Dissemination Of Information Research Articles

Immersive Entertainment: The Reconstruction and Value Analysis of Chinese Mythology

As an integral part of Chinese culture, Chinese mythology embodies rich historical, cultural, and philosophical connotations. With the accelerated development of the cultural and creative industry, Chinese mythology, with its rich content, imagery, and narratives, has gained favor among practitioners. It is deconstructed and reshaped in contemporary contexts, showing a trend of pan-entertainment in the field of cultural consumption. The immersive real-scene entertainment industry, a nascent sector in China with just over twenty years of development, utilizes advanced technologies to create multi-sensory immersive experiences. This medium, following films, theater, and games, serves as another high-quality, high-density information dissemination channel and has unique advantages in the re-creation of original Chinese myths. This study explores the development of Chinese myths such as "The Legend of the White Snake" and "Dunhuang Feitian," analyzing immersive entertainment cases like "Seeking the Realm of Dunhuang - Digital Dunhuang Immersive Exhibition." Through textual analysis and comparative investigation, it examines the current status and future prospects of real-scene entertainment, and the historical tracing and restoration of Chinese mythology that can be achieved via the industry.

Advancing Road Safety Through Intelligent Vehicle Accident Detection and Reporting Enabled by IoT Innovation

The escalating incidence of road accidents poses a significant challenge to public safety, often exacerbated by delays in emergency response. This research introduces an IoT-based intelligent system designed to revolutionize accident management by providing real-time data and critical information to emergency services. By seamlessly integrating Raspberry Pi and Arduino microcontrollers with advanced sensors such as force-sensitive resistors (FSRs), GPS, and potentially additional sensors like accelerometers and gyroscopes, the system accurately detects accidents, assesses their severity, and captures comprehensive data, including passenger images, vehicle details, and precise accident location. Upon impact, the system rapidly transmits this data, along with pre and post-accident images, to a designated emergency response center via a secure and reliable communication network. This swift dissemination of critical information empowers emergency responders to make informed decisions, optimize resource allocation, and prioritize response efforts, ultimately saving lives and minimizing the impact of accidents. The system's intelligence lies in its ability to not only detect accidents but also to assess their severity based on sensor data analysis, enabling a more targeted and efficient emergency response. Furthermore, the system's potential to collect valuable data on accident patterns and causes can contribute to the development of preventive measures and road safety strategies. By leveraging the power of IoT technology, this research aims to significantly enhance road safety and transform accident management practices.

Leveraging Social Media for Enrichment in Buddhist Tourism: A Mixed-Methods Study between Pakistan and China

This research work takes a strategic perspective on how social media can be leveraged for use between Pakistan and China, considering cultural and historical ties under the roof of Buddhist tourism. The Uses and Gratification Theory (UGT) is applied in this qualitative study, complemented by the quantitative analysis of engagement through social media, to gain insights into why people visit different websites and how effective social media is in promoting tourism. The paper considered WeChat, Weibo, Instagram, and Facebook as they all have something unique to give to a tourist. The research has found that culturally relevant and visually rich content is much more effective in attracting Chinese tourists to the Buddhist heritage sites of Taxila and Takht- i-Bahi in Pakistan. Different online platforms have different preferences in presenting information and visual engagement, so WeChat is ideal for the dissemination of information and Instagram for visual engagement. Findings highlight the importance of cross-platform strategies and localized content for maximum outreach of tourism. Tables have been provided to compare the engagement metrics across the platforms, indicating which content types work well. This research provides actionable suggestions for tourism boards and marketers to develop targeted social media policies that can support higher tourist visits between countries and strengthen cultural bonds.

Valuable Data "Gain" and "Loss": The Quantitative Impact of Information Choice on Consumers' Decision to Buy Selenium-Rich Agricultural Products.

Biotechnology assumes a paramount role in addressing micronutrient deficiencies. The promotion thereof and the augmentation of public awareness are indispensable for implementation. The advancement of big data presents challenges due to the plethora of information and the constrained processing capacity, thereby inducing difficulties in consumer decision-making. The study is obliged to intensify information dissemination to empower consumers to apprehend the value of selenium-enriched products as an integral constituent of positive nutrition guidance. The study undertook an experiment related to nutrition information acquisition, in which participants provided relevant interferences. The study utilized the structural equation model (SEM) and fuzzy set qualitative comparative analysis (fsQCA) to analyze the data. The study arrived at three research conclusions. Firstly, the furnishing of valuable information constitutes a significant factor in motivating consumers to purchase selenium-rich agricultural products. Secondly, the communication of brand information holds crucial significance in shaping the perception of product advantages and plays a salient role in the promotion and construction of selenium-rich agricultural products. Finally, the dissemination of health information can be incorporated into the process of promoting selenium-rich agricultural products. This conforms to the urgent necessity to address hidden hunger and establish a value identity.

Analysis of the practice of application of Article 114-2 of the Criminal Code of Ukraine (Unauthorized dissemination of information on the sending, movement of weapons, armaments and ammunition to Ukraine, movement, movement or deployment of the Armed Forces of Ukraine or other military formations formed in accordance with the laws of Ukraine, committed under martial law or a state of

The article analyzes the practice of consideration of cases under Article 114-2 of the Criminal Code of Ukraine, which provides for liability for unauthorized dissemination of information on the sending, movement of weapons, armaments and ammunition to Ukraine, movement, relocation or deployment of the Armed Forces of Ukraine or other military formations formed in accordance with the laws of Ukraine, committed under martial law or a state of emergency. During the monitoring of court decisions posted in the State Register of Court Decisions for 2022 and 2023, 112 guilty verdicts were identified and analyzed, which were delivered by courts between March 24, 2022 and December 31, 2023 (except for those verdicts where information is prohibited for disclosure). During the analysis of the guilty verdicts, it was found that most of the persons were convicted under Part 2 of Article 114 of the Criminal Code of Ukraine and Part 3 of Article 114-2 of the Criminal Code of Ukraine. The author also examines what information was most often disseminated. The author identifies the most typical forms of active actions as a sign of the objective side of the crime, the peculiarities of their commission, the most common methods and tools of crime and qualifying features. Based on the analysis of the verdicts, a number of conclusions are drawn about the typical motives for this crime and the identity of the perpetrator, the presence/absence of sincere remorse, and the confession of guilt. Certain trends in sentencing of perpetrators are identified. In particular, it is noted that in 2022, courts actively used the institute of release from serving a sentence with probation (57% of convicts), but in 2023, 70% of perpetrators were sentenced to «real» imprisonment. As a result of the generalization, the author outlines the most typical criminal law features of this crime. In order to clarify the peculiarities of the offender’s portrait, the data from the report «On Persons Who Committed Criminal Offenses» for 2022-2023 were analyzed. In particular, the number of persons identified under Art. 114-2 of the Criminal Code of Ukraine, their structure by gender, age, citizenship, education, employment, presence/absence of a criminal record, and the peculiarities of the crime (committed in complicity, while intoxicated) are determined. Certain characteristics, such as a person’s place of birth, marital status, dependent minor children, and disabled parents, were identified through sentence monitoring. As a result of summarizing these data, the author outlines a portrait of the offender.

Creating Solvability With Real-Time Crime Centers (RTCCs): Impacts on Homicide and Shooting Investigations

Amidst recent increases in homicides and shootings in the United States, clearances rates for homicides have declined and nonfatal shooting cases remain notoriously difficult to solve. Considerable research indicates that the outcomes of homicide and shooting investigations are likely influenced by a range of factors, including inherited case characteristics, investigative actions, forensic testing, and agency resources. Recent advancements in technologies available to law enforcement may help fill persistent gaps in solvability, but research remains limited on their effectiveness. RTCCs integrate a variety of technological innovations and software programs to rapidly receive and distribute information to support police operations, and they harness the strong potential to powerfully impact investigative outcomes and offer an additional pathway through which police agencies can increase case clearance. The current study explores the impact of strategic efforts in the Hartford Police Department (HPD) to increase investigative effectiveness through RTCC processes and technologies. Our findings indicate that RTCC activities significantly increase the likelihood that a case is solved, and this effect is primarily due to RTCC analysts’ ability to locate and analyze video associated with the case. When associated video was located, cases were 442% more likely to be solved when controlling for other covariates. The HPD’s RTCC operations, institutionalized technology, and organizational culture also play a crucial role, with a commitment to technology and information-sharing enhancing investigative capabilities. This study emphasizes the effectiveness of real-time crime centers in locating digital evidence, facilitating rapid information dissemination, and fostering agencywide collaboration, ultimately improving investigative outcomes.

Rumäniens Beitritt zum Schengen-Raum: Eine pragmalinguistische Untersuchung zu den österreichischen, bundesdeutschen und rumänischen Schlagzeilen in der Online-Presse

Abstract Media linguistics, an interdisciplinary research field, extensively engages in the analysis of language in the media and its impact on society. An interesting application case in media linguistics concerns the analysis of headlines in online press. Headlines in the media play a crucial role in information dissemination and significantly influence public opinion formation. When it comes to political events or international developments, headlines serve as powerful tools to shape the perception of the news and thus steer readers’ attitudes in a desired direction. In this article, I refer to the Austrian, German and Romanian online press regarding Romania’s accession to the Schengen Area. It is noticeable that the coverage in German media often appears more distant, while Austrian media adopt a critical tone in their headlines. This particularity could be linked to Austria’s geo graphical proximity to Romania, raising interesting questions about media linguistics and the cultural imprint on media coverage. In addition, the analysis also employs a pragmalinguistic perspective, which explores how linguistic elements in headlines are used within specific communicative contexts to convey meaning and achieve pragmatic goals.

The Role of Indonesia’s National Health Insurance Cadre: A Case Study in Bali

The management of informal sector participants poses the most significant difficulty to universal coverage attempts throughout Indonesia's National Health Insurance era. As a result, in April 2017, BPJS Kesehatan established the JKN Cadre Program. This program intends to expand the number of participants while also improving the collectability of contributions from the informal sector. This study aims to investigate the role of the cadre and explore the supporting, and inhibiting factors of such a program. This study is a qualitative descriptive case study, with data gathered through in-depth interviews. Informants were chosen purposefully. Thematic Analysis was utilized to examine the data, which Source Triangulation subsequently confirmed. The study found that the JKN KIS cadre has five functions, the most important of which is to remind people and collect contributions. Cadre activities included education and outreach, as well as collecting payment arrears receipts. The study also identified three inhibiting and supportive elements for the role of cadre namely individual, environmental, and organisational factors. To reduce unfavourable perceptions of JKN-KIS, it is vital to increase cadre self-actualization, self-esteem, information dissemination, synergy, and quality.

Analyzing Public Interest in Geohazards Using Google Trends Data

This study investigates public interest in geological disasters by analyzing Google Trends data from 2023. This research focuses on earthquakes, hurricanes, floods, tornadoes, and tsunamis to understand how search behaviors reflect public awareness and concern. This study identifies temporal and geographical patterns in search trends. Key findings reveal that public interest spikes during significant disaster events, such as the February 2023 earthquake in Turkey and Syria and the August 2023 hurricanes in the United States. This study highlights the importance of timely and accurate information dissemination for disaster preparedness and response. Google Trends proves to be a valuable tool for monitoring public interest, offering real-time insights that can enhance disaster management strategies and improve community resilience. This study’s insights are essential for policymakers, disaster management agencies, and educational efforts aimed at mitigating the impacts of natural disasters.

Framing Effects of Emphasis and Form in Emergemcy Communication: A Study of Preventive Behaviors During the Covid-19 Pandemic in Japan

ABSTRACT This study examines the impact of frame differences on preventive behaviors in COVID-19 pandemic information. Survey experiments using large samples of Japanese participants led to the detection of framing effects of the emphasis levels and forms of information. Information framed with high severity was found to intensively influence citizens in refraining from going out. Moreover, this study demonstrates that episodic information facilitates preventive behaviors in discretionary activities. The episodic information has more intensively impacted through heuristic processing by providing exemplars. This study contributes to the reevaluation of government practices on information dissemination using various forms and intensity levels of information.

Understanding COVID-19 Media Framing: Comparative Insights from Germany, the US, and the UK During Omicron

ABSTRACT This study examines the media framing of COVID-19 reporting in Germany, the United States, and the United Kingdom during the period of the highly contagious Omicron variant from December 2021 to March 2022. By identifying issue-specific media frames using hierarchical cluster analysis, the study gains insights into the distinctive characteristics of journalistic roles within each country and sheds light on the similarities and differences in media framing. Findings reveal that the German Süddeutsche Zeitung prioritizes the economic and Omicron impact on society and reports rather emotionally through evaluations and blame on social issues but frames otherwise quite neutral, reflecting its role in opinion formation and information dissemination. Conversely, the American New York Times takes an objective and informative approach, except similar to the Süddeutsche Zeitung when dealing with social impacts of the pandemic, addressing Omicron, economic impacts, and vaccination challenges while emphasizing shared burdens of the pandemic. The British Guardian gives equal weight to economic and social consequences and the Omicron impact and also raises the issues concerning the healthcare sector. Blame and negative evaluations cross all frames and newspapers, although (emotionally charged) evaluations and accusations are most prevalent in the Guardian, often directed at unvaccinated people and politics.

Institutional investor networks and earnings management: The role of the exit threat

This study examines the potential of institutional investor networks in mitigating horizontal agency conflicts, addressing the gap in the regulatory role of institutional investors in concentrated equity markets. Using data on Chinese listed companies from 2007 to 2020, we employ the multiplex network method to investigate the impact of institutional investor networks on earnings management. Our findings reveal a significant negative correlation between institutional investor networks and earnings management. The mechanism analysis indicates that institutional investor networks primarily exert governance through the exit threat rather than through direct intervention and information dissemination. Collectively, our findings elucidate the important role of institutional investors in corporate governance and promote the application of multiplex network theory to the financial field.

Public Perception of Hate Speech on Social Media (Facebook) during the 2023 General Elections in Nigeria

In the contemporary global landscape, the advent of information and communication technology has interconnected societies, fostering increased civic engagement. Notably, social media platforms, a manifestation of this technological innovation, play a vital role in political discourse, drawing active participation from politicians, political parties, and their supporters. However, the utilization of these platforms in the context of electoral campaigns, particularly in nations like Nigeria, has raised concerns due to the dissemination of political information carrying adverse repercussions. This study delves into the examination of the public's perceptions regarding hate speech on Facebook during Nigeria's 2023 general elections. Employing a survey research strategy and leveraging convenient sampling, data were collected from residents within the geographical scope of Kwali Area Council, Abuja, Nigeria. The research framework drew upon the public sphere theory to elucidate its core objectives. Findings underscored the prevalence of hate speech on Facebook during the 2023 elections, attributing it to factors such as financial inducements, conspiracies, lack of citizen journalist training, religious interests, and sectional, tribal, and political influences. Notably, Facebook emerged as a platform for disseminating speeches that fueled animosity toward politicians, tribes, religions, and sections, instigating widespread antipathy without substantial knowledge of the targeted individuals or candidates. The research also highlighted the use of Facebook for insults, harassment, and the propagation of divisive narratives, contributing to tribal and religious conflicts, heightened tensions, attacks, disparities, and internal discord. This study's implications suggest a potential undermining of Nigeria's democratic progress. As a remedy, the study advocates for the responsible and positive use of social media platforms by users, especially during critical events such as elections.

Friendship jealousy and interaction needs: how mutual friend features affect users of WeChat Moments.

Many social networking services (SNSs) have features that highlight the common friends of pairs of users. Previous research has examined recommendation systems that use mutual friend metrics, but few scholars have studied how the existence of features related to mutual friends affects users in SNSs. To explore this issue further, we conducted interviews with 22 users of WeChat Moments to investigate how certain rules involving mutual friends affect users and how they deal with the issues that arise due to these rules. We found that the three Moments rules related to mutual friends (response visibility, response notifications, and information dissemination) can cause users to feel jealous, annoyed, and embarrassed. To prevent these negative experiences, users may reduce the amount of information they disclose or the frequency of their interactions in SNSs. Based on these findings, we propose several future directions for scholars and a small number of design suggestions aimed at assisting providers to satisfy users' interaction needs.

A Weibo local network growth model constructed from the perspective of following-followed

Abstract In order to explore the evolution process of the Weibo local network, this study first defines four factors influencing the evolution of the Weibo network. On this basis, the BA scale-free network model was enhanced by incorporating these four factors and accounting for directionality, resulting in a Weibo local network evolution model based on user attributes and behavioral similarity. The model's validity was validated by comparing simulation results with real data. The findings indicate that the Weibo local network exhibits both small-world characteristics and distinctive features. The results show that the Weibo local network exhibits both small-world characteristics and distinctive properties. The in-degree distribution follows a mixed pattern of exponential and power-law distributions, the degree-degree shows isomatching, and both the in-degree centrality and eigenvector centrality values are relatively low. This research contributes to our understanding of user behaviour in the Weibo network, and provides a structural basis for exploring the impact of Weibo network structure on information dissemination.

TCα-PIA: A Personalized Social Network Anonymity Scheme via Tree Clustering and α-Partial Isomorphism

Social networks have become integral to daily life, allowing users to connect and share information. The efficient analysis of social networks benefits fields such as epidemiology, information dissemination, marketing, and sentiment analysis. However, the direct publishing of social networks is vulnerable to privacy attacks such as typical 1-neighborhood attacks. This attack can infer the sensitive information of private users using users’ relationships and identities. To defend against these attacks, the k-anonymity scheme is a widely used method for protecting user privacy by ensuring that each user is indistinguishable from at least k−1 other users. However, this approach requires extensive modifications that compromise the utility of the anonymized graph. In addition, it applies uniform privacy protection, ignoring users’ different privacy preferences. To address the above challenges, this paper proposes an anonymity scheme called TCα-PIA (Tree Clustering and α-Partial Isomorphism Anonymization). Specifically, TCα-PIA first constructs a similarity tree to capture subgraph feature information at different levels using a novel clustering method. Then, it extracts the different privacy requirements of each user based on the node cluster. Using the privacy requirements, it employs an α-partial isomorphism-based graph structure anonymization method to achieve personalized privacy requirements for each user. Extensive experiments on four public datasets show that TCα-PIA outperforms other alternatives in balancing graph privacy and utility.

Dissemination dynamics based on delayed behavior on double-layer networks

Adoption behavior spreads socially due to a variety of variables, and the classic dynamic model is insufficient to fully understand the impact of psychological elements on humans. To illustrate the intricacy of personal decision-making and information dissemination, this paper presents the psychological mechanism of latency. This research analyzes the dynamic process on double-layer networks using an edge division theory based method. The simulation results show the phenomena of phase transition. Global outbreak is possible when latency behavior is weak; global outbreak did not happen when latency behavior becomes strong. There is good agreement between the theoretical analysis and experimental simulation results. It is extremely important for the study of psychology, sociology, and dynamics.

Racial Biases Associated With Pulse Oximetry: Longitudinal Social Network Analysis of Social Media Advocacy Impact.

Pulse oximetry is a noninvasive method widely used in critical care and various clinical settings to monitor blood oxygen saturation. During the COVID-19 pandemic, its application for at-home oxygen saturation monitoring became prevalent. Further investigations found that pulse oximetry devices show decreased accuracy when used on individuals with darker skin tones. This study aimed to investigate the influence of X (previously known as Twitter) on the dissemination of information and the extent to which it raised health care sector awareness regarding racial disparities in pulse oximetry. This study aimed to explore the impact of social media, specifically X, on increasing awareness of racial disparities in the accuracy of pulse oximetry and to map this analysis against the evolution of published literature on this topic. We used social network analysis drawing upon Network Overview Discovery and Exploration for Excel Pro (NodeXL Pro; Social Media Research Foundation) to examine the impact of X conversations concerning pulse oximetry devices. Searches were conducted using the Twitter Academic Track application programming interface (as it was known then). These searches were performed each year (January to December) from 2012 to 2022 to cover 11 years with up to 52,052 users, generating 188,051 posts. We identified the nature of influencers in this field and monitored the temporal dissemination of information about social events and regulatory changes. Furthermore, our social media analysis was mapped against the evolution of published literature on this topic, which we located using PubMed. Conversations on X increased health care awareness of racial bias in pulse oximetry. They also facilitated the rapid dissemination of information, attaining a substantial audience within a compressed time frame, which may have impacted regulatory action announced concerning the investigation of racial biases in pulse oximetry. This increased awareness led to a surge in scientific research on the subject, highlighting a growing recognition of the necessity to understand and address these disparities in medical technology and its usage. Social media platforms such as X enabled researchers, health experts, patients, and the public to rapidly share information, increasing awareness of potential racial bias. These platforms also helped connect individuals interested in these topics and facilitated discussions that spurred further research. Our research provides a basis for understanding the role of X and other social media platforms in spreading health-related information about potential biases in medical devices such as pulse oximeters.

Audio Deep Fake Detection with Sonic Sleuth Model

Information dissemination and preservation are crucial for societal progress, especially in the technological age. While technology fosters knowledge sharing, it also risks spreading misinformation. Audio deepfakes—convincingly fabricated audio created using artificial intelligence (AI)—exacerbate this issue. We present Sonic Sleuth, a novel AI model designed specifically for detecting audio deepfakes. Our approach utilizes advanced deep learning (DL) techniques, including a custom CNN model, to enhance detection accuracy in audio misinformation, with practical applications in journalism and social media. Through meticulous data preprocessing and rigorous experimentation, we achieved a remarkable 98.27% accuracy and a 0.016 equal error rate (EER) on a substantial dataset of real and synthetic audio. Additionally, Sonic Sleuth demonstrated 84.92% accuracy and a 0.085 EER on an external dataset. The novelty of this research lies in its integration of datasets that closely simulate real-world conditions, including noise and linguistic diversity, enabling the model to generalize across a wide array of audio inputs. These results underscore Sonic Sleuth’s potential as a powerful tool for combating misinformation and enhancing integrity in digital communications.

Therapeutic Patient Education and Eating Habits: A Challenge in Caries Disease.

Dietary Factors and Oral Health: Risky dietary behaviors, particularly excessive sugar consumption, significantly contribute to dental caries. Dental practitioners are tasked with detecting and managing these behaviors to effectively treat caries and prevent recurrences. Although dietary assessment tools exist to identify such behaviors, they have limits. Furthermore, traditional methods, focused on information dissemination and advice, often fall short in promoting sustainable changes in patient behavior toward oral health. From our perspective, there is a necessity to integrate educational approaches with therapeutic management for enhancing the ability current and future dental practitioners to effectively care for their patients' oral health needs. Discussion: Specific educational models have been developed for patients with chronic diseases, through Therapeutic Patient Education (TPE), defined as helping patients acquire or maintain the skills they need to best manage their lives with a chronic disease. Future Directions: By incorporating TPE into dental practice, oral health professionals can empower patients to take control of their eating habits and reduce their risk of caries disease. This holistic approach addresses both the carious lesions and underlying causes of tooth decay, leading to better oral health outcomes for patients.