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Abstract Anti-vaccine trolling on video-hosting websites hinders efforts to increase vaccination rates by using toxic language and threatening claims to intimidate people and promote vaccine hesitancy. However, there is a shortage of research investigating the effects of toxic messages on these platforms. This study focused on YouTube anti-vaccine videos and examined the relationship between toxicity and fear in the comment section of these videos. We discovered that highly liked toxic comments were associated with a significant level of fear in subsequent comments. Moreover, we found complex patterns of contagion between toxicity and fear in the comments. These findings suggest that initial troll comments can evoke negative emotions in viewers, potentially fueling vaccine hesitancy. Our research bears essential implications for managing public health messaging and online communities, particularly in moderating fear-mongering messages about vaccines on social media.

Abstract The emergence of generative AI has sparked substantial discussions, with the potential to have profound impacts on society in all aspects. As emerging technologies continue to advance, it is imperative to facilitate their proper integration into society, managing expectations and fear. This paper investigates users’ perceptions of generative AI using 3M posts on Twitter from January 2019 to March 2023, especially focusing on their occupation and usage. We find that people across various occupations, not just IT-related ones, show a strong interest in generative AI. The sentiment toward generative AI is generally positive, and remarkably, their sentiments are positively correlated with their exposure to AI. Among occupations, illustrators show exceptionally negative sentiment mainly due to concerns about the unethical usage of artworks in constructing AI. People use ChatGPT in diverse ways, and notably the casual usage in which they “play with” ChatGPT tends to be associated with positive sentiments. These findings would offer valuable lessons for policymaking on the emergence of new technology and also empirical insights for the considerations of future human-AI symbiosis.

Predictions of node categories are commonly used to estimate homophily and other relational properties in networks. However, little is known about the validity of using predictions for this task. We show that estimating homophily in a network is a problem of predicting categories of dyads (edges) in the graph. Homophily estimates are unbiased when predictions of dyad categories are unbiased. Node-level prediction models, such as the use of names to classify ethnicity or gender, do not generally produce unbiased predictions of dyad categories and therefore produce biased homophily estimates. Bias comes from three sources: sampling bias, correlation between model errors and node degree, and correlation between node-level model errors along dyads. We examine three methods for estimating homophily: predicting node categories, predicting dyad categories, and a hybrid “ego–alter” approach. This analysis indicates that only the dyadic prediction approach is unbiased, whereas the node-level approach produces both high bias and high overall error. We find that node-level classification performance is not a reliable indicator of accuracy for homophily. Although this article focuses on a particular version of homophily, results generalize to heterophilous cases and other dyadic measures. We conclude with suggestions for research design. Code for this article is available at https://github.com/georgeberry/autocorr.

The transfer of power stemming from the 2020 presidential election occurred during an unprecedented period in United States history. Uncertainty from the COVID-19 pandemic, ongoing societal tensions, and a fragile economy increased societal polarization, exacerbated by the outgoing president's offline rhetoric. As a result, online groups such as QAnon engaged in extra political participation beyond the traditional platforms. This research explores the link between offline political speech and online extra-representational participation by examining Twitter within the context of the January 6 insurrection. Using a mixed-methods approach of quantitative and qualitative thematic analyses, the study combines offline speech information with Twitter data during key speech addresses leading up to the date of the insurrection; exploring the link between Trump's offline speeches and QAnon's hashtags across a 3-day timeframe. We find that links between online extra-representational participation and offline political speech exist. This research illuminates this phenomenon and offers policy implications for the role of online messaging as a tool of political mobilization.

Field experiences provide opportunities for early childhood and early childhood special education (EC/ECSE) educators to implement effective practices in learning settings, and are, therefore, a vital part of EC/ECSE teacher preparation. In this article, we describe field placement models from four universities in the United States: The Bridge Project, Getting Started Early, Peer Coaching to Increase Naturalistic Developmental Behavioral Interventions, and University Supervisors Coaching Teacher Candidates: Supporting Young Bi/Multilingual Children with Disabilities. Although there is variety in the settings and effective practices supported through these field placements, performance feedback and collaboration are clear themes across models.

Most discussions of higher education research in the last four decades have focused on expanding higher education, including increasing access, equity, and quality. However, the growth of higher education enrolment has slowed in many advanced higher education systems since the achievement of massification, with enrolment declining more dramatically in some systems than in others. South Korea (hereafter Korea), which has experienced one of the most dynamic evolutions in higher education, was recently reported to have the lowest birth rate among OECD countries, and its drastic demographic changes are significantly affecting all aspects of higher education. This paper describes Korea's shrinking youth population and its impact on different stakeholders in Korean higher education. It also reviews and evaluates Korea's policies in reaction to the declining population in higher education. The findings of this paper provide policy implications for countries that will experience similar challenges associated with declining enrolment in the years to come, including institutional closures, mergers, and strategies to maintain competitiveness.

Children with disabilities and developmental delays (DD) often face challenges within education systems, which are typically unprepared to meet their language needs nor equipped to support bilingualism because of the current early intervention (EI) workforce. Given this, the five-language domains framework can help bilingual EI educators to collaborate with caregivers in implementing research-based strategies to foster bilingual language development of young bilingual children within naturalistic environments. This paper provides research-based background information on the bilingual language of infants and toddlers with disabilities or DD and highlights how the five-language framework considers culturally appropriate practices and context.

Peer review in journals is in crisis, and its current situation and sustainability are increasingly concerning for academics and scientific communities. We identify this crisis as part of an evolutionary step in the continuous development of science, arguing that peer review maintains a central role. We analyse the emergence and historical development of peer review, identifying its role as crucial to the legitimisation of global science, particularly in guaranteeing quality control in the scientific process of massification--despite its flaws. We then focus on the crisis as part of the recent second wave of massification stemming from 'publish or perish' dynamics, which overburden those involved in peer review management and activities. Based on this crisis and given that the alternative models to peer review rely on the same core ideals, we argue that the current scenario represents a golden opportunity for the peer-review process to adapt by correcting some of its known biases, becoming more inclusive and relevant, and gaining recognition for its crucial role in career progression and in the training of the researchers of tomorrow.

This study explores Hong Kong university students' concerns when making employment decisions after graduation and their attitudes towards working in mainland China, especially in the Greater Bay Area (GBA). Two research questions were identified: What are Hong Kong students' attitudes towards working in the GBA? What factors influence Hong Kong students' employment choices? A qualitative research approach was adopted with semi-structured interviews with 38 final-year students from eight Hong Kong universities. Based on thematic analysis, the findings showed that Hong Kong university students' willingness to work in the GBA was mainly influenced by their previous connections with the destination and potential career development opportunities. However, Shenzhen was the only city out of nine in the GBA they considered for employment. University students were aware of the economic rationale for their employment preparation, but, more importantly, they placed a high value on professional development opportunities and work-life balance. They also valued opportunities for internationalisation and emphasised the importance of the work culture and environment in choosing employment. The findings have policy implications for graduate employment and the intra-mobility of talented young people across GBA cities in China.

This study explored Chinese students' motivations for selecting a cross-border university in China's Guangdong-Hong Kong-Macau Greater Bay Area (GBA) and how they perceive their undergraduate experiences. The GBA was developed as an international economic cluster in China. Despite the vitality of the GBA's international education sector, few studies have focused on individual students' perspectives on cross-border higher education choices and experiences. We interviewed twenty students and two academics in charge of university admissions about their opinions and reflections concerning a GBA cross-border university. Students' university choices were linked to different admission profiles, parental influences, institutional features and interactions between students and the institutions. Our study has significant implications for leaders and policymakers in higher education seeking to attract talented university students, improve enrolment and promote students' learning experiences in cross-border higher education institutions.

BACKGROUND: 2-Fucosyllactose (2-FL) is an oligosaccharide contained in human milk and possesses prebiotic and anti-inflammatory effects, which may alleviate skeletal muscle atrophy under caloric restriction. This study evaluated the impacts of 12 weeks of 2-FL supplementation in conjunction with exercise (10,000 steps/day, 5 days/week) and energy-reduced (-300 kcals/day) dietary interventions on changes in body composition and health-related biomarkers. METHODS: A total of 41 overweight and sedentary female and male participants (38.0 ± 13 years, 90.1 ± 15 kg, 31.6 ± 6.6 kg/m2, 36.9 ± 7% fat) took part in a randomized, double-blind, and placebo-controlled study. The participants underwent baseline assessments and were then assigned to ingest 3 g/day of a placebo (PLA) or Momstamin 2-F while initiating the exercise and weight-loss program. Follow-up tests were performed after 6 and 12 weeks. Data were analyzed using general linear model statistics with repeated measures and mean changes from baseline values with 95% confidence intervals (CIs). RESULTS: No group × time × sex interaction effects were observed, so group × time effects are reported. Participants in both groups saw comparable reductions in weight. However, those with 2-FL demonstrated a significantly greater reduction in the percentage of body fat and less loss of the fat-free mass. Additionally, there was evidence that 2-FL supplementation promoted more favorable changes in resting fat oxidation, peak aerobic capacity, IL-4, and platelet aggregation, with some minimal effects on the fermentation of short-chain fatty acids and monosaccharides in fecal samples. Moreover, participants perceptions regarding some aspects of the functional capacity and ratings of the quality of life were improved, and the supplementation protocol was well tolerated, although a small, but significant, decrease in BMC was observed. CONCLUSIONS: The results support contentions that dietary supplementation of 2-FL (3 g/d) can promote fat loss and improve exercise- and diet-related markers of health and fitness in overweight sedentary individuals initiating an exercise and weight-loss program. Further research is needed to explore the potential health benefits of 2-FL supplementation in both healthy and elderly individuals (Registered clinical trial #NCT06547801).

Although established marketing techniques have been applied to design more effective health campaigns, more often than not, the same message is broadcasted to large populations, irrespective of unique characteristics. As individual digital device use has increased, so have individual digital footprints, creating potential opportunities for targeted digital health interventions. We propose a novel precision public health campaign framework to structure and standardize the process of designing and delivering tailored health messages to target particular population segments using social media–targeted advertising tools. Our framework consists of five stages: defining a campaign goal, priority audience, and evaluation metrics; splitting the target audience into smaller segments; tailoring the message for each segment and conducting a pilot test; running the health campaign formally; and evaluating the performance of the campaigns. We have demonstrated how the framework works through 2 case studies. The precision public health campaign framework has the potential to support higher population uptake and engagement rates by encouraging a more standardized, concise, efficient, and targeted approach to public health campaign development.

Framing is a process of emphasizing a certain aspect of an issue over the others, nudging readers or listeners towards different positions on the issue even without making a biased argument. Here, we propose FrameAxis, a method for characterizing documents by identifying the most relevant semantic axes (“microframes”) that are overrepresented in the text using word embedding. Our unsupervised approach can be readily applied to large datasets because it does not require manual annotations. It can also provide nuanced insights by considering a rich set of semantic axes. FrameAxis is designed to quantitatively tease out two important dimensions of how microframes are used in the text. Microframe bias captures how biased the text is on a certain microframe, and microframe intensity shows how prominently a certain microframe is used. Together, they offer a detailed characterization of the text. We demonstrate that microframes with the highest bias and intensity align well with sentiment, topic, and partisan spectrum by applying FrameAxis to multiple datasets from restaurant reviews to political news. The existing domain knowledge can be incorporated into FrameAxis by using custom microframes and by using FrameAxis as an iterative exploratory analysis instrument. Additionally, we propose methods for explaining the results of FrameAxis at the level of individual words and documents. Our method may accelerate scalable and sophisticated computational analyses of framing across disciplines.

In this critique, we conceptually examine the use of personas in an age of availability of large-scale online analytics data. Based on the criticism and benefits outlined in prior work, we formulate the major arguments for and against the use of personas, analyze these arguments, and demonstrate areas for the productive employment of personas by leveraging digital analytics data in their creation. From our review of the prior literature and the given availability of online customer data, our key tenet is that personas are located between aggregated and individual statistics. At their best, personas capture the coverage of the customer base attributed to aggregated data representations while retaining the interpretability of individual-level analytics. Persona creation benefits from both novel computational techniques and data sources. To demonstrate this, we propose and implement automatically generated personas primarily based on quantitative data. We also review key persona validation issues and examine how these issues can be addressed with automated persona generation using real user data from online analytics platforms. Finally, we outline areas of future research in the persona domain within the field of digital marketing and advertising. Overall, to survive in the rapidly developing marketing industry and online customer analytics, personas must evolve by adopting new practices. There are implications for this evolution of personas in a variety of domains, including design, content creation, and digital marketing.

Exaggerated airway constriction triggered by repeated exposure to allergen, also called hyperreactivity, is a hallmark of asthma. Whereas vagal sensory neurons are known to function in allergen-induced hyperreactivity1-3, the identity of downstream nodes remains poorly understood. Here we mapped a full allergen circuit from the lung to the brainstem and back to the lung. Repeated exposure of mice to inhaled allergen activated the nuclei of solitary tract (nTS) neurons in a mast cell-, interleukin-4 (IL-4)- and vagal nerve-dependent manner. Single-nucleus RNA sequencing, followed by RNAscope assay at baseline and allergen challenges, showed that a Dbh+ nTS population is preferentially activated. Ablation or chemogenetic inactivation of Dbh+ nTS neurons blunted hyperreactivity whereas chemogenetic activation promoted it. Viral tracing indicated that Dbh+ nTS neurons project to the nucleus ambiguus (NA) and that NA neurons are necessary and sufficient to relay allergen signals to postganglionic neurons that directly drive airway constriction. Delivery of noradrenaline antagonists to the NA blunted hyperreactivity, suggesting noradrenaline as the transmitter between Dbh+ nTS and NA. Together, these findings provide molecular, anatomical and functional definitions of key nodes of a canonical allergen response circuit. This knowledge informs how neural modulation could be used to control allergen-induced airway hyperreactivity.

In the context of formative assessment in classrooms, the incorporation of automated evaluation (AE) systems and teachers' interactions with them hold significant importance. This study aimed to investigate the cognitive processes of pre-service teachers as they engaged with an AE system. We developed an unsupervised learning-based AE system, the Scoring Assistant using Artificial Intelligence (SAAI). SAAI calculates scores without relying on predefined labels and generates scientific keywords from student responses to provide constructive feedback. We collected a substantial number of constructed responses from students, and four pre-service teachers evaluated these responses initially without any external assistance and then re-evaluated them using SAAI scores as a reference point. Employing a mixed-methods approach, this study demonstrated a strong level of consistency between human raters and SAAI scores. Pre-service teachers also reflectively recalibrated their assessments and adjusted their rubrics to identify students' learning more accurately. This study highlights the practical application of AE in real classroom settings and demonstrates how AE can enhance efficiency and accuracy in K-12 science assessments, thus supporting teachers.