Background As a major virus outbreak in the 21st century, the Coronavirus disease 2019 (COVID-19) pandemic has led to unprecedented hazards to mental health globally. While psychological support is being provided to patients and healthcare workers, the general public's mental health requires significant attention as well. This systematic review aims to synthesize extant literature that reports on the effects of COVID-19 on psychological outcomes of the general population and its associated risk factors. Methods A systematic search was conducted on PubMed, Embase, Medline, Web of Science, and Scopus from inception to 17 May 2020 following the PRISMA guidelines. A manual search on Google Scholar was performed to identify additional relevant studies. Articles were selected based on the predetermined eligibility criteria. Results: Relatively high rates of symptoms of anxiety (6.33% to 50.9%), depression (14.6% to 48.3%), post-traumatic stress disorder (7% to 53.8%), psychological distress (34.43% to 38%), and stress (8.1% to 81.9%) are reported in the general population during the COVID-19 pandemic in China, Spain, Italy, Iran, the US, Turkey, Nepal, and Denmark. Risk factors associated with distress measures include female gender, younger age group (≤40 years), presence of chronic/psychiatric illnesses, unemployment, student status, and frequent exposure to social media/news concerning COVID-19. Limitations A significant degree of heterogeneity was noted across studies. Conclusions The COVID-19 pandemic is associated with highly significant levels of psychological distress that, in many cases, would meet the threshold for clinical relevance. Mitigating the hazardous effects of COVID-19 on mental health is an international public health priority.
A growing social science literature has used Twitter and Facebook to study political and social phenomena including for election forecasting and tracking political conversations. This research note uses a nationally representative probability sample of the British population to examine how Twitter and Facebook users differ from the general population in terms of demographics, political attitudes and political behaviour. We find that Twitter and Facebook users differ substantially from the general population on many politically relevant dimensions including vote choice, turnout, age, gender, and education. On average social media users are younger and better educated than non-users, and they are more liberal and pay more attention to politics. Despite paying more attention to politics, social media users are less likely to vote than non-users, but they are more likely to support the left leaning Labour Party when they do vote. However, we show that these apparent differences mostly arise due to the demographic composition of social media users. After controlling for age, gender, and education, no statistically significant differences arise between social media users and non-users on political attention, values or political behaviour.
Recent advancements in artificial intelligence, particularly with the emergence of large language models (LLMs), have sparked a rethinking of artificial general intelligence possibilities. The increasing human-like capabilities of AI are also attracting attention in social science research, leading to various studies exploring the combination of these two fields. In this survey, we systematically categorize previous explorations in the combination of AI and social science into two directions that share common technical approaches but differ in their research objectives. The first direction is focused on AI for social science, where AI is utilized as a powerful tool to enhance various stages of social science research. While the second direction is the social science of AI, which examines AI agents as social entities with their human-like cognitive and linguistic capabilities. By conducting a thorough review, particularly on the substantial progress facilitated by recent advancements in large language models, this paper introduces a fresh perspective to reassess the relationship between AI and social science, provides a cohesive framework that allows researchers to understand the distinctions and connections between AI for social science and social science of AI, and also summarized state-of-art experiment simulation platforms to facilitate research in these two directions. We believe that as AI technology continues to advance and intelligent agents find increasing applications in our daily lives, the significance of the combination of AI and social science will become even more prominent.
Abstract While numerous studies have examined the initial adoption of integrated soil fertility management (ISFM) practices, little is known about the factors that sustain their continued use over time. This study addresses this knowledge gap by analyzing the determinants of sustained ISFM adoption among smallholder farmers in northern Ghana. The analysis draws on primary data from a 2023 structured survey of 412 randomly selected maize-farming households across 15 communities—formerly part of the Northern Region, now administratively designated as the Savannah and Northeast regions—and highlights the roles of insurance awareness, extension services, market accessibility, and credit availability. The results show that insurance awareness is positively associated with intercropping or relay cropping, yet negatively correlated with continued use of improved seeds, suggesting the need for insurance products that better align with specific input strategies. Market inaccessibility emerges as a major constraint, underscoring the importance of rural infrastructure development to support ISFM uptake. Credit availability exhibits a positive but statistically insignificant association with chemical fertilizer use, while it is significantly negatively associated with organic fertilizer use, indicating a potential trade-off whereby improved financial access may favor chemical inputs over organic ones. Extension services and household labor availability are both positively associated with input intensity, emphasizing the roles of information and labor resources in sustaining ISFM practices. Overall, the findings suggest the need for integrated policy measures combining tailored insurance schemes, infrastructure investment, and balanced financial support to promote long-term ISFM adoption and sustainable agricultural intensification.
History of scholarship and learning. The humanities, Social Sciences
Tanja Kojić, Maurizio Vergari, Maximilian Warsinke
et al.
This study investigates the impact of the Degree of Interactivity on User Experience (UX) and social acceptability (SA) in Mobile Augmented Reality (MAR) applications. As AR technologies become more prevalent, understanding how varying levels of interactivity influence both user perception and social dynamics is crucial for their design and adoption. Two commercially available MAR applications, IKEA and Virtlo, which differ significantly in their interactivity levels, were used to conduct a user study. The study examines how body movements required for interaction with AR content affect both UX and SA, shedding light on users' comfort levels and potential social barriers in public settings. The findings suggest a complex relationship between interactivity, perceived usability, and social considerations, emphasizing the need for a balanced design approach. This research provides valuable insights into the development of future AR applications by addressing not only usability but also the broader social implications of AR interactions. By integrating social acceptability into traditional UX evaluations, this study highlights its significance in ensuring the seamless integration of AR technologies into everyday environments.
Juliana Yimabel Ballesteros Menéndez, Joe Moisés Gallegos Burnham, Johana del Carmen Parreño Sánchez
et al.
La presente investigación tiene como tema central el estudio de las herramientas digitales para mejorar la evaluación del aprendizaje en la educación superior. De igual forma, identificar los fundamentos teóricos del uso de herramientas digitales en la evaluación. La investigación adoptó un diseño no experimental con un enfoque mixto. La modalidad de estudio fue documental bibliográfico, dado que se centró en la búsqueda, recuperación de la información obtenida de fuentes documentales. La población se enfocó en los estudiantes y docentes de la Facultad de Educación de la carrera de Educación Básica, en la Universidad Bolivariana del Ecuador. La población objetiva está constituida por aquellos que se encuentran cursando los últimos años de la carrera, estudiantes totales 4677 la muestra 55 estudiantes del grupo 30 y 10 docentes que imparten asignaturas pedagógicas en la misma carrera. El método de selección fue un muestreo intencional no probabilístico que aporta información relevante sobre su efectividad. Para la recolección de datos se empleó la encuesta para docentes y estudiantes las cuales están diseñadas para garantizar la validez y la relevancia de los datos. Los resultados mostraron que el 35,7% de los encuestados manifiestan que siempre emplean herramientas digitales en el proceso de evaluación. Así también, un 35,7% manifiestan casi siempre emplean herramientas digitales. En cambio, un 28.6% manifiestan que rara vez emplean herramientas digitales. Se concluye que las herramientas digitales para mejorar la evaluación del aprendizaje en la educación superior son fundamentales, puesto que promueve el desarrollo profesional y reflexivo del estudiante.
The social metaverse is a growing digital ecosystem that blends virtual and physical worlds. It allows users to interact socially, work, shop, and enjoy entertainment. However, privacy remains a major challenge, as immersive interactions require continuous collection of biometric and behavioral data. At the same time, ensuring high-quality, low-latency streaming is difficult due to the demands of real-time interaction, immersive rendering, and bandwidth optimization. To address these issues, we propose ASMS (Adaptive Social Metaverse Streaming), a novel streaming system based on Federated Multi-Agent Proximal Policy Optimization (F-MAPPO). ASMS leverages F-MAPPO, which integrates federated learning (FL) and deep reinforcement learning (DRL) to dynamically adjust streaming bit rates while preserving user privacy. Experimental results show that ASMS improves user experience by at least 14% compared to existing streaming methods across various network conditions. Therefore, ASMS enhances the social metaverse experience by providing seamless and immersive streaming, even in dynamic and resource-constrained networks, while ensuring that sensitive user data remains on local devices.
Michael D. Ekstrand, Afsaneh Razi, Aleksandra Sarcevic
et al.
Recommender systems are usually designed by engineers, researchers, designers, and other members of development teams. These systems are then evaluated based on goals set by the aforementioned teams and other business units of the platforms operating the recommender systems. This design approach emphasizes the designers' vision for how the system can best serve the interests of users, providers, businesses, and other stakeholders. Although designers may be well-informed about user needs through user experience and market research, they are still the arbiters of the system's design and evaluation, with other stakeholders' interests less emphasized in user-centered design and evaluation. When extended to recommender systems for social good, this approach results in systems that reflect the social objectives as envisioned by the designers and evaluated as the designers understand them. Instead, social goals and operationalizations should be developed through participatory and democratic processes that are accountable to their stakeholders. We argue that recommender systems aimed at improving social good should be designed *by* and *with*, not just *for*, the people who will experience their benefits and harms. That is, they should be designed in collaboration with their users, creators, and other stakeholders as full co-designers, not only as user study participants.
This research article aims to study the Phitsanulok political movements and behaviors of a political machine in terms of voter mobilization in the year 2023. Research data were collected by a qualitative research method, including documentary research, in-depth interviews of 19 key informants who were involved as a political machine, including participant and non-participant observations. Research findings showed that Thai structural changes (political economy landscape), institutional change (constitutional amendments and a new electoral system), and technological change (social media) connected all political actors in an electoral process into a closer relation. This led to transformative political behaviors of the political machine of Phitsanulok, from personal favoritism, beneficial reciprocity, and patronage system into upholding political ideologies and party favoritism. However, the political machine did not fade away; it adjusted its operations and processes. As a result, the election in Phitsanulok province in 2023 had changed the political machine into the voter mobilization based on the ideology contestation between conservatism and liberalism, at both local and national levels. Each party and its representatives had opportunities to create an 'open' political space that had not been taken by any political groups.
Arman Isajanyan, Artur Shatveryan, David Kocharyan
et al.
Social reward as a form of community recognition provides a strong source of motivation for users of online platforms to engage and contribute with content. The recent progress of text-conditioned image synthesis has ushered in a collaborative era where AI empowers users to craft original visual artworks seeking community validation. Nevertheless, assessing these models in the context of collective community preference introduces distinct challenges. Existing evaluation methods predominantly center on limited size user studies guided by image quality and prompt alignment. This work pioneers a paradigm shift, unveiling Social Reward - an innovative reward modeling framework that leverages implicit feedback from social network users engaged in creative editing of generated images. We embark on an extensive journey of dataset curation and refinement, drawing from Picsart: an online visual creation and editing platform, yielding a first million-user-scale dataset of implicit human preferences for user-generated visual art named Picsart Image-Social. Our analysis exposes the shortcomings of current metrics in modeling community creative preference of text-to-image models' outputs, compelling us to introduce a novel predictive model explicitly tailored to address these limitations. Rigorous quantitative experiments and user study show that our Social Reward model aligns better with social popularity than existing metrics. Furthermore, we utilize Social Reward to fine-tune text-to-image models, yielding images that are more favored by not only Social Reward, but also other established metrics. These findings highlight the relevance and effectiveness of Social Reward in assessing community appreciation for AI-generated artworks, establishing a closer alignment with users' creative goals: creating popular visual art. Codes can be accessed at https://github.com/Picsart-AI-Research/Social-Reward
ABSTRACT Pets are an important aspect of many families and households, but how many Americans have them? The purpose of this study is to compare point estimates of pet ownership in the U.S. from the General Social Survey (GSS) to estimates from other surveys, and to report demographic and social correlates to pet ownership. Wide discrepancies in estimates of U.S. pet ownership have been previously reported, relying on private industry surveys that do not disclose sampling design. Further, some surveys that reported pet ownership were not available for public use and/or did not lend themselves to social science due to a limited number of other measures of important social and demographic characteristics. U.S. estimates of pet ownership from the GSS tended to be slightly higher than those based on the American Veterinary Medical Association Pet Ownership and Demographics Sourcebook and consistently lower than estimates based on the American Pet Products Association National Pet Owners Survey. Pet ownership varied by race/ethnicity, age, size of place, household composition, and dwelling type. Number and type of pets also varied considerably by social and demographic characteristics. We conclude that the 2018 GSS has several advantages for studying human–animal interaction including a nationally representative sample, availability of a wide range of covariates, and public accessibility.
In this essay, we argue that gerontologists should increase their engagement with anthropologists to increase transdisciplinary collaboration, fulfill the interdisciplinary promise of gerontology as a field, and to ensure the work of anthropologists is formed by, and employed in, situations where meaningful engagement with practitioners and policymakers can lead to social change. Anthropology is the study of human societies in historical, biological, and sociocultural context, comprising a holistic field of study that can contribute unique methods, approaches, and theories to the field of gerontology. Although increasing amounts of anthropological scholarship have focused on older adulthood, this critical work of anthropologists still needs to be utilized by those in positions of power to enact change. Furthermore, the work conducted by anthropologists of aging has not consistently been recognized as anthropological scholarship. Therefore, a notable gap exists between the promise of the anthropology of aging and the utilization of the field, its findings, and engagement with the broader gerontological academy. As such, the contributions of anthropology to aging scholarship and the resulting reduction in inequities in the aging experience are not always adequately recognized. By examining the history of anthropology’s engagement with aging and the lifecourse, we argue for a more applied anthropological gerontology. We conclude with a call to action to ensure that anthropological gerontology is seen as a fundamental branch of scholarship, both within anthropology and gerontology, which can be used to improve the lived experiences of older adults globally.
Edna Paola Fresneda-Patiño, Gabriel Jacobo Sánchez Coral
Con este documento queremos proponer una caracterización de nuestra experiencia como docentes que hemos situado nuestras prácticas investigativas desde la Educación Matemática Crítica y la Etnomatemática, en la que confluye una idea de sujeto político que transforma las concepciones de ser profesor(a) de matemáticas. Nosotros coincidimos hace algunos años en un congreso académico internacional en el que se discutían propuestas investigativas y prácticas pedagógicas enmarcadas en perspectivas alejadas de enfoques cognitivistas y más próximas a dimensiones sociales, políticas y culturales. Allí, compartimos nuestros trabajos académicos y años más tarde nos reencontramos en el II Encuentro de la Red de Educadores Matemáticos Críticos, notando que, si bien nuestros intereses no habían cambiado, estábamos interesados en reconocer la voz del sujeto al relatar sus experiencias investigativas situadas desde enfoques sociales, políticos y culturales de la educación matemática. Para ello usamos las narrativas orales y escritas para estudiar y reflexionar sobre nuestras propias experiencias como docentes de matemáticas. Para lograrlo, teóricamente nos fundamentamos en las ideas del enfoque social, político y cultural, especialmente, en la Educación Matemática Crítica y la Etnomatemática, caracterizando tanto la idea de sujeto político como de contexto sociopolítico. Con relación a la metodología, retomamos la idea de experiencia de Jorge Larrosa y las características de la investigación biográfico-narrativa, usando particularmente los escritos autobiográficos producidos por los autores del presente documento. Buscamos dar vida a la voz del sujeto al narrar sus propias experiencias como docentes e investigadores de carne y hueso que intentan privilegiar en el aula de clase espacios de discusión sobre asuntos sociales, políticos y culturales que se inscriben en los contextos cotidianos de las escuelas colombianas. Además, reconocemos la importancia de usar las matemáticas como herramienta que nos permite leer, interpretar y transformar el mundo y las condiciones de nuestra sociedad actual, reconociéndonos como sujetos políticos agentes de cambio
Ana Paula Jesus, Marta Ferreira Dias, Margarida Coelho
This paper explores the correlation between respondents concerns regarding climate change, their eagerness to adopt an AFV and their responsiveness to incentives. Seen as the solution for a cleaner mobility and greenhouse gas reduction in urban areas globally, alternative fuel vehicles (AFV) still own a modest market share in Europe. Among many reasons, the purchase price seems to be one of the most challenging to overcome. Incentives are considered a solution to mitigate the price barrier. The results of a survey carried out by the authors to 444 respondents led the authors to conclude that participants agree that AFVs contribute to tackle climate change. They also deduced that the vehicles price represents an offside for the lower-income households. Furthermore, the study revealed that the latter are less prone to buy an alternative fuel vehicle than higher-income families (59% against 80%). The authors also inferred that generally, households are more receptive to incentives or benefits based on up-front discounts or exemptions, directly impacting price and immediate savings, such as taxes exemption (value added tax and circulation tax), fuel discounts and purchase incentives. However, some differences were observed between income segments. For instance, the reduction or exemption of loan interests is among the most popular incentives for lower revenues, whilst higher revenues favour scrappage and non-financial incentives. Finally, in line with other studies, as upper incomes are less dependent on incentives and benefits to carry out the purchase, the authors put forward a differential and progressive approach for incentive instruments targeting lower revenues, allowing broader and equitable access to low carbon technology.
Engineering (General). Civil engineering (General), Social sciences (General)
Adelmo Eloy, Thomas Palmeira Ferraz, Fellip Silva Alves
et al.
Science and Engineering fairs offer K-12 students opportunities to engage with authentic STEM practices. Particularly, students are given the chance to experience authentic and open inquiry processes, by defining which themes, questions and approaches will guide their scientific endeavors. In this study, we analyzed data from over 5,000 projects presented at a nationwide science fair in Brazil over the past 20 years using topic modeling to identify the main topics that have driven students' inquiry and design. Our analysis identified a broad range of topics being explored, with significant variations over time, region, and school setting. We argue those results and proposed methodology can not only support further research in the context of science fairs, but also inform instruction and design of contexts-specific resources to support students in open inquiry experiences in different settings.
The rapid growth of technology and computer science, which has led to a surge in demand for skilled professionals in this field. The skill set required for computer science jobs has evolved rapidly, creating challenges for those already in the workforce who need to adapt their skills quickly to meet industry demands. To stay ahead of the curve, it is essential to understand the hottest skills needed in the field. The article introduces a new method for analyzing job advertisements using social network analysis to identify the most critical skills required by employers in the market. In this research, to form the communication network of skills, first 5763 skills were collected from the LinkedIn social network, then the relationship between skills was collected and searched in 7777 computer science job advertisements, and finally, the balanced communication network of skills was formed. The study analyzes the formed communication network of skills in the computer science job market and identifies four distinct communities of skills: Generalists, Infrastructure and Security, Software Development, and Embedded Systems. The findings reveal that employers value both hard and soft skills, such as programming languages and teamwork. Communication skills were found to be the most important skill in the labor market. Additionally, certain skills were highlighted based on their centrality indices, including communication, English, SQL, Git, and business skills, among others. The study provides valuable insights into the current state of the computer science job market and can help guide individuals and organizations in making informed decisions about skills acquisition and hiring practices.