Online News Sources Research Articles

What We Convey When We Talk About Public Health Crisis: A Case Study of Global Media Coverage of COVID-19 Using Big Data Approach

This article addresses the urgent need for a comprehensive understanding of the global media coverage of Coronavirus Disease 2019 (COVID-19) by conducting a massive-scale analysis using the Global Database of Events, Language, and Tone. With a dataset encompassing 53,967,878 news items from 4,708 online news sources across 67 countries, the study spans the entire trajectory of the pandemic from the first reported case on December 31, 2019, to September 11, 2020. The analysis aims to surpass the limitations of previous research by offering a worldwide perspective on COVID-19 media coverage over a significant timeframe. Additionally, the paper explores the intricate relationships between media portrayals and the epidemiological situations in primary countries. By examining the media's impact on public perceptions, the study contributes valuable insights to the ongoing discourse on COVID-19, addressing the limitations of prior research and emphasizing the importance of a nuanced and expansive approach to understanding the role of media in the context of global health crises.

Особенности функционирования транспортной терминосистемы в современных англоязычных новостных интернет-ресурсах

This article is devoted to the problems of English transport terminology, as well as the peculiarities of its functioning. The purpose of the study is to determine the features of the functioning of English–language transport terminology based on the material of English-language news resources covering the state of transportation. The scientific novelty of this study lies in its exploration of the unique characteristics of the transport terminology system, as revealed for the first time through an analysis of English-language online news sources that focus on specific modes of transportation. In the article, 532 transport terms selected from media texts were divided into thematic groups, classified according to partial criteria, and the peculiarities of their functioning were revealed. As a result of the study, it was found that the terms identified in the analyzed material relate to general transport, but their meaning is specified due to attributive units, which causes their transition to a narrowly sectoral terminology. The extralinguistic processes aimed at the implementation of practices for the development of environmental friendliness in the transport industry are reflected in the functioning of terminological phrases formed by combining transport and environmental terms. It is revealed that the specifics of the considered transport terminology are diffusion processes, the reason for which is the transition of a significant part of it into the category of commonly used vocabulary.

Ethnic and racial violence and violations in the context of the Brazilian democratic crisis: a study of Black and Quilombola populations

ABSTRACT This article addresses the question of how the recent political context of Brazil shapes violations of various kinds against Quilombola communities in Brazil. Using data from online news sources, we track violations from 2016 to 2020 related to land disputes, physical attacks and threats, and environmental issues. We show that, despite the legal rights accorded to these communities since the 1988 constitutional reform and subsequent processes of democratisation, vested interests in the agricultural lobby and a later authoritarian turn, especially after 2016, led to a dismantling of social and economic policies for Quilombos. The violations suffered by these communities result from the denial of their collective identities as constitutional subjects and the non-recognition of their dignity, which are the product of historical processes of inferiorisation that have treated some people as non-subjects or not eligible to bear rights, based on colonial classifications but still present in the dominant society.

Media Monitoring oleh Divisi Informasi di KJRI Johor Bahru

This study aims to analyze the media monitoring activities carried out by the Information Division at the Consulate General of the Republic of Indonesia (KJRI) in Johor Bahru. These activities are crucial for understanding how information circulating in the media influences the image and policies of the KJRI, as well as identifying issues relevant to Indonesian citizens in Malaysia. The study employs a descriptive qualitative method with data collection techniques including direct observation, in-depth interviews, and document analysis. The results of the study indicate that the Information Division at KJRI Johor Bahru has implemented various effective strategies in media monitoring, including the use of digital tools to monitor various media platforms. KJRI Johor Bahru conducts Media Monitoring, referred to as Weekly Reports (Lapming), in accordance with the definition of media monitoring activities by Friedel and Lukman (2020). Meanwhile, media tracking at KJRI Johor Bahru involves monitoring various credible online news sources, and media clipping at KJRI Johor Bahru aims to organize news collected from online sources and social media.

The 2024 General Elections in Indonesia: Issues of Political Dynasties, Electoral Fraud, and The Emergence of A National Protest Movements

This research aims to explain the phenomenon of political dynasties, electoral fraud, and protest movements during the 2024 General Elections in Indonesia. By using a qualitative descriptive method, this research focuses on aspects related to the main factors of the emergence of political dynasties, electoral fraud, and protest movements in the 2024 election based on secondary data obtained from online news sources. Data collection process was carried out through reading the news articles using the keywords “political dynasties”, “electoral fraud”, “protest movements”, and “2024 General Elections”. Data analysis was conducted through content analysis of news texts to obtain accurate data, descriptive insights and thematically explore the data inductively. The findings in this study show that the issues of political dynasties, electoral fraud, and the national protest movements in the 2024 General Elections are a series of interconnected phenomena. In addition, this study also reccomends further research on the importance of understanding public perceptions of political dynasties, the issue of electoral fraud, and protest actions against active voters in the 2024 General Elections using an empirical approach.

Using and Believing—Exploring Public Trust in Online News Sources in China

ABSTRACT This research investigated online news consumption and public trust in online news sources in China. It aims to understand the dynamic relationship between media use and media trust in China, with a contrast between official media and social media. In this study, we measured the frequency of use and credibility of 50 online news sources categorized into five groups and two social media platforms, WeChat/Weibo, with a survey (N = 585). The results indicated people used and trusted each online news source group differently. Social media were used most often and the reliance on official media was less. Habitual use of social media enhanced its credibility; however, official media were trusted the most, followed by news portals. This study advances the literature by identifying the online news consumption pattern in China and examining the public trust in online news sources where the government's control of media extends online. This study reveals how the public perceives the legitimacy of the state via official information systems and how technologically-driven media transformations have produced vibrations among the public. The findings also provide important implications for practitioners to understand the trust structure of online news media and conduct targeted regulation.

Analisis Penyebaran Hoax Di Media Sosial Dan Dampaknya Terhadap Masyarakat

The spread of hoaxes on social media has become a serious problem in society. This research aims to analyze the factors that cause the spread of hoaxes, the characteristics of hoax content, a well as their impact on society. The research method used is the study of literature and content analysis from various online news sources. The results showed that the main factors of the spread of hoaxes were lack of digital literacy., economic motivation, and political polarization. Hoax content generally spreads quickly, has sensational titles, and contains inaccurate information. The impact of hoaxes on society includes confusion, social conflict, and a decline in public trust. This research concludes that comprehensive efforts from the government, media, and the public are needed to overcome the hoax problem. This research aims to analyze the causes, patterns of spread, and the impact of hoaxes on social media on the community. The research methods used are literature studies and content analysis from various trusted sources. Patterns of spreading hoaxes generally utilize sicial media algorithms to achieve a wide reach quickly. The negative impact of hoaxes on society is very diverse, ranging from triggering social confilcts, affecting public opinion, to threatening political stability and national security. This shows the urgency of handing hoaxes comprehensively, involving the role of government, social media platforms, and the public.

OPTIMIZING LONG TEXT CLASSIFICATION PERFORMANCE THROUGH KEYWORD-BASED SENTENCE SELECTION: A CASE STUDY ON ONLINE NEWS CLASSIFICATION FOR INDONESIAN GDP GROWTH-RATE DETECTION

Efficiently managing lengthy textual data, particularly in online news, is crucial for enhancing the performance of long text classification. This study delves into innovative approaches to streamline the Gross Domestic Product (GDP) computation process by harnessing modern data analytics, Natural Language Processing (NLP), and online news sources. Leveraging online news data introduces real-time information, promising to improve the accuracy and timeliness of economic indicators like GDP. However, handling the complexity of extensive textual data poses a challenge, demanding advanced NLP techniques. This research shifts from traditional word-weight-based methods to keyword-based extractive summarization techniques to address this. These tailored approaches ensure that selected sentences align precisely with specific keywords relevant to the research case, such as GDP growth rate detection. The study emphasizes the necessity of adapting summarization methods to capture information in unique research contexts effectively. According to classification results, the implementation of sentence selection successfully demonstrated improved performance in terms of classification accuracy. Specifically, there was an average accuracy increase of 0.0226 for machine learning and 0.0164 for transfer learning models. Additionally, in terms of computational efficiency, sentence selection also accelerates processing time during hyperparameter tuning and fine-tuning, as observed using the same computational resources.

Navigating digital tourism governance: a case study of branding strategies in the Mandalika special economic zones

The purpose of this research is to analyze how digital Tourism on Branding the Mandalika Special Region in West Nusa Tenggara; this investigation uses a descriptive methodology combined with a qualitative approach, as well as previously published literature and online news sources as well as secondary data obtained from related agencies. Most importantly, take advantage of the Nvivo 12 plus program to analyze the data results. The findings of this study indicate that the use of information and communication technology to promote Special Economic Zones through digital tourism, utilizing platforms such as websites, YouTube, Facebook, TikTok, Instagram, and the West Nusa Tenggara Tourism Office website, is a viable strategy for increasing tourism. Indonesian tourism industry. ITDC and National Council of Special Economic Zones websites. Government Regulation Number 52 of 2014 identifies two main focus topics, namely tourism areas and special economic areas, and prioritizes several initiatives. Development management in accordance with statutory regulations. PP Number 40 of 2021 discusses three important things: human resources and infrastructure, two facilities, and SEZ convenience for three commercial organizations. The finding of human resources and infrastructure is considered to be the main driver for branding the Mandalika Special Economic Zone in this policy.

Online and Social Media News Usage, Conspiratorial Attitudes and Fear of Terrorism

Are individuals who obtain their news from online news sources or from social media more likely to fear terrorism? If so, why is this the case? Based on the 2021 Chapman Survey of American Fears, this study draws two key conclusions. First, subjects who more frequently use online and social media news sources exhibit higher levels of fear of terrorism. Second, the relationship between online and social media news reliance and fear of terrorism is mediated through conspiratorial attitudes. These findings are robust to the inclusion of a host of demographic and attitudinal control variables.

Drivers of vulnerability to medicine smuggling and combat strategies: a qualitative study based on online news media analysis in Iran

BackgroundMedicine smuggling poses a serious public health threat, limiting patients’ safe and timely access to this essential resource. Thus, this study aims to identify the factors contributing to the vulnerability to medicine smuggling and propose effective strategies to combat this issue in Iran.MethodsAn analysis of news media was conducted using qualitative content analysis. News text items related to medicine smuggling were retrieved from various online news sources between March 21, 2017, and May 21, 2023. To select health-oriented and general online news stations, news agencies, and newspapers, the purposeful sampling method with a maximum variation strategy was used. The selected sources included Mehr News Agency, Khabar Online, Islamic Consultative Assembly News Agency (ICANA), Islamic Republic News Agency (IRNA), Iranian Students News Agency (ISNA), Hamshahri, Donya-e-Eqtesad newspapers, Webda, Sepid Online, and Iran’s Food and Drug Administration News Agency (IFDANA). All data coding was manually done using Microsoft Excel software version 2016.ResultsA total of 277 news articles were found to meet the established criteria for inclusion. The analysis revealed four main themes, each with several sub-themes, that shed light on the factors that drive vulnerability and the strategies to combat medicine smuggling. These themes are the economic environment, government and stewardship, information technology systems, and socio-cultural factors. The economic environment emerged as the most significant theme, encompassing medicine selection, reimbursement, and procurement, all of which affect the smuggling of pharmaceuticals in Iran.ConclusionTo combat medicine smuggling, it is important to adjust policies based on the identified vulnerabilities. Effective strategies to reverse pharmaceutical smuggling include capacity building of pharmaceutical manufacturing companies, implementing regulated and enhanced supervisory and rulemaking policies, strengthening health insurance, improving e-infrastructure, and increasing public awareness through collaborative approaches involving various stakeholders within and outside the health system.

RSS Feeds Filtering from multiple sources using automated techniques of Natural Language Processing

The Internet's rapid growth has resulted in a surge of information, posing challenges for users trying to stay updated. The World Wide Web, with its diverse websites updated at varying intervals, necessitates efficient categorization of news articles. As the number of online news sources continues to rise, categorization becomes crucial for users to find information easily. Given the overwhelming volume of digital media information, categorizing news using algorithms and assigning multiple tags based on their category becomes essential. In the modern digital era, users face difficulties filtering and accessing relevant content tailored to their preferences due to the abundance of information from various sources. This study employs Natural Language Processing (NLP) methods for automated content filtering of RSS feeds. The developed system extracts feeds via RSS, generates headings and summaries, and employs NLP for categorization. This research has broad implications, offering opportunities for improved information management, personalized recommendations, and informed decision-making across diverse domains.

Ethio-Fake: Cutting-Edge Approaches to Combat Fake News in Under-Resourced Languages Using Explainable AI

The proliferation of fake news has emerged as a significant threat to the integrity of information dissemination, particularly on social media platforms. Misinformation can spread quickly due to the ease of creating and disseminating content, affecting public opinion and sociopolitical events. Identifying false information is therefore essential to reducing its negative consequences and maintaining the reliability of online news sources. Traditional approaches to fake news detection often rely solely on content-based features, overlooking the crucial role of social context in shaping the perception and propagation of news articles. In this paper, we propose a comprehensive approach that integrates social context-based features with news content features to enhance the accuracy of fake news detection in under-resourced languages. We perform several experiments utilizing a variety of methodologies, including traditional machine learning, neural networks, ensemble learning, and transfer learning. Assessment of the outcomes of the experiments shows that the ensemble learning approach has the highest accuracy, achieving a 0.99 F1 score. Additionally, when compared with monolingual models, the fine-tuned model with the target language outperformed others, achieving a 0.94 F1 score. We analyze the functioning of the models, considering the important features that contribute to model performance, using explainable AI techniques.

Sustaining Tourism during War: A Case of Russia and Ukraine

This study investigates the underlying motivation for visiting Russia and Ukraine based on which policymakers can frame policies and campaigns around tourism in these war-ravaged countries. Finding ways to promote and sustain tourism in such destinations can immensely contribute to the economy of these nations. The study was conducted by collecting both primary and secondary data. For secondary data, online news sources and Google Trends were employed; for primary data, responses were collected from 207 Indian subjects through an online questionnaire for eliciting responses from a diverse set of subjects a broader reach. The results indicated a clear impact on rising interest of tourists in these countries despite the popular assumption that war might deter tourists from entering such destinations. The subjects admitted that the war ignited their curiosity in Ukraine's people, culture and destinations. This research is the first of its kind, which explores the motivation of tourists to travel to Russia and Ukraine while they are still at war and the ways in which countries can sustain tourism during the period of war.

Evaluating LDA and LSA for Topic Modeling in the Indonesian Natural Disaster

Topic Modeling is a method for analyzing topics, documents, and articles in Natural Language Processing. The LDA (Latent Dirichlet Allocation) and LSA (Latent Semantic Analysis) algorithms are widely used in topic modelling. This study focuses on analyzing articles related to natural disasters in the Indonesian language. The dataset for this study was obtained through data scraping from Google News, which served as a container for several articles and online news sources. The research method is divided into several stages: dataset scraping, data preprocessing, topic modelling with LDA and LSA, model visualization, and model evaluation. The results of the research show that both algorithms can generate topics on datasets relevant to natural disasters in Indonesia such as floods, earthquakes, landslides, tsunamis and so on. From the evaluation results using Coherence Scores, it is found that LDA has better performance than LSA seen from Coherence Scores in modeling topics related to Natural Disasters in Indonesia. The results of this research are expected to provide convenience for information system developers in terms of monitoring natural disasters in Indonesia and make it easier for researchers who want to effectively read a document based on the disaster related in the document.

FOSTERING THE DIGITAL GENERATION: CHALLENGES IN HIGHER EDUCATION INSTITUTIONS DURING THE FOURTH INDUSTRIAL REVOLUTION (IR4.0) EDUCATIONAL LANDSCAPE

This paper deliberates on the construction of the digital generation in contemporary times across various aspects of life, emphasizing the imperative for concerted efforts to advance the nation's capabilities for competitive positioning on the global stage. The research objectives explore the role of Higher Education Institutions (HEIs) in fostering digital technology advancements. Steps toward digital technology progression necessitate interventions such as prioritizing technology-centric courses for students. Discussed issues encompass (i) the role of HEIs in advancing technology, (ii) the significance of digital technology utilization, (iii) the impact of digital technology development among students, and (iv) factors influencing the rapid evolution of technology in tandem with the pace of the era. Data for the study were gathered from diverse sources, including research findings in journals, scholarly writings, online news sources, public forums, and reference books. The study successfully identifies means through which the digital generation can be nurtured, guiding them through appropriate channels to discern the positive and negative ramifications of digital revolution actions in the present generation. The use of digital technology holds potential benefits for users, enhancing individual knowledge and fostering critical thinking skills. The application of digital technology can significantly impact the technological development among graduates, empowering them with digital proficiency. These skills prove invaluable in employment pursuits, given the ubiquitous incorporation of digital technology across various professions today. The rapid technological advancements driven by factors such as high curiosity towards technology have led the younger generation to explore and employ various digital tools, such as smartphones. Amidst efforts to cultivate the digital generation, challenges emerge, with one prominent issue being the misuse of digital technology. Study findings reveal that various initiatives, particularly governmental efforts, have been undertaken to address digital technology misuse, contributing to cybercrimes and online fraud. Consequently, societal perceptions towards digital technology have become increasingly negative. These challenges impede governmental endeavors to foster a digital generation. Thus, in alignment with the identified issues, this study underscores the shared responsibility of all stakeholders in realizing the nation's vision to produce an advanced digital generation in the present era.

Is mental health normalised in Norwegian news media?

News media can influence audience opinions. Thus, the media have enormous potential and responsibility when writing about societal issues, such as mental health. Mental health coverage has traditionally been criticised for creating stigma, as the topic is often presented in combination with violence and crime. Since the 1990s, researchers have found that more positive representations challenge negative portrayals, and that such representa- tions change the audience’s attitudes towards the issue. Few studies on the topic have been conducted in Norway; therefore, one cannot confirm or deny whether the exact coverage change is occurring. Using a quantitative framing analysis, this study argues that mental health issues were normalised in the two most-read online news sources, Verdens Gang (VG.no) and Norsk Rikskringkasting (NRK.no), in 2018–2021.

The Challenges of Media Education in the Digital Era

The advent of the digital era has ushered in a transformative landscape in the field of media, necessitating a reevaluation of media education strategies. This study explores the multifaceted challenges facing media education in the digital age, with a focus on the evolving media landscape, technology integration, pedagogical approaches, and the role of educators. In today’s digitally connected world, the media ecosystem has become more complex and dynamic than ever before. The proliferation of social media platforms, online news sources, and user-generated content has fundamentally altered the way information is produced, disseminated, and consumed. Consequently, media education faces the challenge of keeping pace with the rapid evolution of digital media, ensuring that students are equipped with the critical thinking and media literacy skills necessary to navigate this ever-changing landscape. Another key challenge lies in the integration of technology within media education. While digital tools offer unprecedented opportunities for creativity and engagement, they also pose challenges related to accessibility, the digital divide, and the need for educators to continuously update their technological skills. Finding the right balance between traditional and digital media instruction is essential for effective pedagogy. Pedagogical approaches in media education must evolve to address the changing needs of students in the digital era. Educators must adapt their methods to foster critical thinking, digital literacy, and media ethics. Encouraging students to become discerning media consumers and responsible content creators is paramount to their success in the digital age. Furthermore, educators themselves face the challenge of professional development to stay abreast of emerging trends, technologies, and best practices in media education. Continuous learning and collaboration with industry professionals are essential to equip educators with the knowledge and skills needed to guide students effectively. The challenges of media education in the digital era are manifold, encompassing the dynamic nature of the media landscape, technology integration, evolving pedagogical approaches, and the ongoing development of educators themselves. Addressing these challenges requires a concerted effort from educational institutions, policymakers, and industry stakeholders to ensure that media education remains relevant, effective, and capable of preparing students for the complexities of the digital age.

Online Media Perspective on Trans Jogja as a Public Service in Yogjakarta City with Code Modeling

Transjogya buses are currently not optimal. This research to analyze public perceptions of the importance of Transyogya buses as public transportation in the Special Region of Yogyakarta. This research method uses qualitative research methods by collecting data from online news media, online magazines and other online news sources. The method used modelling coding is to use Nvivo12 software by capitalizing the code results to get analysis results. His research data, it can be seen that by analyzing the agenda setting teory which consists of the media agenda with an online media perspective, it shows that the problems that are often discussed by the mass media related to Transyogya Transportation are Bus Stop Problems, Transyogya Problems and Portable Bus Stop Problems.

An analysis of science communication about COVID-19 vaccination in Portuguese online news media

This study aimed to analyze the usage of scientific concepts and technical terms related to COVID-19 vaccination in Portuguese online news sources and examine citizens' comprehension of these terms. A retrospective descriptive study was conducted, examining Portuguese news articles about COVID-19 vaccination from November 2021 to January 2022. Scientific terms were extracted from 190 articles, and seven citizens provided identification and brief definitions of familiar terms. Approximately 68% of the news articles involved collaboration with researchers or health professionals. A total of 144 scientific terms were identified in 77% of the articles, with more than half (57.54%) of these terms being unknown or inadequately defined by the citizens consulted.