News Content Research Articles

The Effect of K-Pop Fanaticism on Social Media Coverage @tanyakanrl’s Twitter Account

In this article, a questionnaire was distributed to 62 respondents to explore the influence of this phenomenon on news at the @tanyarl autobase. The survey results showed that the majority (61.1%) of respondents agreed that this phenomenon has influenced an increase in reporting on the autobase account. This indicates that K-Pop fanaticism has created a shift in focus and news content. Thus, K-Pop fanaticism can contribute positively to the development of a more creative and innovative journalistic style. However, the pressure to produce content that captures the attention of K-Pop fans can lead to sensationalism and a loss of objectivity. Survey results show that some respondents feel that news on Twitter tends to be more subjective and not entirely accurate in its coverage of K-Pop. Additionally, it was also found that K-Pop can disrupt the balance and fairness of attention given to other topics on the platform. The dominance of K-Pop content on social media makes it difficult for other topics to receive the attention they deserve. Therefore, it is necessary to implement fact-checking mechanisms and promote critical thinking among social media users. Educating users about the assessment of news quality and the importance of topic diversity should be enhanced so that users can distinguish between trustworthy and untrustworthy news content.

Media Ideology and Representation of The National Police Image in The Online Media Frame (Framing Analysis of Teddy Minahasa Drug Case in the October 15, 2022 Edition of Koran Tempo Online)

One of the advantages of online journalism compared to conventional media is accessibility and speed in getting news. However, despite these advantages, online news portals are not automatically superior to conventional media in terms of the value of journalism products or news content. However, media ideology is very influential in the process of news construction, especially through the framing of news. No exception about the news of the drug case that is entangling a Two-Star Police General, Teddy Minahasa, of course, the media is interested in reporting the issue. The method used in this study includes framing analysis developed by Pan and Kosicky, while the approach used is qualitative. In this study, results were obtained that showed that the online tempo newspaper in reporting the tragedy was critical, informative and provocative. This indication can be seen from the results of the framing analysis carried out, namely the main framing of the news is that a Two-Star General is entangled in drugs is a controversial thing and certainly damages the institution of the National Police. With syntactic elements is the strengthening of framing by using unbalanced source quotes so that they are not neutral in reporting. As for the script element, strengthening and enriching the news paragraph related to the How element is carried out to minimize the why element in the news. For thematic elements, there are 3 major themes, namely: 1. A Two-Star General Dragged into a Drug Case 2. Chronology of occurrence of the case 3. Suppression of the negative image of the Indonesian National Police. In addition, the selection of sources as a closing news, to emphasize that the condition of the National Police organization is very bad, is used as a whip for the National Police institution to improve its organization. The last is the rhetorical element, in this element the use of newspaper covers and some graphics to emphasize the element of news that seems hyperbole and provocative and even seems negative. In addition, it can be concluded that the tempo tempo online newspaper according to its media ideology constructs reality through a framing process for the purpose of representing the negative image of the Indonesian National Police in a news story.

How the public perceives the "good nurse" in China: A content analysis of national newspapers.

Newspapers are a predominant channel through which the Chinese public learns about nurses and the nursing profession. However, little nursing research has been performed in China to investigate the newspaper portrayal of nurses, and how the public perceives the role of nurses in the Chinese context is still an ambiguous phenomenon. This study aimed to clarify the public portrayals of nurses in China, and to analyze whether there are changes over time in news content related to nurses in the national newspapers. A content analysis of the newspaper articles citing nurses that have been published since each newspaper was established. We selected two national daily newspapers as sources to systematically search for articles about nurses from 1949 to 2022. A coding instrument was developed to quantitatively extract the contents of the articles identified. Then, using a mixed methods approach, we analyzed newspaper content to show the roles of nurses presented to the public by the media. A total of 317 articles were analyzed. Nurses have been depicted with heterogeneous images in both newspapers with positive wordings and up to 28 types of public images. More than half of the articles portrayed two, three, or more types of images. Among the images of nurses identified, "overworked" appeared the most frequently, followed by "dedicated," "philanthropic and benevolent," and "with a sense of responsibility," and then "technically skilled." By analyzing the image of nurses in both newspapers over time, we found that images related to virtue have largely increased with time, while images about professionalism have decreased. Nursing continues to be depicted as a virtuous caregiving profession, often forgetting the wide need for knowledge, skill, and expertise required in the occupation. The public image of nurses portrayed in the national newspapers does not accurately match their actual roles. The public image of nurses portrayed in the national newspapers does not accurately match their actual roles. To actualize a professional role and increase social status of nurses, intentional image management is needed. Nursing schools, nursing associations, and nursing professionals should be more proactive in overcoming the stereotypical image portrayed of them and use the news media as a tool to invite attention from and dialogue with the public about the value of nursing to reframe the public's understanding of the expert role of the professional nurse in health care and to create a new and more professional image for nursing.

Forecasting TAIEX and FITX with Affirmative and Doubtful Investor Sentiments

Abstract The existing literature have used media messages as a proxy variable for investor sentiment, but they mainly classify sentiment into positive or negative categories based on the words used in news articles, without much attention to the degree of affirmative or doubtful conveyed by the words used. Thus, in addition to classifying news content into positive or negative sentiment, this study also measures the degree of affirmative or doubtful expressed in the news articles in order to achieve more accurate predictive results. The study converts qualitative text to two quantitative scores (sentiment ratio and affirmative ratio) and investigates the predictive ability of these two variables on stock index returns and volatility in Taiwan’s case. The empirical findings indicate that only affirmative ratio exhibits a significant and negative impact on the one-day ahead returns of the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) and the Taiwan Stock Exchange Index Futures (FITX). Additionally, the volatility of returns in both future and spot markets is significantly influenced by both sentiment ratio and affirmative ratio. JEL Classifications: C22; G10; G40. Keywords: Investor sentiment; Text-mining; TAIEX; FITX; Affirmative ratio.

Photojournalist as a Newsworker

Even though news content is the end result of a complex collective production process that involves a number of newsworkers, writing the history of journalism from the perspective of labour remains a rare approach. In this article, we apply the newswork perspective to photojournalism with a two-fold aim. Firstly, we aim to identify crucial themes around which a history of Slovenian photojournalism from a newswork approach could be articulated. And secondly, we aim to demonstrate that adopting the newswork approach from a historical perspective enables us to identifying certain positions within newswork, where contradictions of journalism and transformations of its practices either more visible or have existed long before they “trickled up” to the more visible echelons of newsworkers. We argue that photojournalists are the professional group where the pressures and transformations of journalism are either more pronounced or have appeared earlier. Through the analysis of semi-structured interviews, documents and archive material, we identified three topics that reveal the contradictions of the history of journalism as reflected in the photojournalist qua worker.

Vivid and Engaging: Effects of Interactive Data Visualization on Perceptions and Attitudes about Social Issues

With the rising availability and volume of data, journalists are finding ways to integrate data-rich information into news content and make them accessible to everyday news readers by accompanying them with exemplifying cases. However, these exemplars do not always fully capture the complexity of the data patterns, leading to significant biases in readers’ issue perceptions. Drawing on the theoretical frameworks of exemplification theory and interactivity, this study examines the effectiveness of interactivity in counteracting the exemplification effect through perceived vividness of and user engagement with data-rich information. A mixed-design experiment revealed that, compared to textual description and static visualization, interactive data visualization is effective in motivating systematic processing of baserate information, which positively influences accuracy of issue perception as well as personal attitudes toward two controversial issues—climate change and same-sex marriage legalization. These findings have theoretical and practical implications for journalistic practice and interface design for communicating data information.

Group-Based Personalized News Recommendation with Long- and Short-Term Fine-Grained Matching

Personalized news recommendation aims to help users find news content they prefer, which has attracted increasing attention recently. There are two core issues in news recommendation: learning news representation and matching candidate news with user interests. In this context, “candidate” indicates potential for interest. Due to the superior ability to understand natural language demonstrated by Pretrained Language Models (PLMs), recent works utilize PLMs (e.g., BERT) to strengthen news modeling, obtaining more accurate user interest matching and achieving notable improvement in news recommendation. However, the existing PLM-based methods are usually incapable of fully exploring the fine-grained (i.e., word-level) relatedness between user behaviors and candidate news due to the heavy computational cost brought by PLMs. In this article, we propose a group-based personalized news recommendation method with long- and short-term matching mechanisms between users and candidate news based on PLMs to learn fine-grained matching efficiently and effectively. In our approach, we design to group user historical clicked news into chunks with quite shorter news sequences according to their clicked timestamps, which could alleviate the computation issues of PLMs. PLMs are applied in each group jointly with the candidate news to capture their word-level interaction, and global group-level matching is learned across different groups. In addition, the group-based mechanism could be naturally adapted for long- and short-term user representation learning, in which we build users’ long preferences from the representations of all groups and treat the last group as short interests, respectively. Finally, we employ a gate network to dynamically unify the group-level, long- and short-term representations, yielding comprehensive user-news matching effectively. Extensive experiments are conducted on two real-world datasets. The results show that our proposed method achieves superior performance in news recommendations.

WACANA BERITA KEKERASAN SANTRI PONDOK PESANTREN GONTOR DI REPUBLIKA ONLINE

In every online media platform, there exists a diverse range of ideologies and perspectives that influence the production of news content. Republika Online adheres to its own distinct ideology in the dissemination of information to the publik. Ideology can be discerned by analyzing the textual structure and discourse employed by each media platform. In the year 2022, a significant number of acts of violence occurred within the realm of education. Among these incidents was a case of violence against students at Gontor Islamic Boarding School, located in Ponorogo, East Java. Acts of violence can have adverse effects on both physical and mental health. In the case of the violence that occurred at Gontor Islamic Boarding School, it tragically resulted in the fatality of one of the students, highlighting the severe consequences of such incidents. This thesis focuses on two research questions: Firstly, how does Republika Online, as an online media platform, employ textual structure in presenting news regarding the violence against students at Gontor Islamic Boarding School, specifically in the edition from 06 to 08 September 2022. Furthermore, this study aims to investigate the discourse employed by Republika Online, an online media platform, in presenting news regarding the violence against students at Gontor Islamic Boarding School in the edition from 06 to 08 September 2022. In order to address these two issues, the researcher employed a qualitative (non-participant) approach. In this research, the researcher utilized Teun A. Van Dijk's discourse analysis method to analyze the "Violence against students at Gontor Islamic Boarding School, edition from 06 to 08 September 2022." In this study, it can be concluded that the textual structure utilized by Republika Online exhibits a tendency to explicitly marginalize the perpetrators and Gontor Islamic Boarding School.

Collaborative Mixture-of-Experts Model for Multi-Domain Fake News Detection

With the widespread popularity of online social media, people have come to increasingly rely on it as an information and news source. However, the growing spread of fake news on the Internet has become a serious threat to cyberspace and society at large. Although a series of previous works have proposed various methods for the detection of fake news, most of these methods focus on single-domain fake-news detection, resulting in poor detection performance when considering real-world fake news with diverse news topics. Furthermore, any news content may belong to multiple domains. Therefore, detecting multi-domain fake news remains a challenging problem. In this study, we propose a multi-domain fake-news detection framework based on a mixture-of-experts model. The input text is fed to BertTokenizer and embeddings are obtained by jointly calling CLIP to obtain the fusion features. This avoids the introduction of noise and redundant features during feature fusion. We also propose a collaboration module, in which a sentiment module is used to analyze the inherent sentimental information of the text, and sentence-level and domain embeddings are used to form the collaboration module. This module can adaptively determine the weights of the expert models. Finally, the mixture-of-experts model, composed of TextCNN, is used to learn the features and construct a high-performance fake-news detection model. We conduct extensive experiments on the Weibo21 dataset, the results of which indicate that our multi-domain methods perform well, in comparison with baseline methods, on the Weibo21 dataset. Our proposed framework presents greatly improved multi-domain fake-news detection performance.

Mitigating fake news and misinformation using news literacy behaviors (NLBs)

The increasing presence of fake news and misinformation in the contemporary digital media landscape is of concern to practitioners, educators, policy makers, and the public alike. Whilst the existence of fake news is not new, audiences are aware that the ‘quality’ of information that poses as being factual has changed significantly and is experienced more often in our digital culture. Using the results of a survey (n = 435) this paper examines how young news consumers in the UAE are applying news literacy knowledge and skills to identify and manage incorrect news and information. By regarding this audience as having digital agency, the results of the study demonstrate how they apply aspects of the 5As of media literacy education to fake news and misinformation. The findings contribute to our understanding of how specific news literacy behaviors (NLBs), such as evaluating sources, verifying news content, and sharing responsibly can minimize exposure to and mitigate the impact of fake news.

Non-News Websites Expose People to More Political Content Than News Websites: Evidence from Browsing Data in Three Countries

ABSTRACT Most scholars focus on the prevalence and democratic effects of (partisan) news exposure. This focus misses large parts of online activities of a majority of politically disinterested citizens. Although political content also appears outside of news outlets and may profoundly shape public opinion, its prevalence and effects are under-studied at scale. This project combines three-wave panel survey data from three countries (total N = 7,266) with online behavioral data from the same participants (over 106M visits). We create a multi-lingual classifier to identify political content both in news and outside (e.g. in shopping or entertainment sites). We find that news consumption is infrequent: just 3.4% of participants’ online browsing comprised visits to news sites. Only between 14% (NL) and 36% (US) of these visits were to news about politics. The overwhelming majority of participants' visits were to non-news sites. Although only 1.6\\% of those visits related to politics, in absolute terms, citizens encounter politics more frequently outside of news than within news. Out of every 10 visits to political content, 3.4 come from news and 6.6 from non-news sites. Furthermore, exposure to political content outside news domains had the same – and in some cases stronger - associations with key democratic attitudes and behaviors as news exposure. These findings offer a comprehensive analysis of the online political (not solely news) ecosystem and demonstrate the importance of assessing the prevalence and effects of political content in non-news sources.

Attention-grabbing news coverage: Violent images of the Black Lives Matter movement and how they attract user attention on Reddit.

Portrayals of violence are common in contemporary media reporting; they attract public attention and influence the reader's opinion. In the particular context of a social movement such as Black Lives Matter (BLM), the portrayal of violence in news coverage attracts public attention and can affect the movement's development, support, and public perception. Research on the relationship between digital news content featuring violence and user attention on social media has been scarce. This paper analyzes the relationship between violence in online reporting on BLM and its effect on user attention on the social media platform Reddit. The analysis focuses on the portrayal of violence in images used in BLM-related digital news coverage shared on Reddit. The dataset is comprised of 5,873 news articles with images. The classification of violent images is based on a VGG19 convolutional neural network (CNN) trained on a comprehensive dataset. The results suggest that what significantly affects user attention in digital news content is not the display of violence in images; rather, it is negative article titles, the news outlet's political leanings and level of factual reporting, and platform affordances that significantly affect user attention. Thus, this paper adds to the understanding of user attention distributions online and paves the way for future research in this field.

STRATEGI RRI.CO.ID YOGYAKARTA DALAM UPAYA MEMBANGUN CITRA POSITIF DI YOGYAKARTA DI TENGAH ISU KLITIH

This research analyzes the agenda-setting strategies employed by the news portal rri.co.id in building a positive image of Yogyakarta City regarding the phenomenon of "klitih." Through interviews with rri.co.id editors and journalists and an analysis of published news articles, the study reveals that rri.co.id utilizes an agenda-setting strategy by reframing the term "klitih" as "street crimes" in their reporting. This strategy aims to alleviate the perceived tension among the public and construct a positive image of Yogyakarta City. Furthermore, the research highlights the crucial role of journalists and editors in crafting accurate and responsible news content. The findings align with the agenda-setting theory, which elucidates how the media influences public attention and policymaking through agenda setting. This research provides a better understanding of the media's influence in shaping regional images and the contribution of agenda-setting strategies in the 'klitih' issue in Yogyakarta.

The News Crawler: A Big Data Approach to Local Information Ecosystems

In the past 20 years, Silicon Valley’s platforms and opaque algorithms have increasingly influenced civic discourse, helping Facebook, Twitter, and others extract and consolidate the revenues generated<em>. </em>That trend has reduced the profitability of local news organizations, but not the importance of locally created news reporting in residents’ day-to-day lives. The disruption of the economics and distribution of news has reduced, scattered, and diversified local news sources (digital-first newspapers, digital-only newsrooms, and television and radio broadcasters publishing online), making it difficult to inventory and understand the information health of communities, individually and in aggregate. Analysis of this national trend is often based on the geolocation of known news outlets as a proxy for community coverage. This measure does not accurately estimate the quality, scale, or diversity of topics provided to the community. This project is developing a scalable, semi-automated approach to describe digital news content along journalism-quality-focused standards. We propose identifying representative corpora and applying machine learning and natural language processing to estimate the extent to which news articles engage in multiple journalistic dimensions, including geographic relevancy, critical information needs, and equity of coverage.

How do different market-oriented news organizations portray news coverage about the CARES act?

Drawing from CARES Act news coverage, this study investigated how different market-oriented news organizations modulated the debate on the most expansive stimulus bill in modern U.S. history, released in 2020, during the coronavirus pandemic. A comparative approach was used, between news articles produced by a strongly market-oriented and a weakly market-oriented news outlet, both national news outlets, based in the United States. Using market theory as a guide to explore published news content, this study focuses on showing the range of debate, news sources and journalistic role performances employed in coverage of the same topic, coming from differently funded newsrooms. Some of the findings of this research demonstrate differences in the assessment of objectivity as a journalistic norm, and similarities as the indirect use of government official sources. To conclude, some implications for the field of journalism are discussed, including a revision of objectivity as a journalistic norm.

Media Framing of Identity Politics through Prejudice and Stereotype Towards the 2024 Election

This research discusses identity politics through prejudice and stereotype toward the 2024 presidential election. Identity politics refers to the way politics works in determining and classifying identities. In its development, especially in the last few elections, identity politics is full of harmful content that divides various elements of society. This study aims to analyze the media framing raised in three perspectives of online media, namely, Mediaindonesia.com, Detik.com, and Kompas.com. This study used a qualitative method using Pan & Kosicki’s framing theory. The study results show that Mediaindonesia.com's news content aims to provide normative justification while safeguarding the integrity of the NasDem party as a "movement for change." It is achieved by countering any negative and intolerant stigmas associated with identity politics issues related to the party's endorsed presidential candidate. In contrast, Detik.com is more direct in identifying social polarization categories about identity politics, highlighting the disparities between opposing views through carefully selected source quotes and rhetorical devices. Meanwhile, Kompas.com tends to take a more neutral stance, prioritizing the electability of candidates and navigating the balance between tolerance and intolerance. Framing analysis allows readers to maintain a critical perspective and comprehend how the media presents an issue in order to accomplish specific goals.

Factuality and Impartiality in the Reporting of Sexual Violence Against Children at Kompas.com and Tribunnews.com

During the pandemic, the issue of sexual violence against children in Indonesia reached 10,328 cases. One form of media that can be a source of information in Indonesia are news portals. The media should carry out objectivity in publishing news about sexual violence. News pertaining to sexual violence against children has been highlighted by the media; among them are Kompas.com and Tribunnews.com. This study aims to determine the level of factuality and impartiality of news portals in producing news content on sexual violence against children. Researchers use a quantitative approach with a descriptive nature. In this study, researchers looked at each indicator, including the level of truth, relevance, balance, and neutrality, by Westersthal's concept of objectivity. Researchers use a positivistic paradigm and descriptive content analysis research method. The results showed that the level of truth in the news on Tribunnews.com is higher while Kompas.com has not fulfilled the news with 5W + 1H, Kompas.com still has not fulfilled the level of relevance while Tribunnews.com has fulfilled the level of social reality and the audience so that the news is not subjective. At the level of balance, Kompas.com and Tribunnews.com still tend to report the perpetrator's point of view, and Tribunnews.com still uses hyperbolic language in processing news. In assessing factuality and impartiality, Kompas.com and Tribunnews.com still do not meet the objective requirements in producing news of sexual violence against children.

Fake news stance detection using selective features and FakeNET.

The proliferation of fake news has severe effects on society and individuals on multiple fronts. With fast-paced online content generation, has come the challenging problem of fake news content. Consequently, automated systems to make a timely judgment of fake news have become the need of the hour. The performance of such systems heavily relies on feature engineering and requires an appropriate feature set to increase performance and robustness. In this context, this study employs two methods for reducing the number of feature dimensions including Chi-square and principal component analysis (PCA). These methods are employed with a hybrid neural network architecture of convolutional neural network (CNN) and long short-term memory (LSTM) model called FakeNET. The use of PCA and Chi-square aims at utilizing appropriate feature vectors for better performance and lower computational complexity. A multi-class dataset is used comprising 'agree', 'disagree', 'discuss', and 'unrelated' classes obtained from the Fake News Challenges (FNC) website. Further contextual features for identifying bogus news are obtained through PCA and Chi-Square, which are given nonlinear characteristics. The purpose of this study is to locate the article's perspective concerning the headline. The proposed approach yields gains of 0.04 in accuracy and 0.20 in the F1 score, respectively. As per the experimental results, PCA achieves a higher accuracy of 0.978 than both Chi-square and state-of-the-art approaches.

Exploring the Role of Emotions in Arabic Rumor Detection in Social Media

With the increasing reliance on social media as a primary source of news, the proliferation of rumors has become a pressing global concern that negatively impacts various domains, including politics, economics, and societal well-being. While significant efforts have been made to identify and debunk rumors in social media, progress in detecting and addressing such issues in the Arabic language has been limited compared to other languages, particularly English. This study introduces a context-aware approach to rumor detection in Arabic social media, leveraging recent advancements in Natural Language Processing (NLP). Our proposed method evaluates Arabic news posts by analyzing the emotions evoked by news content and recipients towards the news. Moreover, this research explores the impact of incorporating user and content features into emotion-based rumor detection models. To facilitate this investigation, we present a novel Arabic rumor dataset, comprising both news posts and associated comments, which represents a first-of-its-kind resource in the Arabic language. The findings from this study offer promising insights into the role of emotions in rumor detection and may serve as a catalyst for further research in this area, ultimately contributing to improved detection and the mitigation of misinformation in the digital landscape.

Kullanıcı Deneyimli Haber İçerikleri Bağlamında Etkileşimli İnfografik Haberler

Geleneksel habercilikte yaşanan tek taraflı iletim süreci -internet haberciliği ile birlikte- iki taraflı bir iletişim biçim ve biçemine dönüşmüştür. 2000’li yıllardan itibaren internet ve diğer dijital teknolojilerin habercilik alanında kullanılmasıyla birlikte farklı habercilik uygulamaları ortaya çıkarken; haberin ve bilgilerin sık güncellendiği, hızla değiştiği ve yoğun bilgi bombardımanına maruz kalındığı bu dönemde -haber kuruluşları- okuyucuları ile farklı yaklaşımlarla iletişim kurmaya çalışmışlardır. Zamanla, gelişen teknolojik olanaklar ve bu bağlamda değişen haber tüketim eğilimlerine koşut olarak, çeşitli çoklu ortam platformlarında da haber sunumları söz konusu olmaya başlamıştır. Etkileşimlilik ve habere yorum yapabilme özellikleri sayesinde okuyucularına farklı deneyimleme olanakları sunan söz konusu haber platformları, haber içeriğindeki karmaşık bilgi ve verileri hızlı ve anlaşılır bir şekilde iletmek ve de haberin görsel öyküsünü aktarabilmek için; durağan, devinimli ve etkileşimli infografik tasarım uygulamalarıyla sunma yoluna gitmiştir. Kullanıcı deneyimine dayalı etkileşimli infografik haberler sayesinde; okuyucu, pasif haber tüketiciliğinden aktif haber yararlanıcısına dönüşülebilmekte ve daha çok bilgiye ulaşılabilmektedir. Nitel araştırma bağlamında betimleme yöntemleriyle gerçekleştirilen bu araştırmada; -gelişen web teknolojilerinin haber tüketim eğilimlerine etkisi bağlamında- kullanıcı deneyimine dayalı etkileşimli infografik habercilik üzerinde durulmaktadır. Etkileşimli infografik haberlerin biçim, içerik ve sunum biçemleri yönünden ele alındığı çalışmada; söz konusu uygulamaların verimlilikleri, durağan haberlerden farkları ve grafiksel nitelikleri irdelenerek öneminin ortaya konması amaçlanmaktadır.