Original News Research Articles

Risky business: How metrics obfuscate journalistic values with traffic volumes in digital news production

Based on ethnography from Australian digital newsrooms, this research shows how content production is split into two forms: Original news reporting is considered an act of ‘journalistic discovery,’ while content produced to appease metric indicators is considered an act of ‘metric confirmation.’ By conceptualising the digital space as a “glut of occurrences” (Tuchman, 1978: p.44-45) to be filled, the two case studies shown in this work inform how temporality and metrification intertwine to posit metric confirmation as low-risk, low-cost, high-gain work, while acts of journalistic discovery are comparatively high-risk and high-cost, with unknown outcomes. I argue that the inundation of metrics into newsrooms obfuscates other more crucial news values and poses challenges for the future of journalism when digital distribution is increasingly dependent on third parties while responsibility for commercial success has been shifted onto editorial staff.

Risk Factors and Scoring Systems to Predict the Mortality Risk of Afebrile Adult Patients with Monomicrobial Gram-Negative Bacteremia: A 10-Year Observational Study in the Emergency Department.

The mortality rate of afebrile bacteremia has been reported to be as high as 45%. This investigation focused on the risk factors and predictive performance of scoring systems for the clinical outcomes of afebrile patients with monomicrobial gram-negative bacteria (GNB) in the emergency department (ED). We conducted a retrospective analysis of afebrile adult ED patients with monomicrobial GNB bacteremia from January 2012 to December 2021. We dissected the demographics, clinical pictures, and laboratory investigations. We applied five scoring systems and three revised systems to predict the clinical outcomes. There were 600 patients included (358 males and 242 females), with a mean age of 69.6 ± 15.4 years. The overall mortality rate was 50.17%, reaching 68.52% (74/108) in cirrhotic patients. Escherichia coli was the leading pathogen (42.83%). The non-survivors had higher scores of the original MEDS (p < 0.001), NEWS (p < 0.001), MEWS (p < 0.001), qSOFA (p < 0.001), and REMS (p = 0.030). In univariate logistic regression analyses, several risk factors had a higher odds ratio (OR) for mortality, including liver cirrhosis (OR 2.541, p < 0.001), malignancy (OR 2.259, p < 0.001), septic shock (OR 2.077, p = 0.002), and male gender (OR 0.535, p < 0.001). The MEDS demonstrated that the best predictive power with the maximum area under the curve (AUC) was measured at 0.773 at the cut-off point of 11. The AUCs of the original NEWS, MEWS, qSOFA, and REMS were 0.663, 0.584, 0.572, and 0.553, respectively. We revised the original MEDS, NEWS, and qSOFA by adding red cell distribution width, albumin, and lactate scores and found a better predictive power of the AUC of 0.797, 0.719, and 0.694 on the revised MEDS ≥11, revised qSOFA ≥ 3, and revised NEWS ≥ 6, respectively. The original MEDS, revised MEDS, revised qSOFA, and revised NEWS were valuable tools for predicting the mortality risk in afebrile patients with monomicrobial GNB bacteremia. We suggested that clinicians should explore patients with the risk factors mentioned above for possible severe infection, even in the absence of fever and initiate hemodynamic support and early adequate antibiotic therapy in patients with higher scores of the original MEDS (≥11), revised MEDS (≥11), revised NEWS (≥6), and revised qSOFA (≥3).

GAMC: An Unsupervised Method for Fake News Detection Using Graph Autoencoder with Masking

With the rise of social media, the spread of fake news has become a significant concern, potentially misleading public perceptions and impacting social stability. Although deep learning methods like CNNs, RNNs, and Transformer-based models like BERT have enhanced fake news detection. However, they primarily focus on content and do not consider social context during news propagation. Graph-based techniques have incorporated the social context but are limited by the need for large labeled datasets. To address these challenges, this paper introduces GAMC, an unsupervised fake news detection technique using the Graph Autoencoder with Masking and Contrastive learning. By leveraging both the context and content of news propagation as self-supervised signals, our method reduces the dependency on labeled datasets. Specifically, GAMC begins by applying data augmentation to the original news propagation graphs. Subsequently, these augmented graphs are encoded using a graph encoder and subsequently reconstructed via a graph decoder. Finally, a composite loss function that encompasses both reconstruction error and contrastive loss is designed. Firstly, it ensures the model can effectively capture the latent features, based on minimizing the discrepancy between reconstructed and original graph representations. Secondly, it aligns the representations of augmented graphs that originate from the same source. Experiments on the real-world dataset validate the effectiveness of our method.

Bias of AI-generated content: an examination of news produced by large language models

Large language models (LLMs) have the potential to transform our lives and work through the content they generate, known as AI-Generated Content (AIGC). To harness this transformation, we need to understand the limitations of LLMs. Here, we investigate the bias of AIGC produced by seven representative LLMs, including ChatGPT and LLaMA. We collect news articles from The New York Times and Reuters, both known for their dedication to provide unbiased news. We then apply each examined LLM to generate news content with headlines of these news articles as prompts, and evaluate the gender and racial biases of the AIGC produced by the LLM by comparing the AIGC and the original news articles. We further analyze the gender bias of each LLM under biased prompts by adding gender-biased messages to prompts constructed from these news headlines. Our study reveals that the AIGC produced by each examined LLM demonstrates substantial gender and racial biases. Moreover, the AIGC generated by each LLM exhibits notable discrimination against females and individuals of the Black race. Among the LLMs, the AIGC generated by ChatGPT demonstrates the lowest level of bias, and ChatGPT is the sole model capable of declining content generation when provided with biased prompts.

Translation features of BBC media article headlines (evidence from English and Russian equivalents)

The aim of this paper is the analysis of the translation features, typical of BBC article headlines. The material included 107 news headlines selected randomly, which had their Russian equivalents. A semantic and comparative analysis served as the research method. The close attention to media texts in the era of digital technology proliferation explains the relevance of the study. The findings show that translation equivalents convey both the communicative and pragmatic potential of the original headlines. For this purpose, a complex of semantic transformations is used for maintaining the adequate meaning of original news in the target language, considering background knowledge of the target audience. The theoretical value lies in the fact that media headlines constitute an individual sub-genre which requires special research. The results can be used in the practice of teaching translation techniques to students specializing in linguistics and translation studies.

О центростремительной тенденции в комментировании новостей в социальных сетях

The article considers the ratio of centripetal and centrifugal tendencies in online commenting. The research objective was to describe the consistency of comments to news texts published in social networks. This article focuses on the results obtained on the centripetal trend. The approach and methodology were based on the scientific hypothesis about the self-developing nature of communication in social networks. According to this hypothesis, the degree of subjectivity of online news discussion can be transmitted to the dialogue through the text of its comments. The original news text becomes the basis for comments, which are independent texts focused on the original news. As a result, the original text turns into a complex branched network. Comments develop as chains or branches of discussion responses, which can be analyzed. This research featured an Internet text from the Vkontakte social network, its comments, and their mental map. The ratio of centripetal and centrifugal tendencies revealed a certain pattern: the consistency of the original text determined the consistency of comments. The patterns of their correlation showed how the self-developing nature of communication created new linguistic phenomena. The article is of interest to specialists in Internet communication and social networks.

Information technology infrastructure and earnings management strategy: evidence from a quasi-natural experiment

ABSTRACT Taking the ‘Broadband China’ programme as a quasi-natural experiment, we intend to explore the effect of information technology infrastructure (Hereinafter, ITI) on earnings management strategy. Our results show that with the office location city selected as the pilot city, the firm will strategically reduce the accrual-based earnings management and increase real earnings management. In addition, we find that ITI can reduce audit delay, decrease financial restatement, increase analyst coverage, improve analyst forecast accuracy, promote the media to release original news, and increase investor postings, which is consistent with the view that ITI can improve stakeholders’ monitoring efficiency. Cross-sectional analyses show that the impact of ITI on earnings management strategy is more pronounced for firms with low corporate governance efficiency. This study is helpful to further understand the externalities of ITI to firms’ behaviour.

Research on News Use of Social Media in The Context of New Media

The understanding of social media is to look at "social" and "media" both separately and in combination, to look at the characteristics and ways of social interaction, to look at the characteristics and forms of media, and to study the close relationship between the two. Social communication in the form of media or the choice of media in the form of social communication, and different discussion pointcuts have different understandings of social media.In the history of the development of human communication, human communication activities and the development of media technology have always been accompanied and closely related, and every progress of media technology always gives birth to and reconstructs the new communication ecology of human beings. Social media is a new media rooted in the Internet environment, which rises rapidly.News and communication workers or learners should not only adapt to the communication influence and changes brought by social media, but also adhere to the classic forms and methods of the original news media. Tradition and the emerging are never opposites, but complement and complement each other.

Is news media sharing an active framing process? Examining whether individual tweets retain news media frames about climate change

Abstract Social network sites have become a primary tool for consuming and sharing news. Typically, sharing a news media article on social media involves two pieces of information: the news media frame and the individual’s commentary. With framing as an active, iterative process, we examine the extent to which individuals replicate or reframe when sharing news about climate change to Twitter. First, we conducted a framing analysis of news about climate change. Then, we assessed whether tweets sharing the news media articles in our framing analysis (n = 9,557) retained or reframed the original frame. Results show 74.64% of the tweets were not a direct replication of the original news media frame. Furthermore, the likelihood that an individual chose to reframe depended on the frame of the original article. Overall, our study illustrates how a constructionist framing approach can be applied to understand the dynamic nature of news sharing on Twitter.

Особенности адаптации при переводе новостных текстов (на примере новостей о Китае в русскоязычных и англоязычных СМИ)

This paper deals with adapted translations of news texts. The aim of the study is to identify differences between original and translated news texts and the factors that influence the change in the form and content of a text in the interlingual transmission of information. The scientific novelty is that for the first time it considers adaptation in the translation of news texts based on a comparative analysis of the original news text in Chinese and its translations into Russian and English. As a result of the study, it has been found that the translation of the news text in the media uses different techniques of adaptation and results in different translated texts. The changes depend both on the linguistic and stylistic features of the news genre and on extra-linguistic factors.

Decentralized News Publication Platform

Fake News has become a huge alarming issue since the previous few years.It can be used to influence people on any political, economical or social topics and change people’s thoughts on a particular subject. We’re using a blockchain based technique to overcome this problem. More specifically the proposed approach uses concepts of customized proof of authority and proof of truthfulness consensus algorithm serving as an incentive mechanism to determine the integrity of fake news. As Blockchain is a decentralized system no one will be able to tamper with the original news. Also, we are maintaining the reputation score of each organization. Due to fear of lowering credibility score, no one will produce fake news and the probability of fake news getting viral will be reduced. This platform which is a blockchain based Decentralized application can provide normal readers on the platform with a reliable way of verifying the content and the source by which it gets published. Our work demonstrates that the solutions proposed in this paper ensure data integrity, data security, data transparency, and data traceability by consideration of such a blockchain-based framework for tackling fake news. Key Words: Decentralized Applications, Decentralised Autonomous Organisation, Decentralized Exchange, Peer To Peer, Ethereum Virtual Machine

Mc-DNN

With the advancement of technology, social media has become a major source of digital news due to its global exposure. This has led to an increase in spreading fake news and misinformation online. Humans cannot differentiate fake news from real news because they can be easily influenced. A lot of research work has been conducted for detecting fake news using Artificial Intelligence and Machine Learning. A large number of deep learning models and their architectural variants have been investigated and many websites are utilizing these models directly or indirectly to detect fake news. However, state-of-the-arts demonstrate the limited accuracy in distinguishing fake news from the original news. We propose a multi-channel deep learning model namely Mc-DNN, leveraging and processing the news headlines and news articles along different channels for differentiating fake or real news. We achieve the highest accuracy of 99.23% on ISOT Fake News Dataset and 94.68% on Fake News Data for Mc-DNN. Thus, we highly recommend the use of Mc-DNN for fake news detection.

Does Third-Party Fact-Checking Increase Trust in News Stories? An Australian Case Study Using the “Sports Rorts” Affair

Given the centrality of news media to democracy, it is concerning that public trust in media has declined in many countries. A potential mechanism that may reverse this trend is independent fact-checking to adjudicate competing claims in news stories. We undertake a survey experiment on a sample of 1608 Australians to test the effects of fact-checking on media trust using a real-life case study known as the “sports rorts” affair. We construct duplicate news articles from two national media outlets (i.e. ABC.net.au, news.com.au) containing a senior government minister’s real-life false claim that public funds were not used for political advantage immediately before an election. Half of the participants are exposed to a third-party fact check, which confirms the Minister’s claim is verifiably false, the other half are not. All respondents are asked to evaluate the story’s and news outlets’ trustworthiness. Contrary to our expectations we find a backfire effect whereby independent fact-checking decreases readers’ trust in the original news story and outlet. This negative relationship is not conditional on partisanship or the media source. Our study provides a cautionary tale for those expecting third-party fact-checks to increase media trust and we outline several avenues by which fact-checkers might overcome this.

Daily News Verification as Organizational Work: A Study of Taiwan’s Four Major Newspapers

&lt;p&gt;本研究深度訪談四大報共30 位記者與主管，從組織角度探析日常新聞查證慣例與實踐。本研究發現查證慣例主要起於新聞個案，浮現於組織互動。除非是重要新聞，否則報社多將查證視為記者工作與責任。報社對新聞查證的要求顯現於守門關卡多寡、核稿者是否有路線相關知識，及核稿者與記者的互動。由此來看也可見報社對紙本的查證要求高於即時新聞，尤其後者「搶快」、「爭先」透過組織激化，加上其能接受少量訊息且可不斷更新，提高容忍新聞錯誤「瑕疵」的程度。最後，本研究強調報社能發揮團體優勢，進行查證。尤其跨線查證能獲得不同路線消息來源的回應、交叉確認、分頭查證持續式新聞，甚至發現更多證據，改變原有新聞設計，提高新聞品質。&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;&lt;p&gt;This study conducted in-depth interviews with 30 journalists, who work for Taiwan’s four major newspapers, to analyze the practice of daily news verification at an organizational level. The study found that news verification norms as a routine emerge during the news production process and in organizational interactions. Except for important and influential news stories, the responsibility for news verification is always regarded as the job of individual journalists rather than that of the organization. Further, the news organization’s policy requirements of news verification depend upon the number of gatekeepers, sub-editors’ domain and contextual knowledge, and the interaction between sub-editors and journalists. Based on the above, the news organizations have higher standards of news verification for print news than for online real-time news. Certain flaws in online real-time news stories, which can be short and continuously updated, are often tolerable since they have to be fast and be the first in a competitive market. Finally, the study emphasizes that news verification can be more efficiently accomplished by coordinating journalists of different specialties, interviewing each of the interested parties in different fields, and collaboratively cross-checking information for corroboration when covering the continuing news. This process may even uncover more evidence that may change the original news coverage and improve the overall news quality.&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;

Rethinking International News Translations: Toward a Foreignizing Approach to News Events Translations

The present paper investigates the ideological manipulation that creeps in translated news headlines and falsifies the produced translated version since such process involves both the imposition of dominant ideologies and the negative portrayals of the other in mediated news. Thus, international news translation basically exploits and manipulates the original news events in such a way that misrepresents the image of otherness and creates a positive representation of patrons. In this vein, this paper brings to the fore the influence of extra-textual factors on the translation of headlines. Many strategies and translation techniques are utilized and translators do intervene to align produced headlines with the two networks’ ideological affiliations and editorial policies. The present paper adopts descriptive approach where I attempted to compare translated news headlines and pinpoint the alterations and transformations undertaken over them, also it aims to call for rethinking strategies undertaken while translating global news in a cosmopolitan context where openness to the other and appreciation of difference are conducive to an effective cross cultural and linguistic interactions. Accordingly, it proposes foreignizing approach to global news translation because it retains the image of otherness which is essential in the original event.

Distance to news: how social media information affects bribe-giving in India

While recent empirical evidence reveals some effective interventions in preventing corruption among bureaucrats and politicians, there has been little discussion on how to prevent the bribe-giving behavior of ordinary citizens. This paper investigates the role of social media information in influencing the supply of bribes by citizens instead of the demand side. We, therefore, developed and published an original news application in India and implemented a 3-month experiment. In this application, we randomly circulate live news related to corruption to users and incorporate a lab experiment into the app system to elicit users’ bribery behavior every week. We find that corruption news involving politicians within a close geographical proximity lowers users’ moral costs against the anti-social bribery act, leading to an increase in the amount of bribes. However, news of accused citizens and officials within the geographic proximity increases their moral cost against bribes and decreases the amount. This suggests that individually tailored local information on corruption may be an effective tool to reduce citizens’ supply of bribes.

Is Social Media Killing Local News? An Examination of Engagement and Ownership Patterns in U.S. Community News on Facebook

This article focuses on two forces linked to declines in coverage of genuinely local civic affairs: (a) the impact of increasing corporate consolidation in ownership among news providers, and (b) the degree to which the economic incentives and logics of digital platforms may also drive editorial decision-making at news organizations away from coverage of local news. Using a unique dataset of 2.4 million Facebook posts published by local news organizations in three U.S. states between 2018 and 2019, we find evidence that both factors matter. Long-running trends towards conglomeration in the industry have a demonstrable impact on how much and what kinds of local news gets posted on the site, but we also find that the platform itself may incentivize certain types of coverage over others. Specifically, we find organizations owned by chains are more likely to post duplicative, repurposed content that receive fewer interactions per post—evidence of quantity being valued over quality—as well as higher rates of engagement with national, hard news stories over unique content about local affairs. Findings shed light on how Facebook—combined with media ownership structures—may hinder the task of serving local communities with original news that satisfies important civic needs.

Investigative journalism and media capture in the digital age

This paper develops a model of investigative journalism and media capture in the market for news with the depreciation of the value of news over time and a limited exclusive supply period of original news due to copying by other media outlets. We make distinctions between traditional media outlets that engage in investigative journalism and fringe digital media that mainly copy and spread original news created elsewhere. We show that the quantity and quality of news with investigative journalism decrease and media capture is more likely as digital technologies induce a lower fixed cost of entry for the fringe firms and a shorter exclusive supply period of news. These results may explain why there is scant evidence for the conventional view that more media outlets lead to higher quality news and less political capture, despite proliferation of news and information outlets in the digital age.

Text Summarization with K-Means Method

Text Summarization is a tool used to generate a short form of text that contains important information that is needed by the user automatically. In this study, Text Summarization was conducted on Indonesian news using K-Means method. The news is taken from CNN Indonesia with a free topic. K-Means is used to classify sentences that already have weight in the news with 2 clusters, namely text summaries and not text summaries. The initial centroid is selected based on the sentence with the largest value and the sentence with the smallest value. The test conducted on Indonesian news with a total 50 news and tested for feasibility using a questionnaire. K-Means was successfully summarizing the news with an average 27.3 % of original news length and gain 87% good summarize based on respondents from questionnaire.

Social Media and Trust in News: An Experimental Study of the Effect of Facebook on News Story Credibility

People increasingly turn to social media to get their daily news updates. Still, we are only beginning to understand how this development affects people’s perceptions of consumed news stories. The article reports on an experiment designed to investigate the effect the distribution of a news story in social media (Facebook) has on news message credibility. A control group was exposed to a news story on an original news website, and treatment groups were exposed to the same news story shared on Facebook. Results demonstrate that distribution via Facebook affects the credibility of the news story. The effect is strongest when politicians are intermediary-senders, and to some extent depend on the party affiliation of intermediary-sender and the social media audience. In the context of fake news, the results are reassuring: people are less trustful of news they consume through social media. However, the results also suggest that social media news sharing can contribute to the long-term decrease in trust in news.