Hasil untuk "Social history and conditions. Social problems. Social reform"

A. Ornstein, Francis P. Hunkins

Christine Bennett

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.

Augustinas Jučas, Chirag Raman

Adaptively forecasting human behavior in social settings is an important step toward achieving Artificial General Intelligence. Most existing research in social forecasting has focused either on unfocused interactions, such as pedestrian trajectory prediction, or on monadic and dyadic behavior forecasting. In contrast, social psychology emphasizes the importance of group interactions for understanding complex social dynamics. This creates a gap that we address in this paper: forecasting social interactions at the group (conversation) level. Additionally, it is important for a forecasting model to be able to adapt to groups unseen at train time, as even the same individual behaves differently across different groups. This highlights the need for a forecasting model to explicitly account for each group's unique dynamics. To achieve this, we adopt a meta-learning approach to human behavior forecasting, treating every group as a separate meta-learning task. As a result, our method conditions its predictions on the specific behaviors within the group, leading to generalization to unseen groups. Specifically, we introduce Social Process (SP) models, which predict a distribution over future multimodal cues jointly for all group members based on their preceding low-level multimodal cues, while incorporating other past sequences of the same group's interactions. In this work we also analyze the generalization capabilities of SP models in both their outputs and latent spaces through the use of realistic synthetic datasets.

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.

Nur Shazwani Kamarudin, Ghazaleh Beigi, Lydia Manikonda et al.

There is an increasing number of virtual communities and forums available on the web. With social media, people can freely communicate and share their thoughts, ask personal questions, and seek peer-support, especially those with conditions that are highly stigmatized, without revealing personal identity. We study the state-of-the-art research methodologies and findings on mental health challenges like depression, anxiety, suicidal thoughts, from the pervasive use of social media data. We also discuss how these novel thinking and approaches can help to raise awareness of mental health issues in an unprecedented way. Specifically, this chapter describes linguistic, visual, and emotional indicators expressed in user disclosures. The main goal of this chapter is to show how this new source of data can be tapped to improve medical practice, provide timely support, and influence government or policymakers. In the context of social media for mental health issues, this chapter categorizes social media data used, introduces different deployed machine learning, feature engineering, natural language processing, and surveys methods and outlines directions for future research.

Mar Borges Afonso, Melina Sousa da Rocha

Esse estudo busca refletir sobre a experiência de uma pessoa transgênera não-binária, como iniciada no Candomblé. Considerando que as dinâmicas de gênero, pautadas na lógica binária, foram construídas pela colonialidade, buscamos refletir sobre como essas concepções também estão presentes nas religiões afro-brasileiras e excluem corpas que não se identificam pela dicotomia homem e mulher. Para realizar essa reflexão, utilizou-se o método história de vida para entrevistar uma pessoa trans* não-binária, iniciada em um Candomblé de Nação Ketu. Com isso, o estudo realizou uma revisão de literatura com vistas a contextualizar a percepção presente nessa tradição sobre as identidades de gênero, para dialogar com a experiência vivida. Observou-se a necessidade de acionar a filosofia da encruzilhada como forma de criticar as percepções de gênero tradicionais, reproduzidas nos Candomblés brasileiros, uma vez que a divisão social do gênero está diretamente relacionada às ideologias coloniais e não às cosmopercepções africanas.

C. Bayly

Chih-Chung Hsu, Chia-Ming Lee, Yu-Fan Lin et al.

Social media popularity (SMP) prediction is a complex task involving multi-modal data integration. While pre-trained vision-language models (VLMs) like CLIP have been widely adopted for this task, their effectiveness in capturing the unique characteristics of social media content remains unexplored. This paper critically examines the applicability of CLIP-based features in SMP prediction, focusing on the overlooked phenomenon of semantic inconsistency between images and text in social media posts. Through extensive analysis, we demonstrate that this inconsistency increases with post popularity, challenging the conventional use of VLM features. We provide a comprehensive investigation of semantic inconsistency across different popularity intervals and analyze the impact of VLM feature adaptation on SMP tasks. Our experiments reveal that incorporating inconsistency measures and adapted text features significantly improves model performance, achieving an SRC of 0.729 and an MAE of 1.227. These findings not only enhance SMP prediction accuracy but also provide crucial insights for developing more targeted approaches in social media analysis.

Adriana Grenčíková, Jana Španková, Richard Rigó et al.

The aging of the population is the main global demographic trend of the 21st century and one of the main factors in the formation of supply in the labor market. This study focuses on the aging of the population, which, in the context of the labor market, represents a problem for countries to sustain economic growth. The aim is to determine, based on the analysis of available statistical data, the impact of population aging on labor productivity and the labor market in the Slovak Republic. It also seeks to define how to mitigate the effects of population aging on maintaining economic growth and social stability without raising the retirement age. The study analyzed statistical indicators, utilizing OECD population projections and linking them to macroeconomic indicators (GDP, employment). Assuming GDP growth (3%) and labor productivity (2%) per year while maintaining 70% employment in comparison with population growth presented in the OECD forecasts, there will be approximately 367,000 unfilled jobs on the labor market in the Slovak Republic. Proposed solutions include pension reforms, investment in innovation and education for increased productivity, support for families to raise birth rates, simplified employment of workers from third countries, and improved working conditions for women. Addressing women’s working conditions can help compensate for the shortage in the aging workforce when combined with other solutions.

Nabeel Gillani, Rebecca Eynon

Over the past decade, an explosion in the availability of education-related datasets has enabled new computational research in education. Much of this work has investigated digital traces of online learners in order to better understand and optimize their cognitive learning processes. Yet cognitive learning on digital platforms does not equal education. Instead, education is an inherently social, cultural, economic, and political process manifesting in physical spaces, and educational outcomes are influenced by many factors that precede and shape the cognitive learning process. Many of these are social factors like children's connections to schools (including teachers, counselors, and role models), parents and families, and the broader neighborhoods in which they live. In this article, we briefly discuss recent studies of learning through large-scale digital platforms, but largely focus on those exploring sociological aspects of education. We believe computational social scientists can creatively advance this emerging research frontier-and in doing so, help facilitate more equitable educational and life outcomes.

Effrosyni Papanastasiou, Anastasios Giovanidis

Current network inference algorithms fail to generate graphs with edges that can explain whole sequences of node interactions in a given dataset or trace. To quantify how well an inferred graph can explain a trace, we introduce feasibility, a novel quality criterion, and suggest that it is linked to the result's accuracy. In addition, we propose CEM-*, a network inference method that guarantees 100% feasibility given online social media traces, which is a non-trivial extension of the Expectation-Maximization algorithm developed by Newman (2018). We propose a set of linear optimization updates that incorporate a set of auxiliary variables and a set of feasibility constraints; the latter takes into consideration all the hidden paths that are possible between users based on their timestamps of interaction and guide the inference toward feasibility. We provide two CEM-* variations, that assume either an Erdos Renyi (ER) or a Stochastic Block Model (SBM) prior for the underlying graph's unknown distribution. Extensive experiments on one synthetic and one real-world Twitter dataset show that for both priors CEM-* can generate a posterior distribution of graphs that explains the whole trace while being closer to the ground truth. As an additional benefit, the use of the SBM prior infers and clusters users simultaneously during optimization. CEM-* outperforms baseline and state-of-the-art methods in terms of feasibility, run-time, and precision of the inferred graph and communities. Finally, we propose a heuristic to adapt the inference to lower feasibility requirements and show how it can affect the precision of the result.

A. Tay, A. Riley, Rashidul Islam et al.

Abstract Aims Despite the magnitude and protracted nature of the Rohingya refugee situation, there is limited information on the culture, mental health and psychosocial wellbeing of this group. This paper, drawing on a report commissioned by the United Nations High Commissioner for Refugees (UNHCR), aims to provide a comprehensive synthesis of the literature on mental health and psychosocial wellbeing of Rohingya refugees, including an examination of associated cultural factors. The ultimate objective is to assist humanitarian actors and agencies in providing culturally relevant Mental Health and Psychosocial Support (MHPSS) for Rohingya refugees displaced to Bangladesh and other neighbouring countries. Methods We conducted a systematic search across multiple sources of information with reference to the contextual, social, economic, cultural, mental health and health-related factors amongst Rohingya refugees living in the Asia-Pacific and other regions. The search covered online databases of diverse disciplines (e.g. medicine, psychology, anthropology), grey literature, as well as unpublished reports from non-profit organisations and United Nations agencies published until 2018. Results The legacy of prolonged exposure to conflict and persecution compounded by protracted conditions of deprivations and displacement is likely to increase the refugees' vulnerability to wide array of mental health problems including posttraumatic stress disorder, anxiety, depression and suicidal ideation. High rates of sexual and gender-based violence, lack of privacy and safe spaces and limited access to integrated psychosocial and mental health support remain issues of concern within the emergency operation in Bangladesh. Another challenge is the limited understanding amongst the MHPSS personnel in Bangladesh and elsewhere of the language, culture and help-seeking behaviour of Rohingya refugees. While the Rohingya language has a considerable vocabulary for emotional and behavioural problems, there is limited correspondence between these Rohingya terms and western concepts of mental disorders. This hampers the provision of culturally sensitive and contextually relevant MHPSS services to these refugees. Conclusions The knowledge about the culture, context, migration history, idioms of distress, help-seeking behaviour and traditional healing methods, obtained from diverse sources can be applied in the design and delivery of culturally appropriate interventions. Attention to past exposure to traumatic events and losses need to be paired with attention for ongoing stressors and issues related to worries about the future. It is important to design MHPSS interventions in ways that mobilise the individual and collective strengths of Rohingya refugees and build on their resilience.

Alexandros Efstratiou, Emiliano De Cristofaro

Previous work suggests that people's preference for different kinds of information depends on more than just accuracy. This could happen because the messages contained within different pieces of information may either be well-liked or repulsive. Whereas factual information must often convey uncomfortable truths, misinformation can have little regard for veracity and leverage psychological processes which increase its attractiveness and proliferation on social media. In this review, we argue that when misinformation proliferates, this happens because the social media environment enables adherence to misinformation by reducing, rather than increasing, the psychological cost of doing so. We cover how attention may often be shifted away from accuracy and towards other goals, how social and individual cognition is affected by misinformation and the cases under which debunking it is most effective, and how the formation of online groups affects information consumption patterns, often leading to more polarization and radicalization. Throughout, we make the case that polarization and misinformation adherence are closely tied. We identify ways in which the psychological cost of adhering to misinformation can be increased when designing anti-misinformation interventions or resilient affordances, and we outline open research questions that the CSCW community can take up in further understanding this cost.

E. Erokhina

The article problematizes the possibility of replicating unique scientific and educational innovations in the institutional space of Russian society on the example of referring to the creative biography of Lyudmila Glebovna Borisova and her scientific sociological school. The methodology is based on the concept of the diversity of the transition to modernity by S. Eisenstadt; the method of researching scientific schools in the context of the relationship between the structure of science itself and the social problems of society, of which scientific institutions are a part; generational approach, biographical method and smart grid research method. The empirical base of the research is based on the documents of Lyudmila Glebovna Borisova from the Open Archive of the SB RAS: 10 office documentation, materials of personal origin, scientific publications. The key milestones in the biography of L.G. Borisova in the context of the institutional transformations of science and education of the late USSR, the development of the Novosibirsk Scientific Center (NSC); the history of the formation of sociological schools in the Novosibirsk Academgorodok is shown, the features of one of them, the school of sociology of education, are revealed. The characteristic of a special, selfless type of the Russian scientist is given. The history of the successes and failures of Lyudmila Glebovna Borisova is shown against the background of social changes in society and its institutions. In the context of the late USSR, the development of the scientific school of the sociology of education was influenced by the personality of L.G. Borisova, an ascetic scientist who underwent primary professional socialization in a pedagogical team with an ethos-oriented orientation, containing the ideas of humanism, the unity of word and deed, public service, and equality of interests between the elders and the younger. This ethos she conveyed in relationships with students and colleagues. The new stage of reforms significantly reduced the autonomy of professional communities of scientists and teachers, narrowed the base for recruiting scientific personnel in science and pedagogy, and increased the alienation of professionals from decision-making. In the changed conditions, her departure was irreparable for the scientific school.

Paul van Trigt

Dian Ridlo Pamuji, Galang Sandy Prayogo, Mohammad Nur Shodiq

Tahu adalah makanan yang berbahan utama kedelai, dan juga merupakan makanan favorit masyarakat Indonesia baik kalangan bawah sampai kalangan atas. Selain harganya murah, tahu mengandung air 86 %, protein 8-12%, lemak 4-6% dan karbohidrat 16%. Tahu juga mengandung berbagai mineral seperti kalsium, zat besi, fosfat, kalium, natrium; serta vitamin seperti kolin, vitamin B dan vitamin E. Mengingat semakin meningkatnya harga kebutuhan pokok yang ada sekarang ini, banyak masyarakat yang melakukan usaha kecil menengah demi memenuhi kebutuhan pokok tersebut. Salah satunya adalah dengan usaha produksi tahu. Sekarang banyak sekali ditemukan usaha kecil menengah masyarakat yang memproduksi tahu, salah satunya adalah di Dusun Timurejo Desa Gitik Kecamatan Rogojampi Kabupaten banyuwangi. Besar kecilnya kapasitas produksi usaha produksi tahu ditentukan pada saat pengepresan dan pemotongan tahu. Dengan semakin banyaknya hasil pengepresan dan pemotongan tahu dengan waktu yang singkat, maka tahu yang dihasilkannya pun semakin banyak. Saat ini proses pengepresan dan pemotongan tahu yang dilakukan oleh usaha mikro kecil menegah (UMKM) Produksi Tahu Desa Gitik selama ini masih secara manual dengan menggunakan tenaga manusia dan menggunakan alat-alat yang masih sangat tradisional. Berdasarkan hasil diskusi dan identifikasi masalah bersama mitra, mitra sangat membutuhkan alat atau mesin yang dapat memudahkan dan mempercepat proses pengepresan dan pemotongan tahu. Tahap awal kegiatan pengabdian ini adalah melakukan survey untuk mengidentifikasi permasalahan yang dihadapi oleh mitra dan melakukan studi literatur untuk mendapatkan solusi atas permasalahan mitra. Setelah solusi permasalahan mitra didapatkan, langkah selanjutnya melakukan perancangan dan pembuatan komponen-komponen alat pengepres dan pemotong tahu semi otomatis. Alat yang dibuat dapat membantu masyarakat dalam meningkatkan produktivitas produksi tahu dibandingkan dengan proses manual atau tradisional. Selain itu, dengan adanya alat ini waktu produksi dapat dipersingkat dan pendapatan masyarakat meningkat.

Miguel Lara Castro, Yessica Bautista Bautista, Rosa María Woo García et al.

La fotocatálisis es una reacción química inducida por la absorción de un material sólido, o fotocatalizador. La excitación del sólido desencadena dos reacciones que conducen a la formación casi instantánea de radicales hidroxilos y aniones superóxido (llamadas especies reactivas de oxígeno; ROS). Los ROS producen daño oxidativo en diversos microorganismos incluyendo al virus SARS-CoV2, favoreciendo la desintegración de la conformación proteica de la cápside, cambios en la permeabilidad y daños de la membrana del virión que finalmente conduce a rotura del ADN, sin la oportunidad de reparación. Incluso, la reacción fotocatalítica causa la degradación oxidativa contra materiales peligrosos orgánicos y/o inorgánicos en el aire para convertirlos en sustancias no dañinas como agua o dióxido de carbono.

V. V. Viennikova, I. Kolosov

Paper proposed highlights the experience of Qatar's labor law reform, its features, peculiarities of the countries of the Muslim Legal family taking into account. Mainly directions of aforesaid reform and structural improvements in the legal regulation of Labor Relations in comparison with the pre-reform period are determined. A comparative study with the relevant directions of industry reform in Ukraine was conducted. Similar and distinctive features, advantages and disadvantages of both systems are analyzed. Conclusions about the possibility of borrowing positive foreign experience into the domestic labor and legal reality were showed. Studying of Labor Relations legal regulation experience in the Middle East on the example of Qatar permit to encourage colleagues to put out a scientific discussion about such types of employment contract as educational and service ones, its core conditions, consider the proposals of the trade union movement within the framework of joint committees, outline the problems of sponsorship law and repatriation in connection with subject of Labor Law, discuss problems and apply positive experience in regulating the work of home-based workers, consider the possibility of introducing the institute of anonymous complaints in labor law, pay attention to the experience of creation a labor justice system. Special attention should be paid to a physical attack on the employer or direct supervisor as reasons for termination of the employment contract at the initiative of the employer. Simultaneously, Domestic system of labor law, although it is distinguished by more long-timed traditions of statutory guarantees in field of Labor and Social Security Law, is not without the need to borrow foreign experience in order to update it for the needs of modern social development, which should be devoted to furthermore comparative legal researches.

Juan Pablo de Vicente, Alvaro Soto

Current datasets to train social behaviors are usually borrowed from surveillance applications that capture visual data from a bird's-eye perspective. This leaves aside precious relationships and visual cues that could be captured through a first-person view of a scene. In this work, we propose a strategy to exploit the power of current game engines, such as Unity, to transform pre-existing bird's-eye view datasets into a first-person view, in particular, a depth view. Using this strategy, we are able to generate large volumes of synthetic data that can be used to pre-train a social navigation model. To test our ideas, we present DeepSocNav, a deep learning based model that takes advantage of the proposed approach to generate synthetic data. Furthermore, DeepSocNav includes a self-supervised strategy that is included as an auxiliary task. This consists of predicting the next depth frame that the agent will face. Our experiments show the benefits of the proposed model that is able to outperform relevant baselines in terms of social navigation scores.