Rapid Dissemination Of Information Research Articles

The impact of misinformation on social media in the context of natural disasters

Abstract Background Rapid dissemination of information during natural disasters plays a crucial role in managing public responses and ensuring safety. Social media can be a tool to disseminate lifesaving information but is also a ground for the propagation of misinformation. This study examines the impact of misinformation spread through social media in the context of natural disasters and explores related dynamics, effects, and countermeasures. Methods Cochrane and PRISMA recommendations were used for protocol development and sound reporting. Key terms related to misinformation, social media and natural disasters were used, with the search conducted in PubMed, and without time limitation for adequate capture. Only research papers in English were eligible for inclusion. Journal and article quality were considered. No restriction was imposed on country or age of target populations. Results Findings reveal significant influence of misinformation on public behaviour during disasters, often leading to panic and hindering effective disaster management. Specific characteristics of misinformation were identified, incl. its origins and spread mechanisms; proximity -both spatial and social- was found to be a critical factor in terms of spread and reach. Emerging evidence highlights the importance of trusted sources to effectively counter misinformation, yet response time remains a critical challenge. Technical detection of misinformation can help combat it but requires further enhancements for real-time application in diverse disaster scenarios. Conclusions Misinformation on social media poses complex challenges to disaster management, affecting both individual and societal resilience. Proactive communication strategies are critical, as is the development of advanced verification tools, and public education strategies to combat misinformation. Future research should focus on refining strategies to enhance disaster preparedness and response, ensuring a resilient and well-informed public.

Social Media and Digital Inequity: Reducing Health Inequities by Closing the Digital Divide

As its usage has grown, social media has positively and negatively impacted public health. Although social media presents known harms to mental health and spreads misinformation, it also offers rapid dissemination of public health information, expanded access to health resources, and a robust source of health information. However, these benefits are not equitably shared due in part to the “digital divide” of unequal access and use of information and communication technologies. Measurable inequalities in digital access exist among regions, with an eight-fold difference between Central Africa (9.8% social media penetration) and Northern Europe (80.2% social media penetration). Digital inequalities also differ by gender, age, and socioeconomic classes within countries. Increased digital access has been positively associated with improved health information and outcomes related to chronic diseases, infectious disease outbreaks, and reproductive health. Given the expanding role of social media in public health and the emerging evidence on the health benefits of digital access, we argue for reducing digital inequities by (1) creating an enabling government policy and regulatory environment that views digital health access as a social determinant of health; (2) targeting public and private investments to expand digital access for underserved regions and populations; (3) making digital access and use affordable to low-resource populations; and (4) improving digital competency among these groups through digital literacy programs.

Modality deep-learning frameworks for fake news detection on social networks: a systematic literature review

Fake news on social networks is a challenging problem due to the rapid dissemination and volume of information, as well as the ease of creating and sharing content anonymously. Fake news stories are problematic not only for the credibility of online journalism, but also due to their detrimental real-world consequences. The primary research objective of this study is: What are the recent state-of-the-art modalities based on deep learning to detect fake news in social networks. This paper presents a systematic literature review of deep learning-based fake news detection models in social networks. The methodology followed a rigorous approach, including predefined criteria for study selection of deep learning modalities. This study focuses on the types of deep learning modalities; unimodal (refers to the use of a single model for analysis or modeling purposes) and multimodal models (refers to the integration of multiple models). The results of this review reveal the strengths and weaknesses of modalities approaches, as well as the limitations of low-resource languages datasets. Furthermore, it provides insights into future directions for deep learning models and different fact checking techniques. At the end of this study, we discuss the problem of fake news detection in the era of large language models in terms of advantages, drawbacks, and challenges.

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.

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.

Development and Implementation of a Comprehensive Initiative to Educate Healthcare Providers and Patients in the United States about the Risk of Drug-Drug Interactions Associated with Nirmatrelvir/ritonavir during the COVID-19 Pandemic

This case study describes the development of a comprehensive drug-drug interaction (DDI) education initiative for nirmatrelvir/ritonavir (Paxlovid™) during the COVID-19 pandemic. Following Emergency Use Authorization in December of 2021, the rapid dissemination of information on identification and management of DDIs was needed to ensure appropriate use of nirmatrelvir/ritonavir when treating patients with COVID-19 who were at an increased risk of progression to severe illness. The initiative included comprehensive outreach activities to compliantly inform healthcare providers and patients through the development of various educational materials and omnichannel engagement strategies. This case study may serve as an example to guide best practices for therapeutics requiring timely and comprehensive approaches to the dissemination of medical information in the future.

Weaponization of Social Media – Challenges and Responses

The use of social media as a tool for manipulation poses significant challenges worldwide, affecting public sentiment, intensifying divisions, and endangering democratic systems. This article investigates these issues and examines the responses from governments, tech companies, and civil society. The swift evolution of social media has changed the way we communicate while also facilitating the rapid dissemination of false information and polarizing narratives, threatening societal unity. Researchers emphasize the impact of algorithms in creating echo chambers and filter bubbles that deepen polarization. Additionally, malicious actors take advantage of these platforms to propagate disinformation, sway elections, and incite violence. In response, initiatives such as enhanced fact-checking, media literacy programs, and better content moderation by social networks are being implemented. Regulatory actions to promote transparency and accountability are also recommended, alongside international collaboration to combat cross-border online threats. A comprehensive strategy involving technology, regulation, international co-operation and community resilience is essential to protect democratic ideals in our interconnected society.

Navigating uncertain waters: 12 tips for medical department social media engagement under shifting platform landscapes

Social media has revolutionized how society receives and transmits information in the digital age, including healthcare. While the future of social media platforms remains uncertain, the benefits of social media for healthcare organizations, departments, and divisions are clear when compared to traditional communication methods, including improved recruitment efforts, increased promotion of faculty work, rapid dissemination of information and education innovations, and accelerated professional networking. Consequently, preferred platforms may shift but the benefits of social media likely cement it, in one form or another, in medical education and society at large. The strategic development of a social media presence at the department level can be opaque and overwhelming amidst varying mediums, yet the benefits of use have never been more important. Here, we present 12 tips for developing a successful social media presence as a healthcare department, addressing the creation of a purposeful social media strategy and crucial considerations for any platform, current or future, at all levels of development.

Support from Social Media during the COVID-19 Pandemic: A Systematic Review.

The social distancing measures in response to the COVID-19 pandemic have transformed people from social to isolated individuals. During that time, social media became a useful tool for satisfying people's need for social interaction. Previous systematic reviews, however, have focused largely on the negative impact of social media use and ignored the positive side. Hence, this systematic review examined the role of social media use in providing support-be it social, emotional or informational-during the pandemic. Four databases were systematically searched, and the selection procedure followed the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines. Protocol registration: PROSPERO (CRD42022367903). A total of 20 papers were deemed eligible for data extraction. The findings showed that active engagement on social media contributed significantly to maintaining social capital and collective resilience amidst social restrictions. The emotional support obtained from social media was proven effective in alleviating feelings of loneliness and isolation. Also, social media facilitated the rapid dissemination of information and the grassroots mobilization of support by overcoming bureaucratic hurdles and addressing urgent community needs. This review concluded by highlighting the transformative potential of social media in crisis contexts and suggesting implications for mental health interventions and community resilience strategies.

Turkish Adaptation of Social Media Questionnaire for Nursing Training.

Background and Purpose: The use of social media in education has many effects such as rapid dissemination of information, crowdsourced information sharing, learning, and social interaction. In the study, it was aimed to determine the validity and reliability of the Social Media Questionnaire for Nursing Training (SMQNT), which can be used to determine the effect of social media in nursing education. Methods: The data of this methodological study were obtained from 262 nursing students. Confirmatory factor analysis (CFA) was used to determine the scale's factor structure, while Cronbach's alpha (α) coefficient, test-retest method, and split-half reliability method were used for reliability. Results: In line with the results of the CFA, it was determined that the scale had 13 items and a three-factor structure as "attitudes," "use," and "contrast information." Similar to the original scale, a three-factor establishment was approved. SMQNT Cronbach's α coefficient was found to be 0.87, while Cronbach's α coefficient was found to be 0.658 for the "F1" factor, 0.760 for the "F2" factor, and 0.688 for the "F3" factor. Conclusions: As a result of this study, the Turkish form of SMQNT was a valid and reliable measurement instrument.

Prototype Aplikasi Real Count Pemilihan Kepada Daerah Pada Badan Pengawas Pemilihan Umum Kota Palembang

PILKADA (Regional Head Election) and its deputy are routine activities carried out by each region to carry out democratic government activities. The Provincial KPU carries out Pilkada, and Regency / City KPU is collectively responsible for implementing general elections, supervised by the Provincial Bawaslu and Regency / City Bawaslu. The Palembang City Bawaslu's task in the vote counting process is to oversee the movement of recapitulation data from the TPS Supervisor level, Village / Sub-district Supervisors (PKD), and District Election Supervisory Committee (Panwascam) to the City Bawaslu so that there is no vote inflation which is considered dishonest and unfair. The process of collecting C1 and C-Plano form data to be recapitulated from the lower level to the upper level at the Palembang City Bawaslu collected, the process will take a relatively long time if done manually, especially limited by the long distance and poor natural conditions. In line with the development of increasingly modern technology, considering the need for data and the need for rapid dissemination of information on Pilkada results, in this study, the author will design Real Counting (also known as parallel vote aggregation) as a helpful way to monitor and accelerate the vote aggregation process in the form of an application prototype. This study aims to provide a prototype design for the Pilkada real count application at Bawaslu Palembang City. The software development method used in this study is the waterfall model method, which consists of analysis, design, coding, testing, and support or maintenance.

Shaping Social Proof: A Fission Marketing Model Based on the Herd Mentality Take Pinduoduo, for an Example

This study takes Pinduoduo as an example to explore the influence of herd psychology on consumer decision-making in fission marketing. Fission marketing uses consumer social networks to realize the rapid dissemination of information, in which the herd psychology plays an important role. Through the questionnaire survey, this study analyzes the motivation and effect of Pinduoduo users participating in the fission marketing activities such as "Kanyidao". In that context, "Kanyidao" means helping others bargain. The results show that the majority of respondents participated in activities motivated to save money or make money, and tend to learn about activity information through friends or software channels. User-sharing activity links promote social fission and achieve a rapid growth in the number of users. The research conclusion points out that the herd psychology plays a significant role in the fission marketing, and the fission marketing can effectively expand the market share by stimulating the consumers' enthusiasm for participation.

Prediction of psychological intervention for college students in digital entertainment media environment based on artificial intelligence and parallel computing algorithms

In the era of digital entertainment media, the rapid dissemination of information and the widespread application of social media have a huge impact on user behavior and psychology. For students, the experience of digital entertainment content may have potential adverse effects on their mental health. The aim of this study is to propose a prediction model of university students’ psychological intervention based on optical network transmission based on parallel computing algorithm, in order to improve the computational efficiency and accuracy of the model. Then, a large number of psychological data of college students are collected, and feature extraction and model training are carried out by using machine learning algorithms. Finally, the predictive model of psychological intervention is simulated by parallel computing algorithm. The experimental results show that the optical network transmission based on parallel computing algorithm has high computational efficiency and accuracy in the prediction model of psychological intervention of college students. The model can reliably predict and evaluate the effect of psychological intervention of college students, provide an effective simulation tool for psychological intervention of college students, and help realize personalized and efficient psychological intervention measures.

CRISIS MANAGEMENT IN THE DIGITAL AGE

This study explores the impact of digital technologies on crisis management through a qualitative analysis of secondary data, including literature, reports, and case studies. Findings reveal that social media facilitates rapid information dissemination and real-time engagement, while data analytics enable proactive monitoring and crisis prediction. The study also highlights the role of transparency in fostering public trust and the challenges posed by misinformation. The analysis includes insights from Uzbekistan's digital transformation, emphasizing the need for continuous adaptation in crisis management practices.

Aspek Hukum Pengaruh Transformasi Digital Terhadap Praktik Telemedicine Di Indonesia

Health is a basic human need that continues to increase along with the progress of the times. Technological advances and lifestyle changes have led to a variety of new diseases, increasing the need for health services. Indonesia, with the fourth largest population in the world (272,229,372 people) and 10.14% of the population poor in 2021, faces significant health challenges. The COVID-19 pandemic has exacerbated the situation by limiting access to health services. Barriers to access, unequal distribution of services, and a shortage of doctors hinder efforts to realize the welfare of citizens as mandated by the 1945 Constitution. However, advances in information and communication technology have brought significant benefits in the health sector. Information technology has had a major impact on health and medicine, enabling the rapid, efficient, and accurate dissemination of information. One important development is the practice of telemedicine, which offers innovative solutions in health care.

Exploring scholarly perceptions of preprint servers

Introduction. Preprint servers play an important role in scholarly communication. The study investigates scholars’ engagement, experiences, and perceptions regarding the use of these servers, both as information sources and publishing venues This qualitative study seeks to extend our understanding of how these servers operate within the academic ecosystem and influence scholarly communication. Method. Data was collected through 32 semi-structured interviews with scholars from different disciplines, to explore their engagement, experiences and perceptions in using these platforms. Analysis. The data collected from these interviews underwent thematic content analysis using ATLAS.ti software. This analysis facilitated the organization and thematic examination of the textual narratives derived from the interviews. Results. In this study, scholars discussed their perceptions about the benefits of using preprint servers in scholarly work such as rapid dissemination of information and open access, but also raised concerns regarding the lack of peer review for the studies uploaded to these servers. Conclusion. These findings emphasize the growing, yet diverse, role preprint servers play in scholarly communication and their differential impact across academic disciplines.

Instagram for audience engagement: an evaluation of CERC framework in the GCC nations for digital public health during the Covid-19 pandemic

BackgroundIn this study, we investigate the utilization of Instagram by public health ministries across the Gulf Cooperation Council (GCC) nations to disseminate health-related information during the COVID-19 pandemic. With Instagram’s visual-centric approach and high user engagement, the research aims to investigate its critical yet complex role in information dissemination amid a health crisis.MethodsTo examine how Instagram communication strategies align with the CDC’s Crisis and Emergency Risk Communication (CERC) framework, we employ the content analysis method. This approach helps to evaluate the effectiveness and challenges of employing Instagram for health communication within a region known for its significant social media usage.ResultsFindings indicate that Instagram serves as a vital platform for the rapid dissemination of health information in the GCC, leveraging its visual capabilities and wide reach. The GCC ministries of health utilized Instagram to demonstrate a consistent and strategic approach to communicate essential COVID-19 related information. Kuwait and Bahrain were the most active of all the assessed ministries with respect to the number of engagement metrics (likes and comments). Most of the posts, as per the CERC framework, were informational and related to vaccine infection and death cases. The second most salient theme in line with the CERC framework was about promoting actions, followed by Instagram posts about activities, events, and campaigns.ConclusionsThe research underscores Instagram’s potential as a powerful tool in enhancing public health resilience and responsiveness during health emergencies in the GCC. It suggests that leveraging social media, with careful consideration of its affordances, can contribute significantly to effective health communication strategies in times of crisis.

Fog Computing and Industry 4.0 for Newsvendor Inventory Model Using Attention Mechanism and Gated Recurrent Unit

Background: Efficient inventory management is critical for sustainability in supply chains. However, maintaining adequate inventory levels becomes challenging in the face of unpredictable demand patterns. Furthermore, the need to disseminate demand-related information throughout a company often relies on cloud services. However, this method sometimes encounters issues such as limited bandwidth and increased latency. Methods: To address these challenges, our study introduces a system that incorporates a machine learning algorithm to address inventory-related uncertainties arising from demand fluctuations. Our approach involves the use of an attention mechanism for accurate demand prediction. We combine it with the Newsvendor model to determine optimal inventory levels. The system is integrated with fog computing to facilitate the rapid dissemination of information throughout the company. Results: In experiments, we compare the proposed system with the conventional demand estimation approach based on historical data and observe that the proposed system consistently outperformed the conventional approach. Conclusions: This research introduces an inventory management system based on a novel deep learning architecture that integrates the attention mechanism with cloud computing to address the Newsvendor problem. Experiments demonstrate the better accuracy of this system in comparison to existing methods. More studies should be conducted to explore its applicability to other demand modeling scenarios.

Perilaku Konsumtif Followers Akun @discountfess Pada Media Sosial X

Globalization brings many influences and changes in human life. The rapid dissemination of information obtained through social media can cause change. X account @discountfess as a forum that favolitates the dissemination of information quickly and widely can influence a person's behavior, one of wich is consumprive behavior. This study aims to describe the consumptive behavior of folllwers account @discountfess at social media X, using a descriptive method of quantitative approach. Sampling was accidental sampling with 96 followers @discountfess account. Data collection techniques include observation, questionnaire, documentation and literature study. The results show that the consumptive behavior of followers account @discountfess that causes impulsive purchases in the moderate category of 57%, irrational purchase in the moderate category with a percentage 60% and waste in the high category with a percentage 52%.

Fast-track development of an automated solar photovoltaic module detecting framework utilizing open-access multispectral satellite imagery

The southwest coast of Taiwan is an important habitat for migratory waterbirds. However, the use of fossil fuels has led to climate crises. As society's awareness of environmental issues increases, renewable energy including solar power has become an irreplaceable choice. Monitoring the spread of solar photovoltaic (PV) to mitigate its ecological impact has become an important task. Yet, acquiring information related to the geographic information of this renewable energy is often challenging. Remote sensing techniques for identifying the distribution of solar PV modules have been extensively discussed and published in recent years. However, the use of high-resolution imagery, powerful computational hardware, or high-precision but technically challenging frameworks, particularly in terms of computational costs, hinders the rapid updating and dissemination of information on solar PV distribution. The aim of this study is to rapidly develop a PVs detecting framework. To do so, by utilizing the spectral reflectance characteristics of PV modules, along with open-access Sentinel-2 satellite datasets, we selected false color images derived from Bands 8 (842 nm), 11 (1,610 nm), and 12 (2,190 nm). With the foundation of ArcGIS and the U-Net deep learning architecture, we developed a framework with low training costs, simple data processing, and short training time. Through syntheses of false color with different combinations of spectral bands, we achieved a PVs detecting framework with 94.5% accuracy, 0.94 F1 score, and 0.89 Kappa in aquaculture landscape. In our application in the southwest coast region, the overall accuracy reached 96%, with a 0.92 F1 score and 0.9 Kappa performance. This framework will facilitate the rapid monitoring of the spatial and temporal distribution of PV in Taiwan, accelerate social communication, and alleviate ecological impacts.