Diverse Media Research Articles

Agent-based modelling of polarized news and opinion dynamics in social networks: a guidance-oriented approach

Abstract In the contemporary social network landscape, opinion polarization has emerged as a prominent challenge, sparking concerns about the effective guidance of news sentiment and mitigation of opposing opinions. This is particularly pertinent in the intricate web of social networks, where complexity reigns supreme. Addressing this pivotal issue, this article introduces a news opinion guidance approach grounded in motif recognition. To accurately mirror real-world social networks, we have crafted an agent-based model that simulates polarized news propagation. This model encompasses diverse media agents and user agents, meticulously replicating the news dissemination process within the network. In our quest to unveil the underlying structures of social networks, we have enhanced the Augmented Multiresolution Network approach, incorporating multi-dimensional node attributes for more nuanced clustering and network mapping. This refinement enables us to pinpoint potential motif regions with greater precision. Leveraging these insights, we introduce a triangular motif-based opinion guidance strategy aimed at shaping opinion distribution by bolstering the influence of nodes within these motifs. Once the pertinent motifs are identified, we undertake simulation experiments that reveal the remarkable efficacy of our motif recognition-driven guidance strategy. Notably, it reduces opinion polarization by a substantial 74% compared to scenarios without guidance strategies. This research offers a fresh perspective on crafting personalized and targeted news sentiment guidance strategies. It presents a versatile and potent computational framework for understanding and managing polarization phenomena in social networks, carrying profound theoretical and practical ramifications.

DECONSTRUCTING INDUSTRIAL REVOLUTION 4.0 DISCOURSE IN EDUCATIONAL INEQUALITY IN INDONESIA

Research with the topic of deconstructing industrial revolution 4.0 discourse is become important to provide awareness that except spiritual concepts, absolute truth cannot exist. In the discourse of Industrial Revolution 4.0, we must see the truth as separated fragments. The discourse of the industrial revolution 4.0, is born and forced to become a new regime of truth in society. Knowledge and enthusiasm regarding the discourse of the industrial revolution 4.0 which is disseminated systematically and then manifested into regulations actually curbs people's way of thinking. Therefore, this research aims to examining overlooked meanings, or even presenting a different perspective with critical analysis regarding industrial revolution discourse in education. And also revise the facts behind the belief and enthusiasm for the industrial revolution 4.0 discourse. This research uses a qualitative approach, with a literature study method, so that data is obtained through reviewing various scientific journals related to the research theme. Research findings show 1) industrial revolution 4.0 discourse was formed because the state positioned education as an opportunity for economic activity, which then had to be adapted and lead to children's investment in the future through education, 2) The delegation of quality education to the private sector and the reduced role of the state are caused by neoliberal discourse. Problems then arise when the discourse on industrial revolution 4.0 actually ignores the right to an equitable and prosperous life and further sharpens inequality in society, 3) Each social class has different habits (habitus) to respond to readiness for the industrial revolution 4.0. Starting from media ownership and access to learning, to family cultural factors and the absence of the state in important areas of learning.

Permutation of National Identification Number for a Better Security in Communication Channel

This study proposes a new method to enhance the security of transmitting national identification number via various communication channels like SMS, email, and Box office. It introduces a permutation technique utilizing the Gamma 1 Non-Deranged Permutation group, ensuring the confidentiality of the information. By employing 11 factorial (11!) permutations, the national identification number is transformed into a mixed format for unintended recipients, yet remains easily decrypted by the intended recipient. This approach mitigates concerns regarding data interception and unauthorized access, providing a robust solution for secure information transmission across diverse media channels.

Intermedial participatory culture: ludification and gamification for sustainable development

The research approaches civic engagement from the perspective of Intermedial Studies, shedding light on different strategies of ‘mediation’, the way people engage in civic practices and shape the public sphere in postdigital culture. The paper explores the evolution of civic webs, living labs, forms of meaningful play in ludified transmedia practices, and serious videogames as diverse media that can address the intersection of civic engagement and sustainable development. A focal point of the research is the role of intermedial participatory strategies to promote a sociocultural scenario sensitive towards United Nations' Sustainable Development Goals (SDGs) related to urban planning, smart cities, and environmental issues. Building upon this starting point, the study extends to the transformative realms of transmedia storytelling and the difference between ludification and gamification, elucidating the main role of game-based public participation to fostering community engagement and eco-digital literacy. The paper supports the empowering potential of multiplatform, co-creative and experimental environments in advancing communal pursuits of sustainable goals in interconnected and offline contexts for sociocultural innovation.

Learner Perceptions of Artificial Intelligence-Generated Pedagogical Agents in Language Learning Videos: Embodiment Effects on Technology Acceptance

Artificial intelligence generates vibrant characters, encompassing teachers, peer students, and advisors within diverse educational media. However, the impact of the perceived embodiment of such characters in language learning videos on students’ technology acceptance and adoption is unclear. Integrating structural equation modeling into thematic analysis, this study analyzes 1042 valid responses from higher education students to bridge this research gap. Our study reveals that four subdimensions of embodiment (human-likeness, credibility, learning facilitation, and engagement) significantly and positively predict higher-education students’ perceived ease of use and usefulness of artificial intelligence-generated virtual teachers in language learning videos. Notably, an exception arises, as human-likeness does not significantly predict students’ perceived ease of use in our research context. Students’ perceived systemic interactivity and impact on the learning process emerge as pivotal mediators. The qualitative thematic analysis identifies students’ concerns about classroom administration, developmental support, technical issues, deprived interpersonal collaboration, and liberal attainment cultivation with the virtual teacher presence. This study can illuminate artificial intelligence technology designs and applications in education.

Interpersonal Communication Interconnection in Media Convergence Metaverse

The metaverse aims to provide immersive virtual worlds connecting with the physical world. To enable real-time interpersonal communications between users across the globe, the metaverse places high demands on network performance, including low latency, high bandwidth, and fast network speeds. This paper proposes a novel Media Convergence Metaverse Network (MCMN) framework to address these challenges. Specifically, the META controller serves as MCMN's logically centralized control plane, responsible for holistic orchestration across edge sites and end-to-end path computation between metaverse users. We develop a model-free deep reinforcement learning-based metaverse traffic optimization algorithm that learns to route flows while satisfying the Quality of Service (QoS) boundaries. The network slicing engine leverages artificial intelligence and machine learning to create isolated, customized virtual networks tailored for metaverse traffic dynamics on demand. It employs unsupervised and reinforcement learning techniques using network telemetry from the META controller to understand application traffic patterns and train cognitive slicer agents to make quality of service -aware decisions accordingly. Optimized delivery of diverse concurrent media types necessitates routing intelligence to meet distinct requirements while mitigating clashes over a shared infrastructure. Media-aware routing enhances traditional shortest-path approaches by combining topological metrics with workflow sensitivities. We realize an edge-assisted rendering fabric to offload complex processing from bandwidth-constrained endpoints while retaining visual realism. Extensive simulations demonstrate MCMN's superior performance compared to conventional networking paradigms. MCMN shows great promise to enable seamless interconnectivity and ultra-high fidelity communications to unlock the true potential of the metaverse.

GASEKO: Scramble Game Media to Increase Elementary School Students’ Learning Independence

The lack of diversity in digital media and the low degree of student learning independence in primary schools prompted this development inquiry. In order to help fourth graders become more self-reliant learners, this study seeks to develop a realistic, practical, and successful economic scramble game (GASEKO) for classroom usage. The goal of this research was to analyze the extent to which fourth grade primary school pupils were able to learn independently, and the subjects’ included students, learning technology experts, and subject matter experts. The five-stage ADDIE model—which is used in this development study—consists of the following steps: analysis, design, development, implementation, and evaluation. A questionnaire or surveys are the tools utilized for gathering information. Fifteen primary school pupils in the fourth grade participated in the product trial. Qualitative, quantitative, and statistical descriptive analytic methods were employed to examine the study data. We can conclude that GASEKO media is a viable, practical, and effective strategy for enhancing the learning independence of fourth graders based on the following evidence: (1) GASEKO media has strong credentials from expert validation; (2) GASEKO media has very good credentials according to student responses; and (3) GASEKO media significantly impacts fourth graders' learning independence. This study's findings suggest that GASEKO media can broaden the range of educational resources available to schools, leading to more engaging and effective lessons for students.

A label-free fluorescence aptamer sensor for point-of-care serotonin detection

Serotonin, a pivotal neurotransmitter regulating various physiological functions, plays a crucial role in disease diagnosis, necessitating precise monitoring of its levels in biological fluids for accurate assessment. Aptamers, known for their high specificity and affinity, have emerged as innovative molecular probes for serotonin analysis. However, existing serotonin aptamer sensing platforms exhibit limitations in terms of portability and rapid detection capabilities. In this study, we introduce a novel, portable, label-free serotonin aptamer sensor utilizing a dye replacement strategy, achieving a short sample-to-result turnaround time and convenient signal readout through a smartphone. The performance of this aptamer sensor was thoroughly assessed across diverse physiological media, demonstrating robust stability in buffer, urine, and serum. Importantly, the detection limit was in the nanomolar range, emphasizing its suitability for the rapid, sensitive, and user-friendly detection of serotonin. This research pioneers an approach for the development of a point-of-care testing (POCT) system for serotonin with practical implications, particularly in resource-limited settings.

Banditry and “captive population syndrome” in northern Nigeria

ABSTRACT The banditry crisis in northern Nigeria has been associated with dire implications for human population and settlement. Scholarship on the subject area has largely failed to foreground the nexus between banditry and population dynamics in the context of threat-induced migration, displacement, and bond-settlement patterns. Although there are diverse media and policy-based insights pertaining to the impact of the banditry crisis on the settled population, the conditions of persons, households and communities displaced or subjected to various forms of captivity by the crisis have been almost entirely unexplored by way of organized research. Using a combination of primary and secondary data, this paper examines the population-in-captivity dimension of the banditry crisis in northern Nigeria. It posits that the banditry crisis has, among others, created a captive population(s) who are exposed to complex, mortal existential threats, and vulnerabilities in the context of Nigeria’s burgeoning un(der)governed spaces and state fragility syndrome.

Recent advancements in encapsulation of poly aromatic hydrocarbons via macrocyclic host-guest chemistry

Polyaromatic hydrocarbons (PAHs) pose a significant threat to ecosystems and human health due to their widespread presence and persistence in the environment. Conventional remediation techniques often fall short in both efficiency and environmental impact. However, recent advancements in utilizing organic macrocyclic host molecules show considerable promise for effectively sequestering and eliminating PAHs across diverse media. These macrocyclic host molecules play a central role in host–guest chemistry and supramolecular chemistry. It offers distinct advantages by virtue of their precisely tailored cavities and customizable functionalities, greatly enhancing their selective recognition abilities towards guest PAHs. The pursuit of designing and synthesizing novel functional macrocycles has captivated the attention of researchers, driven by the quest to address various challenges in supramolecular research. Over decades of dedicated exploration in host–guest chemistry and supramolecular chemistry, an expansive array of macrocyclic host molecules, constructed from diverse building blocks, have emerged as pivotal tools for encapsulating PAHs. This review presents an overview of the recent progress in the design, synthesis, and application of purely organic macrocyclic molecules in the encapsulation of PAHs. It elucidates the underlying principles that govern their ability to recognise PAHs, such as host–guest interactions, shape complementarity, and π-π stacking interactions. Furthermore, the review discusses various experimental methodologies, such as spectroscopic analyses, chromatography, and computational modelling, employed to assess the efficiency of organic cage molecules in PAH trapping. Additionally, considerations regarding the scalability and environmental implications of organic cage-based PAH trapping systems are addressed. The insights gleaned from this research provide valuable guidance for the development of robust strategies to combat PAH pollution in diverse environmental contexts.

The Effect of "MOLKESPRO" Educational Media on The Level of Knowledge of Early Adolescents about Reproductive Health

Child marriage in Indonesia is a recurring reality in society. Early marriage is a form of gender inequality, especially for women. Globally, 21 percent of women living in 2020 were married before the age of 18, and 12 million girls under 18 are married each year, or about 23 girls married as children every minute. Various reasons for the high rate of early marriage are not only due to educational, economic, and stigmatizing factors but also due to the low understanding of adolescents about reproductive health, which causes adolescents to have no choice, especially for adolescent girls. The purpose of this study was to determine the effect of "MOLKESPRO" monopoly media on adolescents' knowledge about reproductive health. The design of this study was pre-experimental with a pre-post-test design approach. Using the purposive sampling technique, the population was grade 6 elementary school students, as many as 31. In this study, the instrument used was a questionnaire about reproductive health—data analysis using a paired t-test. The results showed that the respondents' knowledge got the less category (35 percent) before being given health education and got a good knowledge category (81 percent) after being given health education. The results obtained p value less than 0.000 (0.000 less than a). Therefore, there is an effect of "MOLKESPRO" on the knowledge of early adolescents about reproductive health. Thus, the "MOLKESPRO" monopoly media can be used by midwives and other health workers in providing health education to early adolescents related to reproductive health, this is because its attractive design can make students enthusiastic to learn materials about reproductive health using the atmosphere created with fun.

Linguistic diversity in media and state language proficiencies: evidence from Hungarian minority regions in central-Eastern Europe

ABSTRACT Can linguistic diversity in the media impede state language proficiency? In this paper, we test the extent to which the availability of minority languages in the media affects state language proficiency for ethnic minorities. We take advantage of an exogeneous development: The rapid expansion of Budapest-originating media outside Hungary in the mid-2000s transformed the media landscape in neighbouring states. Using an original survey data of ethnic Hungarians in minority regions in four Central-Eastern European states over two waves, we find (1) the availability of minority language media means minorities are consuming less media in the state language, which in turn induces low levels of state language proficiency – i.e. through an exogeneous exposure mechanism; and (2) minorities with weaker state language proficiency choose to consume minority language media – i.e. through an endogenous selection mechanism. The results suggest a strong relationship between the language of media consumption and linguistic proficiency.

Emotion recognition for human–computer interaction using high-level descriptors

Recent research has focused extensively on employing Deep Learning (DL) techniques, particularly Convolutional Neural Networks (CNN), for Speech Emotion Recognition (SER). This study addresses the burgeoning interest in leveraging DL for SER, specifically focusing on Punjabi language speakers. The paper presents a novel approach to constructing and preprocessing a labeled speech corpus using diverse social media sources. By utilizing spectrograms as the primary feature representation, the proposed algorithm effectively learns discriminative patterns for emotion recognition. The method is evaluated on a custom dataset derived from various Punjabi media sources, including films and web series. Results demonstrate that the proposed approach achieves an accuracy of 69%, surpassing traditional methods like decision trees, Naïve Bayes, and random forests, which achieved accuracies of 49%, 52%, and 61% respectively. Thus, the proposed method improves accuracy in recognizing emotions from Punjabi speech signals.

Testing influences of openness, conscientiousness, nationalism, media diversity, social class, and informational echo chambers on support for official responses to COVID-19 in Wuhan in November, 2020.

As the COVID-19 pandemic raged, controversies about governmental responses to the epidemic also emerged in China. Previous studies mainly described the phenomenon of individual differences on support for governmental responses to COVID-19 with less attention to the underlying causal mechanisms. Thus, this study tries to verify the factors influencing public support for official behaviors in COVID-19. A questionnaire survey was drew on in Wuhan city during the COVID-19 outbreak. The quota sampling method was adopted according to the gender and age structure of the population in Wuhan as well as the educational structure of the urban population in China. Through structural equation analysis, this study confirms that personal factors (namely conscientiousness and nationalistic ideology), behavioral factors (namely media diversity and echo chamber acts) exert significantly positive impacts on support for governmental responses. The echo chamber acts play important mediating roles in the relationship between each independent variable and support for governmental responses. The originality of this study is that it constructs a comprehensive model of influencing factors of support for governmental responses with the personal, behavioral, and environmental factors. While contributing insight to political attitude in China, the research results also have significance for promoting public trust and constructing healthy public opinion in China.

Creativity Profile Of Accounting Teachers In The Era Of Independent Learning

This research aims to (1) obtain information regarding teacher creativity in implementing the independent curriculum, (2) determine the obstacles that arise in achieving creative teachers. This research is descriptive qualitative research using interviews and observation techniques, then the data is processed using Miles and Huberman data analysis. Based on the research results, it can be concluded that creativity in preparing teaching modules and teaching materials is grouped into four dimensions, namely personal dimensions, process dimensions, product dimensions and press dimensions. The personal dimension of creativity in preparing teaching modules can be seen from the application of differentiated learning, the application of learning methods, and the elements of teaching modules. The dimensions of the creativity process in preparing teaching modules can be seen from the survey of student needs and understanding of learning outcomes, learning objectives and the flow of learning objectives. The product dimension of creativity in preparing teaching modules can be seen from the appearance of the teaching module and the content of the teaching module. In the press dimension, creativity in preparing teaching modules can be seen from the recognition and responses of other people. Meanwhile, the personal dimension of creativity in preparing teaching materials can be seen from the diversity of teaching materials and learning media as well as the depth of materials and assessments. The dimensions of the creativity process in preparing teaching materials can be seen from understanding the teaching materials. In the product dimension, creativity in preparing teaching materials can be seen from the resulting teaching materials. In the press dimension, creativity in preparing teaching materials can be seen from the recognition and responses of other people. Barriers that are often experienced include self-motivation, time management, and mastery of information technology.

Formulating marketing strategy of Si Bijak microinsurance using SWOT analysis, marketing mix and Business Model Canvas

Life risks can happen to anyone, including low-income people who are vulnerable to the risk of death and loss of property due to unexpected events. This research uses SWOT analysis, marketing strategy, 7P marketing mix, and Business Model Canvas to find out the causes of sales failure and solutions that can be used as a reference for the sale of Si Bijak microinsurance in the future. This research method uses qualitative methods through literature analysis, data, and information from interviews with 4 (four) subjects directly conducted in November 2023-January 2024 and verified through repeated checks so that it can be analyzed. The results showed the need for repricing and the number of insurance benefits, the addition of diverse marketing communication channels and media, massive sales activities through cooperation with microfinance institutions, social institutions, and communities, development of microinsurance application technology, increasing education/literacy to the public, promotional activities for ease of sales, and supervision and support from regulators.

The impacts of biodegradable and non-biodegradable microplastic on the performance and microbial community characterization of aerobic granular sludge.

Microplastics (MPs), identified as emerging contaminants, have been detected across diverse environmental media. Their enduring presence and small size facilitate the adsorption of organic pollutants and heavy metals, leading to combined pollution effects. MPs also accumulate in the food chain thus pose risks to animals, plants, and human health, garnering significant scholarly attention in recent years. Aerobic granular sludge (AGS) technology emerges as an innovative approach to wastewater treatment. However, the impacts of MPs on the operational efficiency and microbial characteristics of AGS systems has been insufficiently explored. This study investigated the effects of varying concentration (10, 50, and 100 mg/L) of biodegradable MPs (Polylactic Acid, PLA) and non-biodegradable MPs (Polyethylene Terephthalate, PET) on the properties of AGS and explored the underlying mechanisms. It was discovered that low and medium concentration of MPs (10 and 50 mg/L) showed no significant effects on COD removal by AGS, but high concentration (100 mg/L) of MPs markedly diminished the ability to remove COD of AGS, by blocking most of the nutrient transport channels of AGS. However, both PLA and PE promoted the nitrogen and phosphorus removal ability of AGS, and significantly increased the removal efficiency of total inorganic nitrogen (TIN) and total phosphorus (TP) at stages II and III (P < 0.05). High concentration of MPs inhibited the growth of sludge. PET noticeably deteriorate the sedimentation performance of AGS, while 50 mg/L PLA proved to be beneficial to sludge sedimentation at stage II. The addition of MPs promoted the abundance of Candidatus_Competibacter and Acinetobacter in AGS, thereby promoting the phosphorus removal capacity of AGS. Both 50 mg/L PET and 100 mg/L PLA caused large amount of white Thiothrix filamentous bacteria forming on the surface of AGS, leading to deterioration of the sludge settling performance and affecting the normal operation of the reactor. Comparing with PET, AGS proved to be more resistant to PLA, so more attention should be paid to the effect of non-biodegradable MPs on AGS in the future.

An Educational Chatbot Using AI in Radiotherapy

The surge in demand for information in cancer centers and hospitals, particularly during the pandemic, overwhelmed the limited manpower available. To address this challenge, there arose a need to develop an educational chatbot tailored for diverse user groups in the field of radiotherapy, including patients and their families, the general public, and radiation staff. Objective: In response to the pressing clinical demands, the primary aim of this endeavor is to delve into the intricacies of designing an educational chatbot for radiotherapy using artificial intelligence.Methods: The chatbot is meticulously crafted using a dialogue tree and layered structure, seamlessly integrated with artificial intelligence functionalities, notably natural language processing (NLP). This adaptable chatbot can be deployed across various platforms, such as IBM Watson Assistant, and embedded in websites or diverse social media channels.Results: Employing a question-and-answer methodology, the chatbot adeptly engages users seeking information on radiotherapy, presenting an approachable and reassuring interface. Recognizing that users, often anxious, may struggle to articulate precise questions, the chatbot facilitates the interaction by offering a curated list of questions. The NLP system augments the chatbot's ability to discern user intent, ensuring the provision of accurate and targeted responses. Notably, the study reveals that functional features, including mathematical operations, are preferred in educational chatbots, necessitating routine updates to furnish fresh content and features.Conclusions: The study culminates in the affirmation that leveraging artificial intelligence facilitates the creation of an educational chatbot capable of disseminating information to users with diverse backgrounds in radiotherapy. Furthermore, the importance of rigorous testing and evaluation, informed by user feedback, is emphasized to iteratively enhance and refine the chatbot's performance. Keywords: AI, machine learning, NLP, chatbot, radiotherapy, IoT, healthcare.

The coordination network toolkit: a framework for detecting and analysing coordinated behaviour on social media

This paper introduces and evaluates the Coordination Network Toolkit, an open-source software package and methodological framework designed to detect and analyse coordinated behaviour on social media platforms. As the dynamics of online communication continue to evolve, coordination analysis has emerged as an important field of study with significant implications for understanding online influence, digital astroturfing, and online activism. Recognising the absence of a comprehensive, open-source tool for constructing coordination networks, our approach fills this gap, catering to multiple behaviors across diverse social media platforms. Our approach synthesises and significantly enhances various methods to provide a methodological framework for ‘multi-behaviour’ coordination detection, utilising weighted, directed multigraphs to capture intricate coordination dynamics. We evaluate our approach by revisiting a case study of the 2020 #ReopenAmerica Covid protest movement on Twitter. The paper concludes with a set of recommendations for future work, emphasising the need for a tailored statistical framework for coordination analysis and a deeper exploration into the motives behind online coordination.

Transport and retention of nanobubbles in saturated porous media: Overlooked role of grain size and shape

Nanobubbles (NBs) are widely used in groundwater pollution treatment due to their unique properties such as small size and high gas mass transfer rate. Therefore, the transport behavior of NBs in the groundwater environment has attracted more attention. Due to the diversity and complexity of aquifer media in the natural environment, grain sands with different sizes and shapes are ubiquitous. Thus, consideration of grain size and shape in porous media is crucial to predict and evaluate the transport and fate of NBs in soil and groundwater systems. This work investigated the stability of NBs in pure water. The transport behavior and mechanism of NBs under different grain sizes and shapes were demonstrated by the column experiment, microscopic observation, and numerical simulation. The results showed that NBs had excellent stability, remaining in solution for more than 10 days. The retention of NBs in coarse, medium and fine sands was 23.5 %, 43.8 % and 50.8 %, respectively. The retention in sphere sands, oval sands and irregular sands was 22.9 %, 24.0 % and 43.8 %, respectively. The smaller grain size and roundness limited the NBs transport in the saturated porous media, which was mainly due to the complexity of the flow channel and the narrowing of the pore throat of fine sands and angular shape of irregular sand that would hinder the NBs transport. This was proved by the Derjaguin − Landau − Verwey − Overbeek (DLVO) theory and ultra − depth − of − field microscope. The BTCs of NBs were fitted by the one − site deposition model (only attachment) and two − site deposition model (attachment and straining), and it was found that two − site deposition model showed a better fit. The straining rate (kstr) was greater than the attachment rate (katt) in different grain sizes and shapes media, indicating that the retention mechanism of NBs in porous media was a synergistic mechanism dominated by pore straining and supplemented by electrostatic attraction.