Online news

Even though coronavirus disease 2019 (COVID-19) vaccination has been done, preparedness for the possibility of the next outbreak wave is still needed with new mutations and virus variants. A near real-time surveillance system is required to provide the stakeholders, especially the public, to act in a timely response. Due to the hierarchical structure, epidemic reporting is usually slow particularly when passing jurisdictional borders. This condition could lead to time gaps for public awareness of new and emerging events of infectious diseases. Online news is a potential source for COVID-19 monitoring because it reports almost every infectious disease incident globally. However, the news does not report only about COVID-19 events, but also various information related to COVID-19 topics such as the economic impact, health tips, and others. We developed a framework for online news monitoring and applied sentence classification for news titles using deep learning to distinguish between ...

This study aimed to determine the discursive devices used in the news headlines, unravel the ideologies of the media practitioners, and reveal the insights that can be generated from the findings. Thirty headlines were gathered from five major online news portals in the Philippines: ABS-CBN, CNN Philippines, GMA, Interaksyon, and Rappler. This is a qualitative study that is seen from Fairclough's Critical Discourse Analysis (CDA) in 1995. Results showed ten discursive devices used in the headlines by media practitioners to attract attention from readers that may direct them to read the headline and read the entire article. It was also found out that the devices brought out media practitioners' ideologies. It was further found that writers or editors were objective or neutral, subjective or biased, and misleading. The selection of the words used in the headlines showed the political dispositions of the news practitioners who intentionally choose only those speeches or news that may create sensational feelings among the readers. The writer or editor's judgment angle re􀅭lected how he or she wanted the readers to perceive the issue. Furthermore, the results of this study may provide ideas to news consumers to not just read the headlines but read the entire article so that they may know if the headline matches its content and that they may be able to identify if the issue is true or not if it is slanted or sensationalized.

As advertising revenues continue to shrink and paywalls become ubiquitous, many publishers are now confronting a critical inflection point: subscription growth has stalled.

In this article I investigate how publishers can reignite momentum by rethinking strategies around access, value, and business models. Drawing on data from the Reuters Institute Digital News Report, WARC, Pew Research Center, and insights from industry thought leaders and journalists like Nic Newman, Federica Cherubini, Greg Piechota, Hanaa Tameez, and Madeleine White, the piece identifies three core strategies: bundling, new product development, and flexible payment models (e.g. micropayments, dynamic paywalls). I argue that subscription strategies are not failing — they are maturing — and that success in 2025 and beyond will depend on publishers’ ability to balance retention of core audiences with experimentation in pricing, partnerships, and content design.

Emotional triggers that elicit user behavior and sharing on social media platforms like Tik Tok, Instagram, and YouTube are becoming more and more important determinants of how digital content virality on these platforms affects users. This research looks at the role of certain high-arousal emotions, such as awe, anger, and nostalgia in the dissemination of online content. The paper relies on the existing literature, including empirical studies, theoretical research, and platform-specific studies to point out the interaction of negative resonance and social sharing mechanisms. Results indicate that content that evokes high levels of emotion is more apt to go viral, where awe inspires admiration and sharing, anger and discourse and repost and anger inspires active discourse and sharing, and nostalgia develops a personal relationship and return visit. Moreover, features of platforms, including short-form video content on Tik Tok and narrative contents on YouTube influence the consumption and distribution of emotional content. The strategic implications of the paper emphasize the need by marketers, content creators and social media strategists to maximize the number of people they reach and engage. Having formed the results of ten main works, this study adds to a better comprehension of the psychology of viral content and offers the framework under the influence of emotional stimulation usage on digital marketing campaign success

The growth in the practice of citizen journalism, propelled by increased Internet penetration and digital media adoption, has expanded the public sphere. Citizens leverage on social networks for their involvements in public discourse, especially politics. Political communication is one area that attracts massive citizens' participation through the reportage and analysis of, and commentary on political issues and events. In today's digital world, members of the public utilise citizen journalism as a veritable tool to promote their preferred candidates through content sharing. In their citizen journalism practices, they selectively use verbal and non-verbal narrative frameworkscalled frames-to construct and share news about political candidates, parties and programmes in ways that lead to meaning-making consequences among the audiencea process termed framing. The theoretical and empirical manifestations of framing in political communication have extended beyond the mainstream to digital media, with attendant pervasive effects of the latter. This paper theoretically discussed the roles of citizen journalism in expanding the public sphere, examined the social media perspective to political news framing, analysed frame building and its consequences and provided empirical evidences of framing consequences in politics. It concluded that, like in previous elections, cases of subjective framing were on the rise among political actors and supporters during the campaigns for Nigeria's 2023 Presidential election. The paper recommended media literacy, facts checking, responsible usage of social media and ethical reorientation as antidotes to negative framing consequences, which have implications on the success of democratic governance.

This research analyses the increasing impact of algorithms on the dissemination and consumption of news inside digital media platforms. Algorithms, specifically engineered to tailor material for individual users, are essential in determining the news presented, thereby affecting public opinion and democratic dialogue. The study examines current literature on algorithmic curation, filter bubbles, and echo chambers, and investigates the effects of algorithm-driven news feeds on information variety and user engagement. Empirical data from user behaviour analytics and case studies of prominent platforms such as Facebook and Google News are examined. Research indicates that whereas algorithms enhance engagement by customizing content according to preferences, they may also restrict exposure to varied viewpoints, thereby exacerbating ideological polarization. The report finishes with suggestions for openness and algorithmic accountability to maintain plurality in news consumption.

false rumors regarding the side effects of the polio vaccine quickly spread across various social media platforms, including Facebook, X (formerly known as Twitter), WhatsApp, and YouTube. This rapid spread of misinformation had a detrimental impact on Pakistan's efforts to eradicate polio. This essay sheds lights on two critical aspects related to polio vaccine misinformation on social media in Pakistan. First, it examines the current state of polio vaccine misinformation on social media and finds it a significant threat to public health, resulting in vaccine refusals, erosion of trust in public health institutions, distrust in science, and providing opportunities for anti-vaccination groups and individual advocates to target healthcare workers involved in polio eradication efforts nationwide. Second, it highlights the collaborative initiatives undertaken by relevant government institutions and social media companies, which have proven inadequate in effectively addressing the persistent dissemination of mis/disinformation, particularly on Facebook. Lastly, we suggest Pakistan should adopt a more inclusive approach of engaging all stakeholders, promote independent fact-checking initiatives, and increase health literacy among the target population about the risks and benefits associated with the polio vaccine.

This study analyzes how entrepreneurial native online newsrooms in Colombia are implementing digital technologies and innovation in their workspaces. The article uses technology studies and entrepreneurial journalism as frameworks to investigate eight relevant case studies. The method used in-depth interviews with the directors of these online media. Results show that native online outlets value people, quality of content, access to information, and journalistic standards more than digital technology and platforms. For them, innovation is not strictly related to implementing new technology, but it is somewhat linked to the type of journalistic innovation products they are creating. They believe they are an alternative voice to mainstream media content but use traditional outlets to distribute their stories and increase their relevance. The integration of users into their editorial process is a goal, but it is still limited.

The emergence of the internet and digital technology is bringing radical changes in the kind of media people consume. It used to be media more for the mass, but nowadays with the media consumption patterns change toward hyper-personalization, people feel more attached if media content caters to their interests individually which then results in the decline of mediato the diversity. What is to be seen however in this kind of context is the effects of audience fragmentation on print publications, and how the media are coping with the overabundance of online media causing their content to be irrelevant among a plethora of sources. Proprietary, and consumer consent, print publications are dealing with this issue on one hand, print advertising being the flagship vehicle to connect with the audience of a particular magazine without massive wastage on one hand; on the other hand, magazine publishers are fighting against duplicate magazines. The actual way forward is to tightly focus on the three main core areas of digital change and a related application, a local area, and a niche market, and to use analytics not only to identify, but to personally engage the individual market segments. Furthermore, this research highlights the fact that personalized content has to coexist with the issue of maintaining official journalistic standards in the media industry, which is more competitive than ever.

Recommender systems are the algorithms which select, filter, and personalize content across many of the world's largest platforms and apps. As such, their positive and negative effects on individuals and on societies have been extensively theorized and studied. Our overarching question is how to ensure that recommender systems enact the values of the individuals and societies that they serve. Addressing this question in a principled fashion requires technical knowledge of recommender design and operation, and also critically depends on insights from diverse fields including social science, ethics, economics, psychology, policy and law. This paper is a multidisciplinary effort to synthesize theory and practice from different perspectives, with the goal of providing a shared language, articulating current design approaches, and identifying open problems. It is not a comprehensive survey of this large space, but a set of highlights identified by our diverse author cohort. We collect a set of values that seem most relevant to recommender systems operating across different domains, then examine them from the perspectives of current industry practice, measurement, product design, and policy approaches. Important open problems include multi-stakeholder processes for defining values and resolving trade-offs, better values-driven measurements, recommender controls that people use, non-behavioral algorithmic feedback, optimization for long-term outcomes, causal inference of recommender effects, academic-industry research collaborations, and interdisciplinary policy-making. Rather than trying to reconcile these diverse frameworks, we take all of these to be concerned with values. We draw on the field of value-sensitive design to define values as "what a person or group of people consider important in life" (Borning and Muller, 2012, p. 1). Building real systems requires both deep technical practice and grounding in the realities of diverse human lives, including an understanding of the actual effects of deployed recommenders. Further, values and our understanding of them are constantly evolving, so the whole exercise depends on moral and philosophical reflection. Therefore, building human values into recommender systems requires a mix of conceptual, empirical, and technical work . Recommender systems are fundamentally social and collaborative both because many of their applications are designed to facilitate user-to-user interactions (e.g. social media) and because most recommender algorithms work by identifying patterns across users (e.g. "people who liked this also liked that"). Value-sensitive design uses the language of stakeholders, defined as those who are affected by design choices. It is their values which should matter in the design process, and recommenders are fundamentally multi-stakeholder systems which must simultaneously serve several types of stakeholders including users, content producers, platforms, and non-users . Their opinions must be considered or solicited in some way, and there are a wide variety of methods for doing so in various contexts including participatory design, user surveys, semi-structured interviews, and deliberative elicitation . To the extent that this feedback influences recommender algorithms, this is also an example of value-sensitive algorithm design This paper is not a comprehensive review. We do not think such a review would be useful at this time, both because it would be massive and because the field is evolving rapidly. Rather, the goal of this paper is to help readers get their bearings in this large and complex space. While not exhaustive, our approach is interdisciplinary and cross-sector. Our authors include experts in recommender systems, journalism, political science, law, psychology, AI alignment, technology policy, human computer-interaction and other fields. We also have substantial representation across academic, industry, and civil society sectors. Even this broad author cohort cannot reflect the entire range of this space, so we focus primarily on recommenders for social media, news content, and entertainment streaming services. However, many of the issues and approaches we highlight are broadly applicable to other important categories of recommender systems, including online shopping, targeted advertising, recruitment, healthcare, and education. We use the term "recommender systems" to focus on the core problem of personalized content selection across many domains. Recommender systems often operate without an explicit user query, though the user may also ask for more tailored recommendations (e.g., "politics podcast"). This contrasts with search functionality which requires an explicit query and where results tend to be much less personalized . Social media is a major application of recommender systems, but we note that the two are not synonymous. While most social media platforms do employ recommenders for content selection, the effects of social media depend on many design decisions beyond algorithmic content selection including the way the content is displayed, the various possible actions or controls made available to users, and the use of other navigation methods such as search or human-curated lists. Further, it is difficult to disentangle recommender effects from user

The substantial concern of this article is a question to what extent does the contemporary World Wide Web as an information retrieval system reflect key attributes of ideal hypertextual systems. The topic is relevant, since in the literature notions of hypertext and hypertextual systems are accompanied with strong implications not only for the ease and efficacy of access to information, but also for fostering democratisation, augmenting creativity and cooperativeness of human beings. After the brief presentation of the problem the paper focuses on the methodology of analysing this problem – definition of relevant dimensions of hypertext in the World Wide Web, their operationalisation and empirical verification. The latter is presented most thoroughly since it includes a procedure of generating a network of web sites in the Slovenian World Wide Web on the basis of approximately 1.8 million of web pages, identified by search system Najdi.si. After the definition of units and relations...

Research in news recommendation, like other areas of recommender systems, focuses heavily on the utility of recommendations for the consumers of news, that is, the users of apps, sites, or feeds in which personalized news is delivered. This emphasis leaves out an important class of stakeholders, namely professional journalists themselves. We argue that these omissions diminish the value of journalists' work and perspectives and leads to lower quality news delivery. As a possible solution, we show that a multistakeholder approach to news recommendation offers an avenue for restoring the journalistic voice to news recommendation. In this paper, we argue that news recommender systems should be designed with journalists as first-class users and explore the research implications of such a commitment. We include preliminary results from an interview study exploring the deficiencies journalists find in current news recommendation platforms and what might be the benefits of greater governance over them.

Text provides a compelling example of unstructured data that can be used to motivate and explore classification problems. Challenges arise regarding the representation of features of text and student linkage between text representations as character strings and identification of features that embed connections with underlying phenomena. In order to observe how students reason with text data in scenarios designed to elicit certain aspects of the domain, we employed a task-based interview method using a structured protocol with six pairs of undergraduate students. Our goal was to shed light on students' understanding of text as data using a motivating task to classify headlines as "clickbait" or "news". Three types of features (function, content, and form) surfaced, the majority from the first scenario. Our analysis of the interviews indicates that this sequence of activities engaged the participants in thinking at both the human-perception level and the computer-extraction level and conceptualizing connections between them.

This paper presents a machine learning-based (ML) approach for identifying fake news on web-based social media networks. Data was acquired from Facebook to develop the model which was used to identify Afan Oromo's false news. The system architecture uses algorithms, such as support vector machines (SVM), k-nearest neighbor (KNN), and convolutional neural networks (CNNs) to detect and classify fake news. Existing models have limitations in understanding reported news accuracy compared with verified news. This study successfully resolved the challenges in the detection of social media fake news detection for the Afan Oromo language with the use of ML models and natural language processing (NLP) techniques. The results show that the SVM approach achieved a precision, recall, and F1score, of 0.92, 0.92, and 0.90.

This study aimed to determine the number of documents suitable for LDA topic modeling analysis. Sample data was created from 7,115 news articles covering the high school credit system until 2022, following the announcement of the introduction of the high school credit system. Four different methods were employed for analysis. First, a total of 120 pieces of sample data, comprising 6 types with 20 pieces, were created, and the analyzed topics and concordance were examined for all documents. Second, through the AUC of the ROC curve, the discriminative power of all documents and the analysis of the same topic variables based on the number of documents were investigated. Third, the total document topics and the frequency of the same topic were analyzed in relation to the number of documents. Fourth, after analyzing the topics within the entire document, sample data reflecting the document ratio and weight by topic were created and compared based on the number of documents. The findings of this study indicate that a minimum of approximately 700 documents is required for robust LDA topic modeling analysis. Moreover, the analysis suggests that collecting over 2,000 documents provides sufficient data for reliable results.

본 연구는 LDA 토픽모델링 분석에 적합한 문서의 수를 알아보고자 하였다. 이를 위해 고교학점제 도입 발표 이후 2022년까지 고교학점제를 주제로 보도된 뉴스 기사 7,115건을 대상으로 샘플데이터를 생성하여 R 프로그램을 활용하여 토픽 분석 후 네 가지 방법을 통해 LDA 토픽모델링에 적합한 문서 수를 분석하고 결과를 종합하였다. 첫 번째, 문서 수에 따라 6가지 유형별 20개씩 총 120개의 샘플데이터를 생성하여 전체 문서를 대상으로 분석한 토픽과 일치도를 분석하였다. 두 번째, ROC곡선의 AUC를 통해 문서 수에 따른 전체 문서 토픽과 동일 토픽 분석력을 알아보았다. 세 번째, 문서 수별로 전체 문서 토픽과 동일한 토픽이 분석된 횟수를 비교하였다. 네 번째, 전체 문서 토픽별 문서의 할당률 및 가중치를 반영한 샘플데이터를 문서 수별 6가지 유형으로 생성하여 토픽 일치도를 비교하였다. 분석 결과 LDA 토픽모델링 분석을 위해서는 연구 대상인 문서 수가 최소 약 700건은 확보되어야 하고, 약 2,000건 이상의 문서가 확보될 경우 충분한 것으로 나타났다.

As fake news, misinformation, and communication disorders continue to raise societal concerns, several countermeasures are emerging to combat this growing challenge. This study examines the role of social media in the spread of information disorder in Africa and evaluates how effectively three prominent factchecking websites-FactCheckHub, Dubawa, and Africa Check-are addressing this communication crisis. Using a content analysis methodology, the research identifies common types of misinformation circulating on Nigerian social media, analyzes existing fact-checking techniques, and assesses the contributions of the selected platforms in mitigating information disorder. Drawing on academic frameworks related to misinformation, disinformation, and verification, the study explores how social media facilitates the spread of false narratives and the societal consequences that ensue. It contributes to broader discussions on media literacy, information integrity, and the cultivation of an informed society in the digital age by providing insights into the dynamics of disinformation in Nigeria and the critical role of fact-checking initiatives in addressing it.

The headline is a salient element of the news story, whose aim is to summarise the story and attract attention to its full text. The internet and online news dissemination and consumption have strongly transformed journalistic discourse, including headlines, which have become longer, significantly more complex, and multifaceted in their aim to attract readers’ attention. This paper presents the results of a qualitative comparative study of online headlines published on Croatian and Lithuanian media outlets from a discourse-analytic perspective. The data was collected from four top-read online news outlets (jutarnji.hr, index.hr, lrytas.lt, delfi.lt) and qualitatively analysed bearing in mind linguistic and visual strategies used to frame the news story and attract readers’ attention. The analysis showed that similar clickbait and narrative strategies are consistently aggregated across semiotic modes in all four news outlets in both countries. Apart from minor context-specific distinctions, no substantial differences were noticed in the overall discourse of headlines in the Croatian and Lithuanian observed media outlets.

The present investigation considers the objectivity of Western print media in reporting on two global wars: the war between Israel and Palestine and the war between Russia and Ukraine. Considering articles published during the period November 1-November 30, 2024, in CNN, BBC News, and Al Jazeera, the investigation utilizes agenda-setting and framing concepts to analyze the ways in which these media outlets create public opinion through selective reporting. The analysis presents sharp contrasts in coverage. Al Jazeera focused on humanitarian emergencies, war crimes, and civilian suffering in the Israel-Palestine conflict, while BBC and CNN less often and less comprehensively covered these topics. In contrast, in the Russia-Ukraine conflict, BBC and CNN reported more on Western engagement and political frames, usually following their geopolitical agendas, while Al Jazeera presented a more balanced picture, covering both military and humanitarian aspects. The research highlights how media bias, driven by institutional ideologies and the expectations of the audience, warps public perception of international conflicts. It invites critical consumption of media and pluralized sources of news to cultivate a more differentiated perspective of global affairs. Through the revelation of these imbalances, the study adds to more general debates around media ethics, objectivity, and the agenda-setting role of journalism in shaping global discourse.

Tarih boyunca insanların birbirleriyle ve doğal çevreleriyle kurdukları ilişkiler neticesinde çeşitli hastalıklar ortaya çıkmıştır. Bunlardan birisi de 31 Aralık 2019 tarihinde Çin'in Wuhan şehrinde ortaya çıkan Covid-19 salgınıdır. Covid-19 birçok insanın ölümüne sebep olmuştur. Bu tür önemli sağlık olayları ile ilgili bilgilerin aktarılmasında sosyal medya platformları aktif bir rol oynamıştır. Pandemi döneminde popülerliğini artıran platformlardan biri de Twitter olmuştur. Sağlıkla ilgili bilgi ve haber paylaşılan önemli bir mecra haline gelmiştir. Bu araştırma, Ocak 2020 ila Mayıs 2020 tarihleri arasında Covid-19 haberlerinin twitter ortamında nasıl aktarıldığının incelenmesi amacıyla yapılmış nitel bir çalışmadır. Gerekçe ve Yöntem: Bu araştırmada, 5 sağlık haber sitesinin twitter hesapları incelenmiştir. Ocak 2020 ila Mayıs 2020 tarihleri arasında sağlık haber sitelerinin ilgili tüm tweetleri değerlendirmeye alınmıştır. Çalışma kapsamındaki Covid-19 haberlerinin incelenmesinde nitel araştırma yöntemlerinden doküman incelemesi yapılarak, içerik analizi tekniği kullanılmıştır. Bulgu: Ocak 2020 ila Mayıs 2020 tarihleri arasında toplam 3413 tweet tespit edilmiştir. Atılan tweetlerin %72,66'sı Covid-19 ile ilgili haberleri oluşturmaktadır. Ana konusuna göre en fazla gündem/magazin haberlerinin yer aldığı, ardından sırasıyla korunma/önlem, teşhis, tedavi, aşı/ilaç geliştirme ve normalleşme süreci ilgili haberlerin yer aldığı saptanmıştır. Tweet paylaşım şekli en fazla görsel öğelerin yer aldığı, ardından makale ile video takip etmektedir. Haber başlıkları daha çok düz cümle ile kurulurken soru cümleleri pek tercih edilmemiştir. Sonuç: Araştırmada dikkat çeken yön, Covid-19 ile ilgili aktarılan tweetlerin daha çok magazinsel bir içerik/tarzda aktarıldığı sonucuna ulaşılmıştır. Pandemi döneminde böyle önemli ve ciddi bir hastalığın magazinsel içerikle paylaşılması dikkat çekmiştir.

Interactivity is one of the most important aspects of digital media, it plays significant roles in the communication process, allowing the user to engage directly with the communicator and the news they publish, or with other users who share their interests and preferences. Interactivity with its tools has become a subject of interest to understand its dimensions, levels, types, and characteristics, in addition to its flaws or weaknesses in media and journalism, in order to diagnose and address them. Therefore, this research aims to identify the dimensions of interactivity in a sample of Iraqi newspaper websites, which are (ALMADA), (AZZAMAN), (ALSABAH ALJADED), and (ALMUSTAKBAL ALIRAQI), using a scale that includes a number of indicators. The research is descriptive; the researchers followed the survey methodology to achieve the objectives. The researchers reached a set of results and conclusions, the most prominent of which is the clear weakness in the dimensions of interactivity within the Iraqi newspaper websites, as many indicators were neglected, and no attention was given to the dimension of user response, which is an important dimension that cannot be dispensed with in the communication process.

Introduction: Digital or social media technology is the new face of Communication: instantaneous Communication and global connectivity. On extensively reviewing the literature, studies have yet to emerge on the type of social media usage and its influence on the mental wellbeing of Jamaicans. This gap in the literature retards knowledge of many challenges in society and the likely solutions to those truths. Jamaica has been experiencing a crime epidemic, and there is a gap in the literature on cyberpsychology. Objective: This study evaluates cyberpsychology and different social media used by Jamaicans. Methods and Materials: This study employed an explanatory cross-sectional survey research design. According to the 2019 population projections from the Statistical Institute of Jamaica [STATIN], Jamaica has 2,024,687 people 18 years and older, including 1,032,369 women and 992,318 men. The sample size in this study is calculated using this number, a 95% confidence level, a 5% margin of error, and the gender distribution of the population. Based on the population size and the data previously provided, the sample size is 385 Jamaicans aged 18 years and older, with a response rate of 78.18%. Findings: The findings revealed that Twitter users experienced the highest level of severe anxiety (13.2%), followed by TikTok users (12.4%) and WhatsApp users (8.2%), and Facebook users experienced the least severe anxiety. TikTok users experienced the highest level of severe depression (4.8%), followed by YouTube users (3.4%) and Instagram users (2.8%), and Facebook users experienced the least severe depression.

This study offers a new way of understanding the motivations that influence media workers’ impression management (or branding) in the social media era. Amid the growing insecurity of media work generally and the particular pressures of branding oneself and promoting one’s employer online, our research introduces a framework through which to interpret the forces and factors—internal (social–psychological) and external (environmental)—that shape how and why media professionals engage in branding. Through a first-of-its-kind survey of a broad cross-section of journalists ( N = 642), this study proposes, tests, and confirms a branding alignment hypothesis. This typology sheds light on how branding activity aligns with individual, organizational, and institutional motivations as well as professional identities. Importantly, the study shows how branding is manifested over and above social media dynamics alone and reveals how “self-made” and “company” journalists differ in how they promote...

This chapter makes sense of the emergent regime of audience measurement by forwarding the idea of enumerative accountability. I posit the current regime of enumerating digital news audience in the history of audience measurement associated with newspapers and broadcast news in India. This helps me to distill recurrent and incremental challenges of accountability in the business of audience measurement in digital markets.

This article is about personalized information delivery in the Netherlands and is based on a review of empirical studies on this topic. The risk of echo chambers and filter bubbles is discussed and put in an international perspective. The focus is on the role government institutions, tech companies and scholars can play in this field. At present, the Dutch journalism landscape would still appear to be sufficiently diverse, delivering information that is accessed by different groups of citizens. But the precise effect of news personalization remains unclear and the growing power of tech companies also shows the need for more insights and better research methods. Without in-depth (data) knowledge, it is difficult to develop solution directions to prevent any problems that the personalization of news could entail.

Email phishing is a manipulative technique aimed at compromising information security and user privacy. To overcome the limitations of traditional detection methods, such as blacklists, this research proposes a phishing detection model that leverages natural language processing (NLP) and deep learning technologies to analyze Indonesian email headers. The primary objective is to more efficiently detect zero-day phishing attacks by focusing on the unique linguistic and cultural context of the Indonesian language. This enables the development of models capable of recognizing phishing attack patterns that differ from those in other language contexts. Four models are tested, combining Indonesian bidirectional encoder representation of transformers (IndoBERT) and FastText feature extraction techniques with convolutional neural network (CNN) and long short-term memory (LSTM) deep learning algorithms. The results indicate that the combination of FastText and CNN achieved the highest performance in accuracy, precision, and F1-score metrics, each at 98.4375%. Meanwhile, the FastText model with LSTM showed the best performance in recall, with a score of 98.9583%. The research suggests exploring deeper into email content or integrating analysis between headers and email content in future studies to further improve accuracy and effectiveness in phishing email detection.

Background and Aims: The post-COVID-19 pandemic period has heightened concerns about student mental health and suicide risk in Bangladesh. While studies have explored these issues during the pandemic, post-pandemic student suicides remain under-researched. This study investigates the characteristics, methods, and triggering events associated with suicidal behaviors among students in Bangladesh during the post-pandemic period (2022-2023).

Methods: Data were collected from 150 online newspaper portals in Bangladesh, covering student suicides from 2022 to 2023. Variables such as causes, methods, timing, location, sex, age, and education level were analyzed using Microsoft Excel, SPSS, and ArcGIS.

Results: A total of 984 student suicide cases were identified. Females accounted for 61% of the cases, while males represented 39%, indicating a higher vulnerability among female students. The majority of cases (72.5%) involved students aged 13-19 years, followed by those aged 20-25 years (18.4%). Secondary school students represented 44.9% of the cases, with 7.2% from madrasahs. Hanging was the most common method (79.7%). Major causes included emotional distress (28%), romantic relationship issues (19.5%), academic pressure (8.4%), family problems (8.1%), mental instability (7%), and sexual harassment (3.3%). The Dhaka division reported the highest rate (27.8%) of student suicides. Suicide rates were lowest in August 2022 (4.3%) but spiked in 2023 (12.6%).

Conclusion: This study highlights the significant rise in student suicides in Bangladesh after the pandemic, primarily driven by emotional distress, with females and the 13-19-year age group being most vulnerable. These findings emphasize the urgent need for gender-specific mental health interventions to address this growing issue.

Este estudo investigou práticas inovadoras no design e produção de livros, revistas e outras publicações que utilizam do meio digital e não possuem os mesmos limites das publicações físicas convencionais. Por meio de uma busca exploratória, 39 resultados foram encontrados, categorizados e filtrados. Após, realizou-se um estudo de múltiplos casos, por meio do qual se analisaram seis tecnologias: Calibre, CoWriter, Issuu, Twine, HedgeDoc e OMP. Os resultados indicam que as ferramentas tendem a ser de fácil acesso, com foco na colaboração e publicação online, se utilizando de recursos como linguagens de marcação e inteligência artificial para auxiliar no design e na produção. Com isso, as ferramentas permitem a criação de publicações interativas e multimídia, explorando as potencialidades do meio digital, fazendo uso de diferentes tecnologias para tal. Finalmente, o estudo contribui para a compreensão de diferentes práticas inovadoras neste campo e abre caminho para pesquisas futuras que explorem outros achados.

The literature review highlights the importance of understanding the relationship between social media usage and mental health outcomes. Previous studies in this field have demonstrated associations between increased social media usage and higher levels of depression and anxiety However, there is a lack of research focusing on the duration of social media usage and its impact on mental health. We aim to explore two hypotheses in this study. The hypotheses are as follows: firstly, that increased time spent on social media correlates with higher levels of anxiety and depression among young adults; and secondly, that this correlation will be stronger among young adults having chronic stress compared to those not having chronic stress. The methodology employed in this study involves a cross-sectional design targeting young adults aged 18-25, primarily recruited from university settings and social media platforms. Participants were required to self-report regular engagement with social media platforms, and exclusion criteria included preexisting mental health conditions. Measures included the Social Media Use Integration Scale (SMUIS), the Patient Health Questionnaire 9 (PHQ-9) for depressive symptoms, and the Perceived Stress Scale (PSS-10) to assess stress levels. Results for the study indicate a positive correlation between social media usage and both depressive symptoms and chronic stress among young adults. However, the expected moderating effect of chronic stress on the relationship between social media usage and depressive symptoms was not observed. Finally, this study contributes to the existing literature by highlighting the impact of social media usage duration on mental health outcomes among young adults. By identifying factors that may exacerbate or mitigate the effects of social media on mental well-being, this research informs targeted interventions and preventive strategies aimed at promoting healthier online behaviors.

This research is aimed at examining how the culture of immediacy is implemented in a newspaper undergoing digital transformation. This paper is written based on the case of Harian Kompas, the most influential newspaper in Indonesia, that just officially launched its paywall-based digital site, kompas.id as an alternative platform. Within this context, the daily implemented the digital-first strategy to put the priority of rapid digital news production prior to its slow-pace print edition. Through ethnography fieldwork in the daily's newsroom, relying on in-depth interviews and participant observations, the study highlights a notion that the culture of immediacy is not easy to implement. The challenge rests on the fact that it is not only contradictory to the common rhythm of rigid newspaper work-flow and deadline among reporters and editors, but further it is considered harmful to the daily's prescribed core value of comprehensive journalism originated from its editorial philosophy as well as journalism credo of being credible. It is within the constant negotiations among all the newsroom's actors, the culture of immediacy remains to be a contesting value that should be carried out by the daily as a way to excrete the old habit of print deadline while the digital-first transformation is still taking shape.

This paper presents a machine learning-based (ML) approach for identifying fake  news  on  web-based  social  media  networks.  Data  was  acquired  from Facebook  to  develop  the  model  which  was  used  to  identify  Afan  Oromo's false news. The system architecture uses algorithms, such as support vector machines  (SVM), k-nearest  neighbor(KNN),  and  convolutional  neural networks  (CNNs)  to  detect  and  classify  fake  news.  Existing  models  have limitations in understanding reported news accuracy compared with verified news.  This  study  successfully  resolved  the  challenges  in  the  detection  of social media fake news detection for the Afan Oromo language with the use of  ML  models  and  natural  language  processing  (NLP)  techniques.  The results  show  that  the  SVM  approach  achieved  a  precision,  recall,  and  F1-score, of 0.92, 0.92, and 0.90.

Journalism's various crises have been well-documented, such as lack of credibility and a decline in its active role in the democratic process, but there has been a lack of constructive response or research into solutions to its problems. There is evidence of a growing audience for live, face-to-face events. This article reviews past and present relationships between journalism and the stage and uses them as a springboard to introduce the concept of News Theatre. It configures a version of Habermas's public space/sphere as a new locus for this kind of open journalism, performed to the public. In an age of confused news literacy, it presents examples to show how face-to-face journalism might be successful in helping to re-establishing its status and role in society as truth-teller. It argues that human intervention is now required to restore journalism's authority and contends that journalism should consider communicating face-to-face, in order to rediscover its audience, by meeting them, in person. The paper points the way towards rebuilding communities of readers, strengthening the relationship between news, public and performance. The paper makes the historical connection between earliest known formats of News Theatre, from town crier, through revolutionary theatre in Russia and China and Living Newspapers of last century, to today's experiments in event journalism around the world. It uses a theoretical framework to consider the role of audience as activists. It redefines the boundaries between journalism, theatre and political activism, and proposes a model which might help towards sustaining journalism for the future, while rediscovering the public sphere, through 'News Theatre.'

Platforms facilitate news publishers to reach a very large audience, while the latter offer platforms a stream of content to incessantly engage users. In this seemingly symbiotic relationship, only platforms know the true popularity of the news distributed to their users, and the incremental advertising revenues accrued from the content produced by publishers. Platforms are also known to change the metrics to gauge popularity and audience preference. These problems raise questions about transparency, accountability, and parity in the dealings between platforms and publishers.

How is political news shared online? This fundamental question for political communication research in today's news ecology is still poorly understood. In particular, very little is known how explaining news sharing differs from explaining news viewing. Based on a unique dataset of approximately 870,000$ URLs shared approximately 100 million times on Facebook, grouped by countries, age brackets, and months, we study the predictors of viewing versus sharing of political versus non-political news.We first identify websites that at least occasionally contain news items, and then analyze metrics of the news items published on these websites. We enrich the dataset with natural language processing and supervised machine learning. We find that political news items are viewed less than non-political news items, but are shared more than one would expect based on their views. Furthermore, the source of a news item and textual features often studied in clickbait research and in commercial ...

ang sÑng t-p trung ß mÙt làng biên giÛi (làng k M½, xã BÝ Y, huyÇn k Glei, tinh Kontum) cách ngã ba biên giÛi Lào, ViÇt Nam, Campuchia 10km. Theo lÝi nhïng ng°Ýi cao tuÕi ß E ¯k M¿, làng Br §u này tëng c° trú ß mÙt thung lkng rÙng lÛn cing °ãc gÍi là •k M¿. Vùng ¥t này hiÇn nay thuÙc Ëa ph-n cça Campuchia. Sau n m 1975, °Ýng biên giÛi giïa ba n°Ûc ViÇt Nam, Lào và Campuchia °ãc thi¿t l-p tách ng°Ýi Brâu sÑng ß vùng ranh giÛi này thành nhïng nhóm tÙc nguÝi thuÙc các quÑc gia khác nhau. Nhóm Brâu °ãc c¯t vÁ ViÇt Nam di chuyÃn të vË trí ci ¿n khu våc hiÇn nay và vân giï tên làng ci là £ MÃ. 203 VÛi dân sÑ chi kho£ng trên 400 ng°Ýi trong lãnh thÕ ViÇt Nam', Brâu °ãc coi là mÙt trong nhïng nhóm dân tÙc ít ng°Ýi nh¥t t¡i ViÇt Nam. Trong nhïng n m §u 1990, mÙt sÑ bài báo² còn c£nh báo vÁ nguy c¡ bË "tuyÇt chçng" hay "diÇt chçng" cça dân tÙc Brâu do dân sÑ it, trình Ù kinh t¿ và v n hóa th¥p, sÑng tách biÇt và hôn nhân c-n huy¿t. MÙt sÑ nghiên céu dân tÙc hÍc c©n trÍng h¡n sau ó ã phàn bác l¡i quan iÃm này (Vi Lãi 1993; Bùi NgÍc Quang 2004) khi chi ra r±ng, ng°Ýi Brâu có nhïng quy t¯c hôn nhân khác dòng tÙc ch•t ch¿ cing nh° giï quan hÇ vÛi hÍ hàng có dân sÑ hàng chåc ngàn ng°Ýi bên kia biên giÛi. D §u v-y, trong chính sách cça nhà n°Ûc vÛi các dân tÙc thiÃu sÑ (DTTS) Brâu v¥n °ãc coi là mÙt trong nhïng dân tÙc còn r¥t ít ng°Ýi' và nh-n °ãc nhïng 3 u ãi •c biÇt à phát triÃn kinh t¿, xã hÙi. Ch³ng h¡n të n±m 1992 ¿n 1995 nhà n°Ûc thông qua nguÓn vÑn Ënh canh, Ënh c° a âu t° g §n 1 tó Óng à xây dñng c¡ sß h¡ t §ng cho làng Ënh cí ¯k Mà (NguyÅn Th¿ HuÇ 2002). Trong n m 2017, UBND tinh Kon Tum phê duyÇt ê án h× trã phát triên kinh t¿ xã hÙi dân tÙc thiÁu sÑ í t ng°Ýi Brâu tinh Kontum ¿n n±m 2025 vÛi tông kinh Phi 65.702.000.000 ông, MÙt m•t nh-n °rÍc nhïng Á án h× tro

Viral video advertising is one of the effective tools used by brands to optimise social media presence. Marketers aim to create content that induce viewers to like, comment, and share videos, which ultimately increases brand presence. This study covers various aspects of emotional appeal and their impact on high video virality. Semi-structured interviews were conducted with creative professionals from advertising agencies and production studios to explore the role of emotional appeal, which influences large numbers of people to like, comment, and share videos. This study provides insights on how video virality is influenced by a particular aspect(s) of emotional appeal and helps professionals in viral video creation.

The rapid growth of mobile technologies has transformed social media, making it crucial for expressing emotions and thoughts. When making significant decisions, businesses and governments can benefit from understanding public opinion. This information makes sentiment analysis vital for understanding public sentiment polarity. This study develops a hyper tuned deep learning model with swarm intelligence and many approaches for sentiment analysis. convolutional neural network (CNN), bidirectional encoder representations from transformers (BERT), long shortterm memory (LSTM), CNN-LSTM, BERT-LSTM, and BERT-CNN are the six deep learning models of the sentiment analysis using deep learning with reinforced learning based on reptile search algorithm (SA-DLRLRSA) model. The reptile search algorithm, an enhanced swarm intelligence algorithm (SIA), optimizes deep learning model hyper parameters. Word2Vec word embedding is used to convert textual input sequences to representative embedding spaces. Pre-trained Word2Vec embedding is also used to address issue of unbalanced datasets. Experimental results demonstrate that the SA-DLRLRSA model works best with accuracies of 93.1%, 94.7%, 96.8%, 96.3%, 97.2%, and 98.3% utilizing CNN, LSTM, BERT, CNN-LSTM, BERT-CNN, and BERT-LSTM.

Republished article finding is the task of identifying instances of articles that have been published in one source and republished more or less verbatim in another source, which is often a social media source. We address this task as an ad hoc retrieval problem, using the source article as a query. Our approach is based on language modeling. We revisit the assumptions underlying the unigram language model taking into account the fact that in our setup queries are as long as complete news articles. We argue that in this case, the underlying generative assumption of sampling words from a document with replacement, i.e., the multinomial modeling of documents, produces less accurate query likelihood estimates. To make up for this discrepancy, we consider distributions that emerge from sampling without replacement: the central and noncentral hypergeometric distributions. We present two retrieval models that build on top of these distributions: a log odds model and a bayesian model where document parameters are estimated using the Dirichlet compound multinomial distribution. We analyse the behavior of our new models using a corpus of news articles and blog posts and find that for the task of republished article finding, where we deal with queries whose length approaches the length of the documents to be retrieved, models based on distributions associated with sampling without replacement outperform traditional models based on multinomial distributions.

Title: “Inifrån åsiktsfabriken” - en kvalitativ studie av ledarjournalisters uppfattningar om sin yrkesroll Authors: Noa Söderberg, Jonatan Andersson and Sebastian Lindström Subject: Undergraduate research paper in journalism studies, Department of journalism, media and communication (JMG), University of Gothenburg Term: Spring 2017 Supervisor: Britt Börjesson, JMG, University of Gothenburg Pages/words: 45 pages, 18 508 words (including abstract and appendix). Purpose: The main purpose of this study is to examine how the editorial boards of Swedish newspapers perceive their professional role, their organizational procedures and their professional goals and ideals. Method: Qualitative in-depth interviews with seven Swedish editorial journalists, representing four newspapers. Procedure: We have interviewed seven editorial journalists, representing the editorial boards of four different Swedish newspapers, and transcribed and analyzed them based on Jürgen Habermas democratic theories, ...

This study aimed to observe image construction of the Islamic Defenders Front (FPI) based on six articles of the Jakarta Post Online News about the FPI's protest toward three issues: Ahmadiyah, the arrival of Lady Gaga in Indonesia, and Ahok as the substitute governor of Jakarta. The author qualitatively explored the FPI's image using Halliday's systemic functional linguistics (SFL), which defines the types of process in a clause. The author also analyzed the thematic structure of the clause to support the analysis of each type of process. The result was approximately 208 clauses from the six news articles. This study shows that the dominant process in the abovementioned three issues is the material process. The material process represents 51% in the issue of Ahmadiyah, 41% in the issue of the arrival of Lady Gaga, and 70% in the issue of Ahok as Jakarta's substitute governor. This material process shows that the Jakarta Post Online News constructed a negative image of the FPI's by reporting this organization's action during the protest. In the issue of Ahmadiyah, the FPI was framed as anarchist, while in the issue of Ahok and of Lady Gaga it was represented as protestor. The analysis of thematic structures shows the FPI as the dominant topical theme, which indicates the FPI was the main topic of the articles.

CD&V Yves Leterme, Els Schelfhout, Miet Smet, Elke Tindemans. Wouter Beke, Sabine de Bethune, Nahima Lanjri, Pol Van Den Driessche, Tony Van Parys. MR Alain Destexhe, Philippe Monfils, François Roelants du Vivier. Jacques Brotchi, Alain Courtois, Marie-Hélène Crombé-Berton, Christine Defraigne. Open VLD Margriet Hermans, Paul Wille. Nele Lijnen, Martine Taelman, Patrik Vankrunkelsven. Vlaams Belang Jurgen Ceder, Karim Van Overmeire. Anke Van dermeersch, Freddy Van Gaever, Joris Van Hauthem. PS Philippe Mahoux, Olga Zrihen. Sfia Bouarfa, Joëlle Kapompolé. sp.a Guy Swennen, Marleen Temmerman. Bart Martens, Myriam Vanlerberghe, André Van Nieuwkerke. CDH Jean-Paul Procureur. Anne Delvaux, Marc Elsen. Écolo Josy Dubié. José Daras, Isabelle Durant.

This study seeks to understand how journalists deal with story/truth-making in their daily news practice, based on in-depth interviews with 67 journalists from Belgium and the Netherlands. The findings revealed a difference between news makers and storytellers and related differences in the way journalists prepare and present news stories. In preparing stories, news makers consider pegs and predefined angles as vital, while storytellers see them as obstacles. In presenting stories, newsmakers defend many of the journalistic conventions challenged by storytellers. The findings are discussed in terms of boundary work and in the light of the ubiquity of online news.

Throughout this article, we are presenting a proposal to conduct digital media studies as one of the first deliverables of an ongoing research project. This proposal, which we are calling "Articulated System to Analyse Digital Media" (ASADM): consists of a set of concepts presented through specific terminology, and of a group of articulated elements allowing to determine what we call the what (parameters) and how (indicators) of any future study regarding online newspapers or digital media. Thus, we obtain an operative analysis protocol as a deliverable. In between, we characterize the typical context of the sort of studies that constitute the context for our proposal. Table of contents: 1. Introduction and background 2. Components 3. Context 4. Obtaining Parameters and Indicators: going from what to how 5. Phases, Activities and Results 6. Conclusions 7. References 8. Annex 1 9. Annex 2

Throughout this article, we are presenting a proposal to conduct digital media studies as one of the first deliverables of an ongoing research project. This proposal, which we are calling "Articulated System to Analyse Digital Media" (ASADM): consists of a set of concepts presented through specific terminology, and of a group of articulated elements allowing to determine what we call the what (parameters) and how (indicators) of any future study regarding online newspapers or digital media. Thus, we obtain an operative analysis protocol as a deliverable. In between, we characterize the typical context of the sort of studies that constitute the context for our proposal. Table of contents: 1. Introduction and background 2. Components 3. Context 4. Obtaining Parameters and Indicators: going from what to how 5. Phases, Activities and Results 6. Conclusions 7. References 8. Annex 1 9. Annex 2

The document, "The Impact of Misinformation and Disinformation on Anti-Polio Vaccination Refusal in Pakistan's Tribal Areas and Among Hardcore Muslims," examines how false narratives have hampered polio vaccination efforts in Pakistan. Despite significant vaccination campaigns, distrust fueled by extremist groups, misinformation, and socio-cultural factors lead to vaccine hesitancy, especially in tribal areas and among certain religious groups.

The study distinguishes misinformation (unintentionally false information) from disinformation (deliberate falsehoods). Extremist groups and religious leaders often spread disinformation claiming that polio vaccines are part of a Western agenda against Muslims. Shared widely through social media, local media, and religious sermons, these narratives lead to reduced vaccination rates and attacks on health workers.

Recommendations include engaging community leaders, monitoring misinformation, and promoting accurate information to rebuild trust and support public health efforts.

Predmet istraživanja ove doktorske disertacije su promene medijske publike koje se dešavaju usled ekspanzije interneta. U centru rada su pitanja u čemu se ogledaju te promene, šta je novo i drugačije u iskustvu ljudi kada koriste internet kao medij, kao i da li su te promene tolike da dovode u pitanje dalju upotrebu samog koncepta publike. Da bi se došlo do odgovora na ova pitanja rad je struktuiran oko dve ose – teorijskog promišljanja koncepta publike i analize medijskih iskustava ljudi koji čine te publike u onlajn okruženju. U prvom delu rada analizirano je da li teorijsko nasleđe iz perioda istraživanja publike tradicionalnih medija pomaže razumevanju publike digitalnih medija. Odgovor na ovo pitanje nije jednostavan, pre svega zato što ne postoji jedinstveno, koherentno i sveobuhvatno razumevanje publike. Istorija proučavanja medija, a samim tim i publike može se interpretirati na različite načine. U ovom radu se teorijsko nasleđe istraživanja publike predstavlja kroz prikaz t...

Предмет истраживања ове докторске дисертације су промене медијске публике које се дешавају услед експанзије интернета. У центру рада су питања у чему се огледају те промене, шта је ново и другачије у искуству људи када користе интернет као медиј, као и да ли су те промене толике да доводе у питање даљу употребу самог концепта публике. Да би се дошло до одговора на ова питања рад је структуиран око две осе – теоријског промишљања концепта публике и анализе медијских искустава људи који чине те публике у онлајн окружењу. У првом делу рада анализирано је да ли теоријско наслеђе из периода истраживања публике традиционалних медија помаже разумевању публике дигиталних медија. Одговор на ово питање није једноставан, пре свега зато што не постоји јединствено, кохерентно и свеобухватно разумевање публике. Историја проучавања медија, а самим тим и публике може се интерпретирати на различите начине. У овом раду се теоријско наслеђе истраживања публике представља кроз приказ три водећа теоријс...