Social Trends Research Articles

Natural resource rents and public spending on education in Africa: Does women's political empowerment matter?

The increase in the number of women in political office is one of the most significant social trends of recent decades. Although still underrepresented, women's participation in decision-making bodies is increasing. This paper analyzes the moderating effect of women's political empowerment on the relationship between natural resource rents and public spending on education in a sample of 47 African countries over the period 2003–2020. This study employs several recent methods to effectively address the endogeneity issue, including the Generalized Method of Moments in System (GMM-S) and the Two-stage Instrumental Variables (2SIV) approach. Overall, the results show that natural resource rents reduce public spending on education, but their interaction with the index of women's political empowerment in composite and disaggregated form increases public spending on education in Africa. These results are tested at four levels of robustness, including the inclusion of additional control variables, the exclusion of outliers, and the use of alternative dependent and independent variables. We suggest improving the representation of women in African political decision-making. This could include quotas for women in decision-making bodies, mentoring programs for women leaders, and financial incentives for political parties that promote women's participation. Steps must also be taken to address structural barriers that prevent women from fully participating in political life, such as discrimination and violence against women.

Glocalization: an analysis into it’s conceptual and strategic underpinnings

Glocalization is a “simultaneity—the co-presence—of both universalizing and particularizing tendencies” emphasizing the need for tempering the effects of local conditions on global pressures. While the increasing presence of best-known fast food chain restaurants worldwide such as McDonald’s and KFC is a manifestation of globalization, the shrewd and strategic adaptations of their menu to satiate the local palates and tastes by these “Glocal Enterprises” is illustrative of glocalization. Conversely, the chief point of glocalization perspective is: “even the most local ways of carrying out business operations are more and more co-constituted by economic and social trends that are most global.” Language has a huge role to play in addressing the cultural and linguistic barriers and designing a successful global talent management and language learning solution that is complemented by local support. When used as an extension of the “Think Global, Act Local” grassroots movement, glocalization also refers to market advantage of local businesses versus global companies. In the face of globalization, both the little guys and would-be entrepreneurs can emerge triumphant by tapping into their hometown markets and then scaling up. However, it is imperative that MNCs restructure the national economies to become and remain more resilient, sustainable, and inclusive in their globalization to glocalization migration odyssey. An attempt would be made in this conceptual Paper to address this issue—a challenge and an opportunity—for the key players by enumerating the stories of successful transition into glocalization by several popular Multi National Corporations in the Indian context.

Insights Unveiled: Harnessing AI to Explore Human Behaviour in Social Sciences

AI's evolution has expanded its potential to understand complex human behaviours, revealing new insights into human psychology and sociology. This essay explores AI's capabilities in detecting intricate behavioural patterns, its applications in social sciences, the challenges and ethical considerations associated with its use, and predictions for the future. AI's ability to uncover patterns invisible to the human mind offers an exciting frontier of exploration, particularly in understanding human behaviour. Human behaviour, characterized by its intricacy and influenced by sociocultural, economic, and psychological factors, has traditionally been studied through various methodologies. However, the unpredictability and dynamism of human behaviour often defy simple categorization or comprehension. AI has the potential to serve as a guide, decoding patterns beyond the reach of human cognition and traditional methodologies. AI can offer a new lens through which we view the rich tapestry of human experience, such as predicting social trends, understanding consumer behaviour, and exploring the underpinnings of political sentiment. Despite challenges such as feasibility, interpretability, and ethics, the potential impact of AI in understanding human behaviour is enormous. By shedding light on hidden patterns, we can foster a more nuanced understanding of our societies, inform policies, drive innovation, and potentially address some of the pressing challenges of our times.

Archaeobotanical data from the Sabor Valley reveal shifting moments in landscape and agriculture in NW Iberia during the Holocene

NW Iberia is dominated by Atlantic climate areas that favour pollen preservation, useful for palaeoecological studies. However, the region also includes Mediterranean sectors in which preservation of such palaeoenvironmental evidence is more difficult. To overcome these constraints, archaeological plant macroremains can be used to help characterize flora and vegetation dynamics at a local and regional level. To fill the gap in knowledge in an understudied Mediterranean region, a large archaeobotanical study was conducted at the river Sabor valley, NE Portugal. With 13 archaeological sites sampled for charcoal, fruits and seeds, it allowed the study of vegetation throughout the Holocene, starting in the Mesolithic up to Modern times, with some chronological gaps. Tree taxa dominates the older period and an expansion of shrubby taxa since Bronze age was observed. Diversification of plants used during the Iron Age and Roman period suggests an intensification of resources exploitation and deforestation. These trends seem to be related with changes in human settlements and productive strategies. During Prehistory, agricultural fields were established in flat and wide areas, and, during Iron Age, fortified granaries were used to store large amounts of grains, particularly free-threshing wheat. Drastic changes in settlement during Roman times and the establishment of small farms producing wine and/or olive oil were testified by the occurrence of Olea and Vitis in both anthracological and carpological datasets. Data from more recent periods is scarce. Results highlight that the combination of several proxies and integration of archaeological evidence helps to understand ecological dynamics in areas without pollen data and contributes to the characterization of heterogeneous areas under diverse climatic conditions and with a variety of social trends.

Enhanced Multi-Task Traffic Forecasting in Beyond 5G Networks: Leveraging Transformer Technology and Multi-Source Data Fusion

Managing cellular networks in the Beyond 5G (B5G) era is a complex and challenging task requiring advanced deep learning approaches. Traditional models focusing on internet traffic (INT) analysis often fail to capture the rich temporal and spatial contexts essential for accurate INT predictions. Furthermore, these models do not account for the influence of external factors such as weather, news, and social trends. This study proposes a multi-source CNN-RNN (MSCR) model that leverages a rich dataset, including periodic, weather, news, and social data to address these limitations. This model enables the capture and fusion of diverse data sources for improved INT prediction accuracy. An advanced deep learning model, the transformer-enhanced CNN-RNN (TE-CNN-RNN), has been introduced. This model is specifically designed to predict INT data only. This model demonstrates the effectiveness of transformers in extracting detailed temporal-spatial features, outperforming conventional CNN-RNN models. The experimental results demonstrate that the proposed MSCR and TE-CNN-RNN models outperform existing state-of-the-art models for traffic forecasting. These findings underscore the transformative power of transformers for capturing intricate temporal-spatial features and the importance of multi-source data and deep learning techniques for optimizing cell site management in the B5G era.

Tides of change: employee training strategies for promoting risk-taking tourism in the North Sea

PurposeThis study critically examines the transformative impact of the “North Sea TikTok” phenomenon on the marine tourism sector, emphasizing the role of employee training in fostering resilience and adaptability within marine economics and integrated marine systems. It delves into how viral social media trends influence marine tourism destinations, particularly the North Sea, affecting local economies, marine resource management and tourism strategies. By analyzing this trend, the paper seeks to uncover how marine tourism destinations can effectively respond to the challenges and opportunities presented by digital media-driven tourism.Design/methodology/approachEmploying a multidisciplinary framework that merges insights from digital marketing, risk perception in tourism and human resource management, this paper provides a comprehensive qualitative analysis of the “North Sea TikTok” trend. Through a meticulous content analysis of viral videos and an examination of user engagement metrics, alongside a thorough review of contemporary literature in marine tourism and sustainability, the study unpacks the far-reaching implications of social media on marine tourism ecosystems.FindingsThe analysis reveals that the “North Sea TikTok” trend has markedly altered public perceptions of the North Sea, catalyzing a shift toward adventure and risk-taking tourism. This pivot promises economic rejuvenation for local tourism sectors and necessitates agile marine management strategies to accommodate the evolving demands. Implementing innovative employee training programs focusing on safety protocols, environmental conservation and digital engagement is central to managing these dynamics. The paper emphasizes integrating sustainable practices to ensure the equitable growth of marine tourism economies and environmental preservation.Originality/valueThis paper pioneers exploring the nexus between social media trends and their operational and strategic impacts on marine tourism management and economics. Synthesizing social media's viral dynamics with marine tourism development introduces groundbreaking insights into adapting marine tourism strategies in the digital age. It emphasizes the critical need for a skilled workforce capable of navigating the complexities of digital trend-driven tourism markets, proposing a novel model for employee training that aligns with the shifting paradigms of marine tourism engagement. This unique contribution advances academic discourse in marine economics and provides practical frameworks for stakeholders aiming to harness social media trends for sustainable tourism development.

Pedagogical Representation of Modern Childhood Image in the Context of Social Development Trends

Pedagogical Representation of Modern Childhood Image in the Context of Social Development Trends

Artifical intelligence in surgery: ethical considerations in the light of social trends in the perception of health and medicine.

The use of artificial intelligence (AI) in medicine and surgery is currently predicted to be very promising. However, AI has the potential to change the doctor's role and the doctor-patient relationship. It has the potential to support people's desires for health, along with the potential to nudge or push people to behave in a certain way. To understand these potentials, we must see AI in the light of social developments that have brought about changes in how medicine's role, in a given society, is understood. The trends of 'privatisation of medicine' and 'public-healthisation of the private' are proposed as a contextual backdrop to explain why AI raises ethical concerns different from those previously caused by new medical technologies, and which therefore need to be addressed specifically for AI.

Using Facebook to Recruit Urban Participants for Smartphone-Based Travel Surveys

Social media has become an integral part of everyday life for many individuals, serving as a platform to express opinions, share memories and lifestyles, follow news, and adapt to social trends and norms. The wealth of user information and analytics on these platforms has facilitated the development and sale of tailored products and services, benefiting advertisers and researchers seeking survey participants. Social media advertising has demonstrated its effectiveness in reaching hard-to-reach populations. However, transport researchers have yet to capitalise on this potential fully. This paper presents our experience using social media to recruit participants for two smartphone travel surveys conducted in Australia. We demonstrate that social media recruitment and smartphone-based travel surveys are highly effective, adaptable, and can be rapidly deployed in response to research opportunities, such as during the early phase of the COVID-19 pandemic when traditional methods may be less suitable. This approach also holds great potential for travel surveys targeting the general population. This paper shares several lessons from this experiment, including our administrative approach and detailed technical instructions to utilise open-source software tools for conducting smartphone travel surveys like ours. This approach significantly reduces study costs compared to most commercial solutions.

Social and Seasonal Organisation of Red Deer Hunting from the Neolithic to the Late Iron Age (c. 2000 BC to AD 1000)

This is the first paper to examine social and seasonal organization of red deer hunting using stone-set hunting blinds in Norway. The paper examines seven hunting blinds discovered in Gjesdal, western Norway. Four of the hunting blinds are unique; it was possible to date them directly with radiocarbon dating. The sites exhibit multiple construction phases, with a usage period ranging from the Neolithic to the Mid Iron Age, and we would suggest likely extending into the Late Iron Age and Middle Ages. The datings and multiple phases make it possible to discuss temporal change in the construction of the hunting blinds, which is unprecedented in a Fennoscandian context. Hunting appears to align with social trends, becoming more prominent during periods of settlement decline and increased use of outfield resources for surplus production. While hunting in the lowlands of western Norway, particularly between 0 and 900 metres above sea level, appears to have been smaller in scale compared to mass-scale hunting in Norway’s high-altitude zones and eastern regions, the high population of red deer until about 500 years ago indicates profitable hunting opportunities during specific seasons. The cluster of hunting blinds suggests organized cooperation among neighbours and families, with surplus products potentially sold and exported to local and regional markets.

Analysis of Network Public Opinion from the Perspective of Social Psychology

Online public opinion refers to the behavior of individuals or groups of people discussing, commenting, and expressing their views on a particular topic or event on the Internet through various forms of social media. With the popularity of the Internet and the rise of social media, online public opinion plays an important role in today’s society. It is not only an important channel for information dissemination but also an influence on social trends, public opinions, and values. Therefore, the analysis of network public opinion has important theoretical and practical significance.

Navigating the Digital Landscape: Unveiling Language Dynamics and Digital Identity among Indonesia’s Contemporary Generation

This research article investigates the impact of the Internet on language development and digital linguistics in Indonesia. It explores the search frequency and familiarity trends of Indonesian words and phrases, examining their connection to social change and identity. The study utilizes the Google Trend platform to collect data from 2018 to 2023, capturing the prevalence of the Indonesian language in Google searches. The research incorporates a comparative analysis of online data from social media, incorporating ethnographic interviews with 30 participants, and conducting a comprehensive lexicon survey. 77 Indonesian words and phrases are collected and analyzed, providing insights into familiarity patterns. Additionally, interviews and surveys are conducted with Indonesian university students to understand their attitudes towards language, its role in shaping identities, internet usage, and societal norms. The analysis focuses on 40 selected words, investigating their correlation with language patterns, identity formation, emotions, and societal conventions. The findings reveal how neologisms within Indonesia’s digital linguistic landscape reflect societal shifts, including contemporary events, social media trends, and societal pressures. The proliferation of trending words aligned with themes of identity, societal norms, and emotional well-being highlights the influence of social media and the Internet on language dissemination. These changes are deeply embedded in Indonesia’s digital linguistic milieu and are further elucidated through interviews, offering insights into internet users’ linguistic practices. The study emphasizes the importance of tracking language and societal trends for self-expression and integration into diverse communities. It also highlights the reciprocal relationship between self-identity and communal influence on language development. This research contributes to understanding language dynamics and digital identity in the Indonesian context, revealing the complex interplay between language, society, and individual perspectives.

Прогнозирование социальных изменений с помощью алгоритмов машинного обучения

This study is devoted to analyzing the capabilities of machine learning algorithms in the context of predicting social change. The main objective of the work is to evaluate the effectiveness and accuracy of various machine learning models, including artificial neural networks, decision trees and clustering methods, for analyzing so-cial data and predicting relevant trends. The research methodology includes data collection and preprocessing, training models based on selected algorithms, and evaluating their performance using standard metrics such as accuracy, completeness, and F1-measure. The results demonstrate that the application of machine learning can not only identify current social trends, but also predict future social changes with reasonable probability. The paper also discusses potential limitations related to data availability and quality, as well as ethical consid-erations for the use of algorithmic methods in the social sciences. It concludes by suggesting directions for fur-ther research, including improving the interpretability of models and enhancing multidisciplinary collaboration to better understand social processes.

First public dataset to study 2023 Turkish general election.

In the context of Turkiye's most recent parliamentary and presidential elections ("seçim" in Turkish), social media has played an important role in shaping public debate. It is of utmost importance to capture social media trends during the 2023 Turkish elections, since it uncovers a great deal of information of election propaganda, political debates, smear campaigns, and election manipulation by domestic and international actors. We provide a comprehensive dataset for social media researchers to study Turkish elections, develop tools to prevent online manipulation, and gather novel information to inform the public. We are committed to continually improving the data collection and updating it regularly leading up to the election. Using the #Secim2023 dataset, researchers can examine the social and communication networks between political actors, track current trends, and investigate emerging threats to election integrity. Our dataset and analysis code available through Harvard Dataverse and Github, respectively.

A Study on The Problematization of Logistics in Agricultural Production in The State of Tocantins

Objective: the research aims to describe the logistical service system, observing the problematization of agricultural production in the state of Tocantins, considering that this sector is one of the most promising in terms of socioeconomic and regional development in the country. Theoretical benchmark: with the growing advancement of agricultural production and the exploration of new frontiers, Brazil stands out as one of the main exporters of agricultural products today. Given the significant development of agriculture, it is observed that the logistical factor, mainly costs and infrastructure, is among the elements with the greatest impact on the efficiency of the entire agricultural production chain in the state of Tocantins. Method: the methodology adopted will be the deductive method, based on theoretical logistics studies, applicable legislation, and support materials for logistics learning systems, in addition to economic representation in the state of Tocantins. The resources used include bibliographic and documentary material and other instruments or research techniques in accordance with the adopted methodology, aiming to provide support for research on the proposed theme. Results and conclusion: given the content of this study, it is highlighted that the chain of agricultural processes encompasses a complex network of activities in the production chain, and cannot be conceived solely as a relationship between producer and consumer, given its breadth of action. In this context, it should be noted that logistics services end up representing one of the obstacles to the development of agriculture in the State of Tocantins, mainly due to its geographic location. Implications of the research: the approach adopted in this research offers unprecedented scientific contributions to the field of logistics, providing theoretical bases for interventions and public policies that can impact this economic activity in a Brazilian state with strong economic and social growth trends, whose production has repercussions at national and international levels. Originality/value: the social transformations of recent decades, related to the process of globalization of the economy and technology, have directly influenced the social and economic life of countries, affecting production and service chains and interfering in labor relations. Therefore, the increase in regions dedicated to agribusiness activities is a general trend among emerging countries, requiring a deeper understanding of the territorial approach to regional development, especially in economic activities hampered by bottlenecks in the logistics system, both national and international. Thus, new reflections and planning are necessary and imperative elements in Brazilian states like Tocantins.

Profil épidémiologique des dermatoses vues en consultation dans les services de dermatologie de Lomé (Togo)

Objective: The aim of this study was to list the various dermatoses observed in consultations at dermatology departments in Lomé. Method: This was a retrospective descriptive study conducted over a 16-year period (1 January 2005 to 31 December 2020) in the public dermatology departments of Lomé. Patient files were reviewed. Pathologies were grouped into immuno-allergic, inflammatory, infectious and tumoral dermatoses, sexually transmitted infections and other dermatoses. Results: During the study period, 42523 patient files were reviewed, 2730 files (6.4%) were excluded for incomplete information. July was the month with the highest frequency of consultations (11%). The average age of patients was 26.36 +/- 16.85 years (range: 1 month to 102 years) and the sex ratio (M/F) was 0.6. The age range 0-15 years was the most represented 29%. Immuno-allergic dermatoses accounted for 40.9% of consultations, followed by inflammatory dermatoses (21.4%) and infectious dermatoses (20.7%). The top 5 causes of consultation in general were: eczema 23.5%; prurigo 9.3%; irritant dermatitis 8.9%; acne 5.5% and pruritus 4.4%. Conclusion: Our study shows a high frequency of immunoallergic dermatoses in Lomé. Dermatoses are also influenced by climate change, the country’s development and various social trends.

Product Design for the Elderly Based on Human-Computer Interaction in the Era of Big Data

Since 21st century, social aging trend has become more and more serious. It needs accurately identify the nursing needs of elderly disabled people, who are characterized by inconvenient movement and unclear speech. How to solve these problems has become a key point in the field of elderly care and medical care. In response to this problem, this research has designed a human-computer interactive gesture recognition system for elderly nursing beds in the context of big data. The recognition rate of the fusion feature + support vector machine (SVM) classifier adopted in this study is higher than 90% for each category of gesture. On the test set, this method has an average recognition rate of 96.35%, which is much higher than that of single feature + SVM classifier. While other methods’ recognition rate is lower than 90%. The recognition rate of tag c (nursing bed posture turning left) with obvious gesture feature information is as high as 99.28%, and that of tag h (nursing bed posture bedpan lowering) with weak gesture feature is 93.65%. The human-computer interaction system has well realized the recognition intention of user’s dynamic and static gestures, achieved the goal set by the research, and the interaction form is natural and reliable. In the later research, we can further realize a more comprehensive, accurate and natural human-computer interaction product design through the multi-channel joint decision-making scheme to meet the needs of the elderly.

Microfluidic preparation of surfactant-free ultrafine DAAF with tunable particle size for insensitive initiator explosives

High purity and ultrafine DAAF (u-DAAF) is an emerging insensitive charge in initiators. Although there are many ways to obtain u-DAAF, developing a preparation method with stable operation, accurate control, good quality consistency, equipment miniaturization, and minimum manpower is an inevitable requirement to adapt to the current social technology development trend. Here reported is the microfluidic preparation of u-DAAF with tunable particle size by a passive swirling microreactor. Under the guidance of recrystallization growth kinetics and mixing behavior of fluids in the swirling microreactor, the key parameters (liquid flow rate, explosive concentration and crystallization temperature) were screened and optimized through screening experiments. Under the condition that no surfactant is added and only experimental parameters are controlled, the particle size of recrystallized DAAF can be adjusted from 98 nm to 785 nm, and the corresponding specific surface area is 8.45 m2·g−1 to 1.33 m2·g−1. In addition, the preparation method has good batch stability, high yield (90.8%–92.6%) and high purity (99.0%–99.4%), indicating a high practical application potential. Electric explosion derived flyer initiation tests demonstrate that the u-DAAF shows an initiation sensitivity much lower than that of the raw DAAF, and comparable to that of the refined DAAF by conventional spraying crystallization method. This study provides an efficient method to fabricate u-DAAF with narrow particle size distribution and high reproducibility as well as a theoretical reference for fabrication of other ultrafine explosives.

Утомленные социально – сегодня и навсегда? Рецензия на книгу Бён-Чхоль Хана «Общество усталости. Негативный опыт в эпоху чрезмерного позитива». Москва: Издательство АСТ, 2023. 161 с.

<p style="text-align: justify;">The reviewed book presents a philosophical view on a number of social and socio-psychological problems of the modern era, a significant part of which is analyzed through the prism of subjective human experiences, including destructive ones. Depression, emotional burnout, attention deficit hyperactivity disorder, which are widespread today, are, according to the author's position, the natural consequences of an increasing social trend – the imperative of individual achievements characteristic of a society that expects each of its members to comply with the requirements of multitasking and constant acceleration. Such a society naturally replaces open violence against a person with the practice of self–exploitation, and its value guideline is "positivity" (orientation to all positive things), leading to the denial of real social diversity, and eventually to social atomization. The author sees a constructive way out for a person of the "fatigue society" in the need for non-action and conscious contemplation, which immanently imply openness to the world.</p>

Exploring the Influence of Social Media on Financial Literacy among Millennials and Assessing the Gender Gap

The purpose of this study is to investigate how social media influences financial literacy among millennials, as well as to analyze the gender difference in financial knowledge and behavior within this group. Given the increasing integration of social media into millennials' daily lives, these platforms have the potential to significantly influence their understanding of financial matters. The study will examine how social media content, interactions, and trends influence millennials' financial knowledge, attitudes, and behaviors, particularly in detecting gender differences in financial literacy. Data on millennials' social media usage patterns, financial awareness levels, and attitudes toward money management will be gathered using a combination of quantitative surveys and qualitative interviews. The purpose of this research is to identify links between social media exposure and financial literacy results, as well as disparities in financial behaviors across male and female millennials. Finally, the findings will help to better understand the impact of social media on financial literacy and suggest ways for closing the gender gap in financial awareness and decision-making among millennials. Keywords: Social Media, Financial literacy, Millennials, Gender gap, Financial Knowledge, Financial Behavior, Social media influence, Financial attitudes, Financial management, Financial decision-making, Social media content