Hasil untuk "Social Sciences"

J. V. Bavel, Katherine Baicker, Paulo S Boggio et al.

The COVID-19 pandemic represents a massive global health crisis. Because the crisis requires large-scale behaviour change and places significant psychological burdens on individuals, insights from the social and behavioural sciences can be used to help align human behaviour with the recommendations of epidemiologists and public health experts. Here we discuss evidence from a selection of research topics relevant to pandemics, including work on navigating threats, social and cultural influences on behaviour, science communication, moral decision-making, leadership, and stress and coping. In each section, we note the nature and quality of prior research, including uncertainty and unsettled issues. We identify several insights for effective response to the COVID-19 pandemic and highlight important gaps researchers should move quickly to fill in the coming weeks and months. Forty-three experts highlight some key insights from the social and behavioural sciences for effective response to the COVID-19 pandemic and point out important gaps researchers should move quickly to fill in the coming weeks and months.

R. Wilson, S. Gosling, Lindsay T. Graham

M. Weber

P. Hedström, P. Ylikoski

Sheri Berman

A. Wimmer, N. Schiller

Methodological nationalism is understood as the assumption that the nation/state/society is the natural social and political form of the modern world. We distinguish three modes of methodological nationalism that have characterized main- stream social science, and then show how these have influenced research on migra- tion. We discover parallels between nationalist thinking and the conceptualization of migration in postwar social sciences. In a historical tour d'horizon, we show that this mainstream concept has developed in close interaction with nation-state building pro- cesses in the West and the role that immigration and integration policies have played within them. The shift towards a study of 'transnational communities' - the last phase in this process - was more a consequence of an epistemic move away from methodo- logical nationalism than of the appearance of new objects of observation. The article concludes by recommending new concepts for analysis that, on the one hand, are not coloured by methodological nationalism and, on the other hand, go beyond the fluidism of much contemporary social theory. After the first flurry of confusion about the nature and extent of contemporary pro- cesses of globalization, social scientists moved beyond rhetorical generalities about the decline of the nation-state and began to examine the ways in which nation-states are currently being reconfigured rather than demolished. That nation-states and nationalism are compatible with globalization was made all too obvious. We wit- nessed the flouring of nationalism and the restructuring of a whole range of new states in Eastern Europe along national lines in the midst of growing global interconnec- tions. The concomitance of these processes provides us with an intellectual opening to think about the limitations of our conceptual apparatus. It has become easier to under- stand that it is because we have come to take for granted a world divided into discrete and autonomous nation-states that we see nation-state building and global inter- connections as contradictory. The next step is to analyse how the concept of the nation-state has and still does influence past and current thinking in the social sciences, including our thinking about transnational migration. It is our aim in this article to move in this direction by exploring the intellectual potential of two hypotheses. We demonstrate that nation-state building processes have fundamentally shaped the ways immigration has been perceived and received. These perceptions have in turn influenced, though not completely determined, social science

R. Stebbins

K. Thelen

J. Landeta

F. Castro

D. Kaplan

Zhiye Jin, Yibai Li, K. D. Joshi et al.

This study presents the development of the PsyCogMetrics AI Lab (psycogmetrics.ai), an integrated, cloud-based platform that operationalizes psychometric and cognitive-science methodologies for Large Language Model (LLM) evaluation. Framed as a three-cycle Action Design Science study, the Relevance Cycle identifies key limitations in current evaluation methods and unfulfilled stakeholder needs. The Rigor Cycle draws on kernel theories such as Popperian falsifiability, Classical Test Theory, and Cognitive Load Theory to derive deductive design objectives. The Design Cycle operationalizes these objectives through nested Build-Intervene-Evaluate loops. The study contributes a novel IT artifact, a validated design for LLM evaluation, benefiting research at the intersection of AI, psychology, cognitive science, and the social and behavioral sciences.

Masanori Takano, Kenji Yokotani, Takahiro Kato et al.

Online communication via avatars provides a richer online social experience than text communication. This reinforces the importance of online social support. Online social support is effective for people who lack social resources because of the anonymity of online communities. We aimed to understand online social support via avatars and their social relationships to provide better social support to avatar users. Therefore, we administered a questionnaire to three avatar communication service users (Second Life, ZEPETO, and Pigg Party) and three text communication service users (Facebook, X, and Instagram) (N=8,947). There was no duplication of users for each service. By comparing avatar and text communication users, we examined the amount of online social support, stability of online relationships, and the relationships between online social support and offline social resources (e.g., offline social support). We observed that avatar communication service users received more online social support, had more stable relationships, and had fewer offline social resources than text communication service users. However, the positive association between online and offline social support for avatar communication users was more substantial than for text communication users. These findings highlight the significance of realistic online communication experiences through avatars, including nonverbal and real-time interactions with co-presence. The findings also highlighted avatar communication service users' problems in the physical world, such as the lack of offline social resources. This study suggests that enhancing online social support through avatars can address these issues. This could help resolve social resource problems, both online and offline in future metaverse societies.

Wendy Scholtes-Bos, Machteld van Lieshout, Michelle H. I. van Roost et al.

The Food Boost Challenge (FBC) uses a community-up participatory action research approach to promote healthier eating habits among young people, aged 10–24 years old, by giving them a voice in food system change. This approach encourages turning ideas into action through collaboration with young people, both adolescents and students, teachers, researchers, and food system partners. This study explored the impact of the FBC beyond its direct effect on healthy eating behavior, focusing on innovative idea generation and how participation affected young people and partners, at both the individual and community level, using indicators of community-based participatory action research. Ideas generated in various phases of the FBC were listed. Data were collected using semi-structured interviews with young people, digital feedback surveys after group meetings, and informal discussions with partner representatives to explore the impact of participation in the FBC. The results demonstrate positive effects, including changes in participant’s attitudes toward healthy eating, skill development among young people, and enhanced collaboration among stakeholders. Along the lines of the Community-Based Participatory Research conceptual model, the Food Boost Challenge fostered trust development, mutual learning, and capacity building at both individual and community levels. In conclusion, utilizing a community-up participatory action research approach, the Food Boost Challenge shows significant promise in empowering young people and fostering community-level changes. To translate its generated innovative solutions into real impact, a structured implementation phase is essential.

Abolfazl Kazzazi, Amir Mohammad khani

<p>This study aims to investigate the unique features of the food supply chain, examining the impact of food supply chain integration, consisting of internal integration, supplier and customer, the quality of food products and product innovation capability. Managers need to understand the importance of supplier and customer integration when responding to supply chain risk and company uncertainty. The data were collected from 168 managers active in the food industry in Tehran province. The partial least squares tool (SmartPLS 3.0) was used to analyze the data using Structural Equation Modeling (SEM) technique. The results show that there is a strong relationship between uncertainty and supply chain integration including customer, supplier and internal integration. The findings indicate that customer integration and supplier integration are critical factors in improving product quality in the food supply chain. The results can be related to the prominent role of customer relations and contact in the development of innovation capabilities in manufactured products, which has also been approved by some previous studies. Additionally, analyzing the various dimensions of supply chain integration separately revealed that internal integration is a capability factor for external integration. This study can help businesses in the food industry understand the value-creating roles of food supply chain integration and provide valuable guidance for them to decide how to meet the various challenges and manage food supply chain integration in order to improve product quality and product innovation capability.</p>

Rogelio Del Prado Flores, Rebeca-Illiana Arévalo-Martínez

T. Rajaretnam

Kai-Cheng Yang, Onur Varol, Alexander C. Nwala et al.

While social media are a key source of data for computational social science, their ease of manipulation by malicious actors threatens the integrity of online information exchanges and their analysis. In this Chapter, we focus on malicious social bots, a prominent vehicle for such manipulation. We start by discussing recent studies about the presence and actions of social bots in various online discussions to show their real-world implications and the need for detection methods. Then we discuss the challenges of bot detection methods and use Botometer, a publicly available bot detection tool, as a case study to describe recent developments in this area. We close with a practical guide on how to handle social bots in social media research.

Ghazal Kalhor, Hannah Gardner, Ingmar Weber et al.

Online professional social networking platforms provide opportunities to expand networks strategically for job opportunities and career advancement. A large body of research shows that women's offline networks are less advantageous than men's. How online platforms such as LinkedIn may reflect or reproduce gendered networking behaviours, or how online social connectivity may affect outcomes differentially by gender is not well understood. This paper analyses aggregate, anonymised data from almost 10 million LinkedIn users in the UK and US information technology (IT) sector collected from the site's advertising platform to explore how being connected to Big Tech companies ('social connectivity') varies by gender, and how gender, age, seniority and social connectivity shape the propensity to report job promotions or relocations. Consistent with previous studies, we find there are fewer women compared to men on LinkedIn in IT. Furthermore, female users are less likely to be connected to Big Tech companies than men. However, when we further analyse recent promotion or relocation reports, we find women are more likely than men to have reported a recent promotion at work, suggesting high-achieving women may be self-selecting onto LinkedIn. Even among this positively selected group, though, we find men are more likely to report a recent relocation. Social connectivity emerges as a significant predictor of promotion and relocation reports, with an interaction effect between gender and social connectivity indicating the payoffs to social connectivity for promotion and relocation reports are larger for women. This suggests that online networking has the potential for larger impacts for women, who experience greater disadvantage in traditional networking contexts, and calls for further research to understand differential impacts of online networking for socially disadvantaged groups.

Sho Tsugawa, Kohei Watabe

Identifying influencers in a given social network has become an important research problem for various applications, including accelerating the spread of information in viral marketing and preventing the spread of fake news and rumors. The literature contains a rich body of studies on identifying influential source spreaders who can spread their own messages to many other nodes. In contrast, the identification of influential brokers who can spread other nodes' messages to many nodes has not been fully explored. Theoretical and empirical studies suggest that involvement of both influential source spreaders and brokers is a key to facilitating large-scale information diffusion cascades. Therefore, this paper explores ways to identify influential brokers from a given social network. By using three social media datasets, we investigate the characteristics of influential brokers by comparing them with influential source spreaders and central nodes obtained from centrality measures. Our results show that (i) most of the influential source spreaders are not influential brokers (and vice versa) and (ii) the overlap between central nodes and influential brokers is small (less than 15%) in Twitter datasets. We also tackle the problem of identifying influential brokers from centrality measures and node embeddings, and we examine the effectiveness of social network features in the broker identification task. Our results show that (iii) although a single centrality measure cannot characterize influential brokers well, prediction models using node embedding features achieve F$_1$ scores of 0.35--0.68, suggesting the effectiveness of social network features for identifying influential brokers.