Hasil untuk "Social sciences and state - Asia (Asian studies only)"

Shiori Furukawa, Sho Tsugawa

Although beneficial information abounds on social media, the dissemination of harmful information such as so-called ``fake news'' has become a serious issue. Therefore, many researchers have devoted considerable effort to limiting the diffusion of harmful information. A promising approach to limiting diffusion of such information is link deletion methods in social networks. Link deletion methods have been shown to be effective in reducing the size of information diffusion cascades generated by synthetic models on a given social network. In this study, we evaluate the effectiveness of link deletion methods by using actual logs of retweet cascades, rather than by using synthetic diffusion models. Our results show that even after deleting 10\%--50\% of links from a social network, the size of cascades after link deletion is estimated to be only 50\% the original size under the optimistic estimation, which suggests that the effectiveness of the link deletion strategy for suppressing information diffusion is limited. Moreover, our results also show that there is a considerable number of cascades with many seed users, which renders link deletion methods inefficient.

Dr. Amjad Zarin, Dr. Zafar Hussain

Climate change poses a critical challenge to South Asia, a region highly vulnerable to climate extremes, rising temperatures, water scarcity, and sea level rise. Despite the urgency of these issues, gaps in public knowledge and institutional responses remain, largely due to the inadequate media coverage and limited scientific literacy. This paper investigates the role of climate journalism in South Asia, focusing on the ways media coverage or the lack thereof affects public awareness and climate change adaptation efforts. The study explores the state of climate change reporting across Pakistan, India, Bangladesh, Nepal, and Sri Lanka, highlighting regional challenges in media coverage, such as event-based reporting, limited technical knowledge, and economic constraints. Media in the region often fails to address the long-term and systematic nature of climate issues, instead focusing on immediate events or political concerns, thus hindering a deeper public understanding of climate science and policy. The paper also delves into the changing dynamics of climate journalism in the context of South Asia’s unique media landscape, examining the organizational and structural challenges faced by the journalists. It discusses the influence of political, economic, and social factors on the framing of climate stories, and the resulting implications for the climate policy and public engagement. By conducting a content analysis of environmental reporting in regional print media, this study identifies key gaps in the coverage of climate change, especially the underreporting of local environmental issues and the broader systemic impacts. The research contributes valuable insights into how media can better support climate change mitigation and adaptation strategies in South Asia, promoting more informed and inclusive responses to one of the most pressing global challenges.

Sho Tsugawa, Hiroyuki Ohsaki

In this paper, we address the challenge of discovering hidden nodes in unknown social networks, formulating three types of hidden-node discovery problems, namely, Sybil-node discovery, peripheral-node discovery, and influencer discovery. We tackle these problems by employing a graph exploration framework grounded in machine learning. Leveraging the structure of the subgraph gradually obtained from graph exploration, we construct prediction models to identify target hidden nodes in unknown social graphs. Through empirical investigations of real social graphs, we investigate the efficiency of graph exploration strategies in uncovering hidden nodes. Our results show that our graph exploration strategies discover hidden nodes with an efficiency comparable to that when the graph structure is known. Specifically, the query cost of discovering 10% of the hidden nodes is at most only 1.2 times that when the topology is known, and the query-cost multiplier for discovering 90% of the hidden nodes is at most only 1.4. Furthermore, our results suggest that using node embeddings, which are low-dimensional vector representations of nodes, for hidden-node discovery is a double-edged sword: it is effective in certain scenarios but sometimes degrades the efficiency of node discovery. Guided by this observation, we examine the effectiveness of using a bandit algorithm to combine the prediction models that use node embeddings with those that do not, and our analysis shows that the bandit-based graph exploration strategy achieves efficient node discovery across a wide array of settings.

S. O. Adekalu, Lami Sunday, Ismaila Muhammed et al.

Examination malpractice poses significant challenges to most institutions of higher learning, particularly those from economically disadvantaged countries. Despite the plethora of studies that have been conducted on malpractices, few investigations have been conducted with a diverse, non-Asian sample of students in an attempt to understand the preferred malpractice styles and how they are perpetrated during examination periods. In response, surveys were administered to 120 undergraduate students from diverse Nigerian backgrounds studying allied health science courses and affiliated degree programs in Enugu State, Nigeria. Most respondents were female (78, 65.0%) and Christian students (110, 91.7%) aged 17 to 25 years. The results showed that (61, 51.0%) were admitted to the use of unwanted materials, (28, 23.3%) whispering of answers, (19, 15.8%) writing on part of the body, (7, 5.8%) unauthorized device, (4, 3.3%) financial inducement of official, and (1, 0.8%) in-personation as their preferred malpractice styles during examination. The study recommends, among others, effective ‘management’ of students’ examination supervision, strict enforcement of anti-malpractice policies, and infrastructural development in Nigerian universities. Most importantly, there should be a convincing leadership will on the part of the university management to conduct staff audits and employ qualified, licensed, and practicing school social workers to adequately manage examination sensitization and counseling interventions that will help in reducing the dishonest behavior of students. Implications for future research are also discussed.

Y. Illiashenko, A.I. Lysenko

The article highlights the significance of the institutionalization of world history research in contemporary Ukraine. This process is exemplified by the State Institution “Institute of World History of the National Academy of Sciences of Ukraine”, which stands as a leading academic center for the systemic and comprehensive study of global historical development from ancient times to the present day. The multifaceted activities of the Institute are thoroughly characterized, underscoring its pivotal role in the institutionalization of world history within domestic academia. The systematic approach of the Institute in studying world history is evident, as its research encompasses a vast spectrum of issues related to the historical development of European, Asian, African, North American, and South American regions, including their civilizational peculiarities and interdependencies from the perspective of global studies and transcontinental interaction. The authors focus on the Institute’s active research and publishing endeavors. Notably, the establishment of the journal «Problems of World History» has created opportunities for direct coordination of world history studies in Ukraine. Furthermore, the Institute publishes collections of scholarly works, monographs, analytical notes, and encyclopedias, covering a wide range of global historical topics. It is emphasized that the Institute serves as a stable platform for training academic staff in the field of world history through the functioning of a specialized academic council. This ensures open access to dissertation research for scholars and the public. The article also argues for the importance of the Institute’s active implementation of digital tools (an informative official website, an electronic scholarly library, and a YouTube videoblog) to promote academic achievements in world history. It is confirmed that the Institute not only systematizes the study of global historical processes but also actively shapes the institutional environment for the development of academic personnel, ensures the openness of scholarly data, and contributes to the integration of Ukrainian historiography into the global academic space.

Mélanie Sadozaï

This article assesses how the five Central Asian republics are covered in the field of English-language border studies. It features the social science literature which places one or multiple borders at the core of their study. I argue that the work on borders by scholars of Central Asia is not only well located in border studies debates but that it also contributes to renewing it. By reviewing 76 references of research works dealing with Central Asian borders, I contend that those are not peripheral examples of larger epistemological conversations of the field but an integral and legitimate part of it. This article is an attempt to establish a state of the art of borders in the region and could serve scholars interested in informing dominant concepts and theories of border studies or to position their own research in the existing literature.

Masahiro Suzuki, Sho Sagara, Nozomi Yamawaki et al.

Anuratha Rajasegaram, S. Kumaran, Paran Gani

Environmental injustice has emerged as a defining yet under-examined dimension of rapid development in Southeast Asia. This study critically analyses how pollution burdens are unevenly distributed across socio-economic groups, with low-income and marginalised communities experiencing disproportionate exposure to hazardous air, water, and land contamination. Drawing on regional evidence and country-level case studies, the analysis situates environmental harm within historical legacies of colonial urban planning, post-colonial industrialisation, and contemporary governance failures. Pollution exposure is shown to be shaped not merely by proximity to industrial or infrastructural sources, but by entrenched inequalities in land tenure, political representation, regulatory enforcement, and access to public services. Low-income communities are systematically positioned within high-risk environments through informal settlement patterns, weak zoning regulations, and uneven state investment, while simultaneously lacking institutional capacity to contest these arrangements. The findings highlight how environmental injustice in Southeast Asia operates through a multi-vector pollution framework in which air, water, and land contamination intersect with labour precarity, inadequate sanitation, and transboundary environmental flows. Health impacts, including respiratory illness, waterborne disease, and toxic exposure, are concentrated among populations already burdened by poverty, social exclusion, and limited healthcare access. The study further demonstrates that existing policy responses often prioritise technological fixes and economic growth over distributive equity, failing to address cumulative exposure and structural vulnerability. By integrating environmental justice theory with regional political-economic analysis, this study argues that addressing pollution in Southeast Asia requires not only environmental regulation but transformative governance reforms, participatory planning, and rights-based approaches that centre affected communities as key agents of change rather than passive victims of development.

Haiko Lietz

Social Network Analysis is a way of studying agents embedded in contexts. In about 1998, physicists discovered social networks as representations of complex systems. Small-world and scale-free networks are the paradigmatic models of this Network Science. Relying on various models and mechanisms of socio-cultural processes, an identity model is developed and calibrated in a case study of Social Network Science. This research domain results from the union of Social Network Analysis and Network Science. A unique dataset of 25,760 scholarly articles from one century of research (1916-2012) is created. Clustering this set of publications, five subdomains are detected and analyzed in terms of authorship, citation, and word usage structures and dynamics. The scaling hypothesis of percolation theory is formulated for socio-cultural systems, namely that power-law size distributions like Lotka's, Bradford's, and Zipf's Law mean that the described identity resides at the phase transition between the stability and change of meaning. In this case, it can be diagnosed using bivariate scaling laws and Abbott's heuristic of fractal distinctions. Identities are not dichotomies but dualities of social network and cultural domain, micro and macro phenomena, as well as stability and change. Story sets that give direction to research fluctuate less, are less distinctive, and more inert than the individuals doing the research. Identities are scale-free. Six senses are diagnostic of different aspects of identity, and when they come together as process, a complex socio-cultural system comes into existence. A mutual benefit that results from mating Relational Sociology and Network Science is identified. The latter can learn from the former that social systems are dualities of transactions and meaning. For the social sciences, the importance of Paretian thinking (scale invariance) is pointed out.

Ori Swed, Sachith Dassanayaka, Dimitri Volchenkov

In 2016, a network of social media accounts animated by Russian operatives attempted to divert political discourse within the American public around the presidential elections. This was a coordinated effort, part of a Russian-led complex information operation. Utilizing the anonymity and outreach of social media platforms Russian operatives created an online astroturf that is in direct contact with regular Americans, promoting Russian agenda and goals. The elusiveness of this type of adversarial approach rendered security agencies helpless, stressing the unique challenges this type of intervention presents. Building on existing scholarship on the functions within influence networks on social media, we suggest a new approach to map those types of operations. We argue that pretending to be legitimate social actors obliges the network to adhere to social expectations, leaving a social footprint. To test the robustness of this social footprint we train artificial intelligence to identify it and create a predictive model. We use Twitter data identified as part of the Russian influence network for training the artificial intelligence and to test the prediction. Our model attains 88% prediction accuracy for the test set. Testing our prediction on two additional models results in 90.7% and 90.5% accuracy, validating our model. The predictive and validation results suggest that building a machine learning model around social functions within the Russian influence network can be used to map its actors and functions.

Dmitry Maidachevsky

The article on the example of the Eastern Department of External Relations of the Faculty of Social Sciences of Irkutsk State University, which existed in 1921–1924, considers a forgotten, and perhaps simply ignored by historiography, attempt to build in the early Soviet period in domestic science and the formation of the disciplinary field of international relations. The study focuses on considering the form that international relations have taken as a field of study and teaching, influenced both by social, explaining the history of its formation, and by intellectual factors that define and reflect the internal dynamics of the emerging disciplinary field. The latter in the case considered in the article developed in the process of interaction between international law and the history of international relations with oriental studies, which set the object of study — the interaction of the countries of the Far East (Northeast Asia) with the leading powers of the world and/or with each other. Disciplinary identity (objectivity, specialization) of the field was ensured by relying on Marxist political and economic methodological foundations common to its disciplines, as well as the theoretical concept of imperialism/colonialism (international political economy). Beginning in the second half of the 1920s. radical transformations in the study and teaching of social sciences sharply cut short not only the institutionalization of international relations as a promising area of social knowledge, but also the whole line for its construction on the basis of creative, academic Marxism, giving rise to infertility, which it still suffers.

H. V. Luong

In the context of accelerating globalization as well as a shifting theoretical landscape in the social sciences and the humanities, this article examines the recent greater attention to the state and global forces, including the global neoliberal ideology, in Asian studies. Empirically, the article examines the resilient roles of family members and relatives in childcare and elderly care in Vietnam and many other parts of East and Southeast Asia, as well as the related trend of relatively low public social expenditures in most East and Southeast Asian societies. The long-standing ideology of familialism, which underlies the pattern of care for the young and elderly in Vietnam and many Asian societies, shapes state policies and exerts an impact on global capitalist operations in Vietnam, notwithstanding the acceleration of globalization, the global neoliberal ideology, and the strong power of the Vietnamese communist party-state. This article suggests that the relation between the local sociocultural landscape, state policies, and global forces involves a dialogic process.

Malashri Lal

Indra Kusumawardhana, Gustin Saptarani Dewi

The Timor Gap had been a hotspot of territorial dispute between Australia and Timor-Leste. In 2018, Australia finally agreed to settle a permanent maritime boundary in favour of Timor-Leste. Why was Australia willing to sacrifice the border and give a favourable outcome to Timor-Leste? The research examined the importance of the tripartite approach to Foreign Policy analysis to understand why a country may choose seemingly unfavourable options in territorial disputes. The analysis showed how Australian foreign policy was influenced by agency-structure interactions within the international system. The research demonstrated that structural constraints at the international level influenced Australia’s decision, including the South China Sea dispute between ASEAN members and China, previous agreements Australia-Timor-Leste on the management of the Timor Gap, and domestic political dynamics in Australia. The research reveals a relationship between actors’ structural and dispositional dimensions in foreign policy. In the case of Australia, there is a strong link between democratic values ​​and respect for the international rules-based order. Altogether, this situation prompted Australia to continue negotiations with Timor-Leste over the Timor Gap and ultimately to accept an agreement for maritime delimitation in Timor-Leste’s favor.

Wenwen Li

GeoAI, or geospatial artificial intelligence, is an exciting new area that leverages artificial intelligence (AI), geospatial big data, and massive computing power to solve problems with high automation and intelligence. This paper reviews the progress of AI in social science research, highlighting important advancements in using GeoAI to fill critical data and knowledge gaps. It also discusses the importance of breaking down data silos, accelerating convergence among GeoAI research methods, as well as moving GeoAI beyond geospatial benefits.

Marcelo Sartori Locatelli, Pedro Calais, Matheus Prado Miranda et al.

Politicization is a social phenomenon studied by political science characterized by the extent to which ideas and facts are given a political tone. A range of topics, such as climate change, religion and vaccines has been subject to increasing politicization in the media and social media platforms. In this work, we propose a computational method for assessing politicization in online conversations based on topic shifts, i.e., the degree to which people switch topics in online conversations. The intuition is that topic shifts from a non-political topic to politics are a direct measure of politicization -- making something political, and that the more people switch conversations to politics, the more they perceive politics as playing a vital role in their daily lives. A fundamental challenge that must be addressed when one studies politicization in social media is that, a priori, any topic may be politicized. Hence, any keyword-based method or even machine learning approaches that rely on topic labels to classify topics are expensive to run and potentially ineffective. Instead, we learn from a seed of political keywords and use Positive-Unlabeled (PU) Learning to detect political comments in reaction to non-political news articles posted on Twitter, YouTube, and TikTok during the 2022 Brazilian presidential elections. Our findings indicate that all platforms show evidence of politicization as discussion around topics adjacent to politics such as economy, crime and drugs tend to shift to politics. Even the least politicized topics had the rate in which their topics shift to politics increased in the lead up to the elections and after other political events in Brazil -- an evidence of politicization.

Loukas Ilias, Dimitris Askounis

Stress and depression are prevalent nowadays across people of all ages due to the quick paces of life. People use social media to express their feelings. Thus, social media constitute a valuable form of information for the early detection of stress and depression. Although many research works have been introduced targeting the early recognition of stress and depression, there are still limitations. There have been proposed multi-task learning settings, which use depression and emotion (or figurative language) as the primary and auxiliary tasks respectively. However, although stress is inextricably linked with depression, researchers face these two tasks as two separate tasks. To address these limitations, we present the first study, which exploits two different datasets collected under different conditions, and introduce two multitask learning frameworks, which use depression and stress as the main and auxiliary tasks respectively. Specifically, we use a depression dataset and a stressful dataset including stressful posts from ten subreddits of five domains. In terms of the first approach, each post passes through a shared BERT layer, which is updated by both tasks. Next, two separate BERT encoder layers are exploited, which are updated by each task separately. Regarding the second approach, it consists of shared and task-specific layers weighted by attention fusion networks. We conduct a series of experiments and compare our approaches with existing research initiatives, single-task learning, and transfer learning. Experiments show multiple advantages of our approaches over state-of-the-art ones.

D. Cherian

Abstract Historians of Islamic occult science and post-Mongol Persianate kingship in the Ottoman, Safavid, and Mughal Empires have in recent years made clear just how central this body of knowledge was to the exercise of imperial power. Alongside, scholarship on tantra has pointed to its diffuse persistence in the early modern period. But what dynamics beyond courts and elite initiates did these investments in occult science and tantra unleash? Through a focus on the seventeenth-century Mughal court and the Rajput polity of Marwar in the eighteenth century, this article weaves together the history of animals with that of harmful magic by non-courtly actors. It demonstrates the blended histories of tantra, Islamicate occult sciences, and folk magic to argue that attributions of liminality encoded people, animals, and things with occult potential. For some, like the owl, this liminality could invite violence and death and for others, like expert male practitioners, it could generate authority. By the eighteenth century, the deployment of practical magic towards harmful or disruptive ends was a political tool wielded not only by kings and elite adepts for state or lineage formation but also by non-courtly subjects and “low”-caste specialists in local social life. States and sovereigns responded to the popular use of harmful magic harshly, aiming to cut off non-courtly access to this resource. If the early modern age was one of new ideologies of universal empire, the deployment of occult power outside the court was inconsistent with the ambitions of the kings of this time.

Phathara-on Wesarat, Rudsada Kaewsaeng‐on, Daranat Tansui et al.

Educational standards are extremely important to educational sector worldwide because they could be used to ensure that all students attain their educational goals. To reach high educational standards, expected learning outcomes should not only be clear, measurable, and achievable, but also should reflect the needs of stakeholders. This could assist students to achieve employability. The purpose of this paper is to develop expected learning outcomes for the Bachelor of Business Administration Program, Faculty of Humanities and Social Sciences, Prince of Songkla University (Pattani Campus), Thailand (a developing country in Southeast Asia). The development of expected learning outcomes is in accordance with the concept of outcome based education and international standards of education (such as the ASEAN University Network Quality Assurance and the Association to Advance Collegiate Schools of Business). This study collected data from the participants who were core stakeholders and non-core stakeholders using the questionnaire with open-ended questions. The categorization of stakeholders into two groups was based on the criterion used in this study. Qualitative method was adopted to thematically categorize and analyze the data. This study found that there were nine items of expected learning outcomes for the Bachelor of Business Administration Program. These expected learning outcomes included generic outcomes and subject specific outcomes that could be used to guide teaching and learning approach as well as student assessment of the program. Since the expected learning outcomes developed in this study were based on stakeholders’ needs of the Bachelor of Business Administration Program located in Southernmost Thailand, they may not be generalized to other educational programs or other regions.

Lucas Skora, Helen Senefonte, Myriam Delgado et al.

A better understanding of the behavior of tourists is strategic for improving services in the competitive and important economic segment of global tourism. Critical studies in the literature often explore the issue using traditional data, such as questionnaires or interviews. Traditional approaches provide precious information; however, they impose challenges to obtaining large-scale data, making it hard to study worldwide patterns. Location-based social networks (LBSNs) can potentially mitigate such issues due to the relatively low cost of acquiring large amounts of behavioral data. Nevertheless, before using such data for studying tourists' behavior, it is necessary to verify whether the information adequately reveals the behavior measured with traditional data -- considered the ground truth. Thus, the present work investigates in which countries the global tourism network measured with an LBSN agreeably reflects the behavior estimated by the World Tourism Organization using traditional methods. Although we could find exceptions, the results suggest that, for most countries, LBSN data can satisfactorily represent the behavior studied. We have an indication that, in countries with high correlations between results obtained from both datasets, LBSN data can be used in research regarding the mobility of the tourists in the studied context.