, and shallow ulcerations in the rectum and colon. Biopsies were consistent with Crohn's colitis. He was admitted for infliximab infusion for his unremitting diarrhea. Five days before admission, the patient noted mild swelling and redness of the left lower eyelid, which progressed to involve the right lower eyelid with frank pus draining from both eyes. He had no visual impairment or eye pain. Two days before admission, an ophthalmologist prescribed a steroid eyedrop with no relief. He also complained of seropurulent painful skin lesions on his face and scalp, which spread to involve his upper trunk and proximal arms. On admission to the hospital, dermatology, ophthalmology, and infectious disease consultations were obtained to rule out disseminated infection before initiation of infliximab therapy. The patient was afebrile and hemodynamically stable. His oral mucosa was normal. He had prominent bilateral lower eyelid edema, erythema, and superficial erosions with hemorrhagic crusting and frank green purulent drainage from both eyes, with crusting along the lower lash line and bilateral sclera injection (Figure 1). On his scalp, face, trunk, and proximal extremities, he had 25 to 30 erythematous, 4- to 8-mm papulopustules with narrow red halos, some with central necrosis and crusting (Figure 2). Cultures from the purulent ocular drainage and pustules on the trunk and arms were all negative for bacteria, virus, and fungi. Gram stain from the eye drainage showed polymorphonuclear leukocytes without organisms. Tissue cultures were negative for bacterial, fungal, and mycobacterial infection. Skin biopsy taken from the central upper back demonstrated subcorneal pustules with areas of eroded epidermis and collections of neutrophils in the superficial dermis (Figure 3). Special stains were negative for organisms. He received infliximab infusion 5 mg/kg for a total dose of 420 mg over 2 hours. Within 48 hours of infusion, there was notable decrease in size of lesions, in addition to reduction of purulent drainage from both eyes. The patient was discharged home following infliximab infusion. His skin lesions resolved during a period of 2 weeks, leaving small pink atrophic scars. He received his second infusion of infliximab 2 weeks after discharge with continued improvement in his gastrointestinal symptoms.

Why we dehumanize illegal immigrants: A US mixed-methods study.

Dehumanization is a topic of significant interest for academia and society at large. Empirical studies often have people rate the evolved nature of outgroups and prior work suggests immigrants are common victims of less-than-human treatment. Despite existing work that suggests who dehumanizes particular outgroups and who is often dehumanized, the extant literature knows less about why people dehumanize outgroups such as immigrants. The current work takes up this opportunity by examining why people dehumanize immigrants said to be illegal and how measurement format affects dehumanization ratings. Participants (N = 672) dehumanized such immigrants more if their ratings were made on a slider versus clicking images of hominids, an effect most pronounced for Republicans. Dehumanization was negatively associated with warmth toward illegal immigrants and the perceived unhappiness felt by illegal immigrants from U.S. immigration policies. Finally, most dehumanization is not entirely blatant but instead, captured by virtuous violence and affect as well, suggesting the many ways that dehumanization can manifest as predicted by theory. This work offers a mechanistic account for why people dehumanize immigrants and addresses how survey measurement artifacts (e.g., clicking on images of hominids vs. using a slider) affect dehumanization rates. We discuss how these data extend dehumanization theory and inform empirical research.

Virtual reality and the psychology of climate change.

Researchers and practitioners have used virtual reality (VR) as a tool to understand attitudes and behaviors around climate change for decades. As VR has become more immersive, mainstream, and commercially available, it has also become a medium for education about climate issues, a way to indirectly expose users to novel stimuli, and a tool to tell stories about antienvironmental activity. This review explicates the relationship between VR and climate change from a psychological perspective and offers recommendations to make virtual experiences engaging, available, and impactful for users. Climate change is perhaps the most urgent global issue of our lifetime with irreversible consequences. It therefore requires innovative experiential approaches to teach its effects and modify attitudes in support of proenvironmental actions.