News Media Reports Research Articles

The metaverse-industrial complex

ABSTRACT This paper explores the role that Nvidia is playing in shaping the Metaverse for industrial applications in simulation and automation. As the world's largest manufacturer of Graphics Processing Units for computationally intensive tasks and one of the largest corporations by market capitalization, Nvidia has remained relatively overlooked within critical discussions of ‘Big Tech', the Metaverse, and Artificial Intelligence. This paper draws on news media reports and publicly accessible Nvidia publications such as developer documentation and press releases to understand the role of Nvidia in shaping the Metaverse for industrial enterprises. It conceptualises the ‘Metaverse-Industrial Complex' to theorise the processes of market capture, territorialization, and platform expansionism occurring within the convergence of the Metaverse and Artificial Intelligence that is reconfiguring the governance of public and private assets and infrastructure. Through an examination of Nvidia's ‘Omniverse' platform and network of industrial partnerships, the paper examines the Metaverse-Industrial Complex as an assemblage of developer tools, platforms, data standards, and industry partnerships that converge machine learning and 3D graphics into photo-realistic ‘digital twin’ simulations of physical objects and environments.

An LLM-Based Inventory Construction Framework of Urban Ground Collapse Events with Spatiotemporal Locations

Historical news media reports serve as a vital data source for understanding the risk of urban ground collapse (UGC) events. At present, the application of large language models (LLMs) offers unprecedented opportunities to effectively extract UGC events and their spatiotemporal information from a vast amount of news reports and media data. Therefore, this study proposes an LLM-based inventory construction framework consisting of three steps: news reports crawling, UGC event recognition, and event attribute extraction. Focusing on Zhejiang province, China, as the test region, a total of 27 cases of collapse events from 637 news reports were collected for 11 prefecture-level cities. The method achieved a recall rate of over 60% and a precision below 35%, indicating its potential for effectively and automatically screening collapse events; however, the accuracy needs to be improved to account for confusion with other urban collapse events, such as bridge collapses. The obtained UGC event inventory is the first open access inventory based on internet news reports, event dates and locations, and collapse co-ordinates derived from unstructured contents. Furthermore, this study provides insights into the spatial pattern of UGC frequency in Zhejiang province, effectively supplementing the statistical data provided by the local government.

Disembedded politics: Discourses on Neoliberal Labor Law reforms in Lithuania (2014–2016)

Since regaining its independence in 1991, Lithuania has undergone a process of chaotic privatization in which labor was systematically disempowered, above all, by the targeted erosion of labor rights formally endorsed in the pre-existing Soviet labor code. In the newly legitimized and aggressive pro-business environment of the post-Soviet era, organized labor's residual power was seen as an anachronistic impediment to the power of capital in reshaping society and the economy. This article investigates the political dynamics of disembedded labor law reform in Lithuania, which enabled neoliberal reformers to legislate while disregarding broader societal interests and imposing unilateral changes in labor relations. A content analysis of 852 news media reports on labor law reforms published in 2014–2016 was used to demonstrate how discursive and institutional exclusion and sequencing were employed by the neoliberal government to circumvent the interests of major social and economic groups, resulting in the passage of pro-business legislation. The implications of resorting to disembedded politics in the labor reform process are discussed.

Personalization of tech corporations: Examining personalized news and the media reputation of Google, Facebook, and Apple in Swiss news media

Tech corporations, such as Google, Facebook, and Apple, have increasingly become the focus of public media attention and are subject to public scrutiny due to their prominence and scandals. Often, the news media reports on the corporations’ chief executive officers and founders as representatives of the corporations to make complex company-related information comprehensible and gain more public attention. The personalization trend in the news media has turned some corporate leaders into celebrities and is linked to tech companies’ media reputations, that is, the evaluations of tech companies in the news media. However, research on personalization in corporate news is rare and conflicting, and whether and how personalization is linked to the media reputations of Big Tech corporations is not yet clear. By focusing on different personalization types, this study investigates the relationship between personalization and the evaluation of tech companies in the news. A quantitative content analysis of media articles ( N = 5234) in Swiss news outlets revealed that the news on tech companies is frequently personalized, and personalized news is more negative and more often related to the social aspects of tech corporations than non-personalized news. Our study indicates that personalization is used as a journalistic style in the news about tech corporations but is most common in negative reporting in which the role of tech corporations in society is critically assessed.

Evaluation Algorithm of TV Program Host Performance Based on Emotion Recognition

With the rapid development of information technology and system norms and the incongruity of personnel training speed, the development of news media reports has caused a large number of negative effects. From the current situation of the development of news media reports, due to the lack of perfect management, the difference in media literacy between users and enterprises, entertainment to death, rampant consumer culture, and many other factors, the network media reports are chaotic. In the proposed model Fuzzy Fredholm Integral Market Efficiency (FFI-ME) for the media coverage. With the FFI-ME model, the information technology computes the news media data for the estimation of the coverage to achieve market efficiency. The FFI-ME model uses the Fredholm Integral model to compute the market efficiency for the media data in China. The FFI-ME model computes the news data in China and clusters the data for the classification and detection of the instances in the equation. Through the Integral Fredholm model, the features of the news are estimated to compute the media coverage and efficiency of the news media data. The model uses the Deep learning model for the classification of the data instance in the media data. The simulation analysis expressed that the proposed FFI-ME model achieves a higher classification data accuracy of the 98%.

Transitional care programs for older adults moving from hospital to home in Canada: A systematic review of text and opinion.

Investing in transitional care programs is critical for ensuring continuity of health and coordinated care for older adults transitioning across health settings. However, literature delineating the scope of transitional care programs across Canada is limited. The aim of this systematic review of text and opinion is to characterize Canadian transitional care programs for older adults transitioning from hospital to home. Following JBI guidelines for systematic review of text and opinion, we conducted a search of Canadian grey literature sources published online between 2016 to 2023. A 3-phase search was undertaken for: 1) Canadian databases and organizational websites; 2) advanced Google search of national sources and news media reports; and 3) advanced Google search of provincial/territorial sources. Two reviewers independently screened sources for eligibility against inclusion criteria. Data were extracted by one reviewer and verified by a second. Textual data were extracted from multiple sources to characterize each transitional care program. Grey literature search produced a total of 17,092 text and opinion sources, identifying 119 transitional care programs in Canada. Model of care was a key characteristic defining the design and delivery of transitional care programs within community (n = 42), hospital (n = 45), and facility-based (n = 32) settings. Programs were characterized by goal, population and eligibility, setting and length of program, intervention and services, and healthcare team members. Patient, caregiver, and health system outcomes were reported for 18 programs. The province of Ontario has the most transitional care programs (n = 84) and reported outcomes, followed by British Columbia (n = 10). Characterizing transitional care programs is important for informing health services planning and scaling up of transitional care program models across Canada. Recognizing transitional care programs as a core health service is critical to meet the health care needs of older adults at the right time and place. PROSPERO ID 298821.

Crash Contributing Factors and Patterns Associated with Fatal Truck-Involved Crashes in Bangladesh: Findings from the Text Mining Approach

Despite extensive research on traffic injury severities, relatively little is known about the factors contributing to truck-involved crashes in developing countries, especially in the context of Bangladesh. Because of the unavailability of authentic crash data sources, this study collected data from alternative sources such as online English news media reports. The current study prepared a database of 144 truck-involved fatal crash reports during the period of 12 months (January 2021 to December 2021). The crash reports contain a bag of 15,300 words. Several state-of-the-art text mining tools were utilized to identify crash patterns, including word cloud analysis, word frequency analysis, word co-occurrence network analysis, rapid automatic keyword extraction, and topic modeling. The analysis revealed several important crash contributing factors, such as the type of vehicle involved (auto-rickshaw, bus, van, motorcycle), the manner of collision (head-on), the time of the day (morning, night), driver behavior (speeding, overtaking, wrong-way driving), and environmental factors (dense fog). In addition, “coming from opposite direction” and “head-on collision” are two important sequences of events in truck-involved crashes. Truck drivers are also involved in crashes with trains at rail crossings. The findings of this research can assist policymakers in identifying crash avoidance strategies to lower truck-related crashes in Bangladesh.

Extending Kingdon's Multiple Streams Policy Framework Through an Analysis of How Community Health Workers in India Are Driving Policy Changes.

In this paper we develop and provide a novel account of the process through which the Accredited Social Health Activists (ASHAs), a cadre of seemingly powerless community health workers in India, are navigating a complex policy process to incrementally achieve their goals. ASHAs have been demanding better working conditions, better compensation, and regularisation as public service employees through protests and strikes and have managed to gain concessions from both the Central and various State governments. We observed two important aspects that emerged: (a) ASHAs achieved incremental increases in their wages despite being the lowest in the health system hierarchy, and, (b) major gains were made during the 2years of the pandemic. We examine and analyse ASHAs' engagement and strategies used, both overt and covert, sometimes with the government, and the role of other actors in determining these policy outcomes. We do so by drawing on academic literature and news media reports; we trace the changes in ASHAs' wages by tying together key events, 'windows of opportunity', and actions of 'policy entrepreneurs' involved in the process.In doing so, we further develop and propose an extension to Kingdon's multiple streams policy framework through the addition of a 'narrative stream'.

Internet Public Opinion on Media Report Semantics of U.S. House Speaker Nancy Pelosi’s Visit to Taiwan

On August 2, 2022, the U.S. House Speaker, Nancy Pelosi visited Taiwan. China expressed strong dissatisfaction, triggering the 4th Taiwan Strait Crisis. We investigated the differences in the frameworks constructed by the news media and the public opinion about the “event of Nancy Pelosi’s visit to Taiwan”. Semantics and “public opinions” associated with the report contents of Nancy Pelosi’s visit to Taiwan were analyzed using the online news media of major newspapers in Taiwan, as well as the social media PTT Gossiping. The Python programming language was used for web crawling, and the word frequency database snowNLP in Python was adopted as a sentiment analysis tool. The research results showed that the emphasis of different media in different periods was slightly different. The topics of netizens in PTT Gossiping were often affected by the topic framework of the news media. However, the public developed their discussion topics. News media reports did not have a framing effect on the emotional changes of common words used by the public about the issues.

Quality of online media reports of suicide and attempted suicide in India.

News media reporting of suicide may influence the masses toward or against suicidal behavior. So, responsible reporting by news media is important to protect vulnerable people from the deleterious effects of media reporting. World Health Organization has issued guidelines for media reporting of suicide in this regard. We planned this research to evaluate the quality of online news media reports of suicide and attempted suicides in India. We assessed a total of 210 news reports about suicide and attempted suicides (70 English, 70 Malayalam, and 70 Hindi) to evaluate the reporting of harmful and protective characteristics in news according to the World Health Organization guidelines for reporting suicide in media. We found all three language media reported almost all potentially harmful characteristics with gender (100%), location/site of suicide in the headline (97.61%), precipitating life events (95.24%), mentioning term 'Suicide' in the headline (98.10%), monocausal explanation for suicidality (90.95%), suicide method in the headline (90.95%), an accompanying photo (92.38%), and suicide method (93.81%) being reported with highest frequency. Potentially protective characteristics were not included in most news reports with poor focus on awareness information. Vernacular language media were poor as compared to English news media about the quality of reporting suicide. We found poor adherence to reporting guidelines by online news media for reporting of suicide with poor coverage of educative and awareness information for the general public. It underlines the need for improving awareness among media professionals about responsible reporting of suicide.

News media reporting on Scottish cases in which women kill following domestic abuse

This paper presents the results of a feminist analysis of news media reports related to Scottish cases in which women killed following domestic abuse. The findings show that problematic narratives have prevailed within the reporting of cases of this type and that, at a time when knowledge and understanding of domestic abuse was improving in Scotland, news media presentations of women who kill following abuse were worsening. It is argued that the reporting landscape was changed by an especially high-profile case of this type, and that judicial statements also exert a significant influence on how cases of this type are reported. It is concluded that more must be done to ensure that reporting of these cases follows national guidelines related to the reporting of violence against women, especially since reporting is likely to influence public perceptions and understandings of the subject matter.

Political referenda and investment: Evidence from Scotland

We present evidence that referenda have a significant, detrimental outcome on investment. Employing an unsupervised machine learning algorithm over the period 2008-2017, we construct three important uncertainty indices underlying reports in the Scottish news media: Scottish independence (IndyRef)-related uncertainty; Brexit-related uncertainty; and Scottish policy-related uncertainty. Examining the relationship of these indices with investment on a longitudinal panel of 3,589 Scottish firms, the evidence suggests that Brexit-related uncertainty associates more strongly than IndyRef-related uncertainty to investment. Our preferred specification suggests that a one standard-deviation increase in Brexit uncertainty foreshadows a reduction in investment by 8% on average in the following year. Besides we find that the uncertainty associated with the Scottish referendum for independence while negligible at the aggregate level, relates more strongly with the investment of listed firms as well as those operating on the border with England. In addition, we present evidence of greater sensitivity to these indices among firms that are financially constrained or whose investment is to a greater degree irreversible.

An Ontology-Based Knowledge Representation Method for Typhoon Events from Chinese News Reports

Typhoons are destructive weather events. News media reports contain large amounts of typhoon information. Transforming this information into useful knowledge to provide a basis for mining typhoon knowledge and supporting disaster prevention and relief is urgently required to solve this problem. Knowledge representation can be used to address this problem, although it presents several challenges. These challenges lie in expressing the static and dynamic characteristics of typhoons and formalizing the knowledge representation method and making it suitable for machine processing. Moreover, the general Chinese time and space representation method is overly cumbersome for use in ontologies. The present study proposes an ontology-based typhoon event representation method that solves the representation problems of the typhoon static concept and dynamic features. Furthermore, it summarizes the fixed patterns of time and space in Chinese news and designs a time and space model suitable for typhoon event ontologies. From the ontology population, typhoon event ontology instances are created, and the typhoon event ontology model is applied to the analysis of typhoon processes, verifying the effectiveness of the typhoon event ontology model.

An investigation of media reports of digital surveillance within the first year of the COVID-19 pandemic.

The COVID-19 pandemic prompted a surge in digital public health surveillance worldwide, with limited opportunities to consider the effectiveness or impact of digital surveillance. The news media shape public understanding of topics of importance, contributing to our perception of priority issues. This study investigated news media reports published during the first year of the pandemic to understand how the use and consequences of digital surveillance technologies were reported on. A media content analysis of 34 high- to low-income countries was completed. The terms "COVID-19," "surveillance," "technologies," and "public health" were used to retrieve and inductively code media reports. Of the 1,001 reports, most were web-based or newspaper sources on the development and deployment of technologies directed at contact tracing, enforcing quarantine, predicting disease spread, and allocating resources. Technology types included mobile apps, wearable devices, "smart" thermometers, GPS/Bluetooth, facial recognition, and security cameras. Repurposed data from social media, travel cards/passports, and consumer purchases also provided surveillance insight. Media reports focused on factors impacting surveillance success (public participation and data validity) and the emerging consequences of digital surveillance on human rights, function creep, data security, and trust. Diverse digital technologies were developed and used for public health surveillance during the first year of the COVID-19 pandemic. The use of these technologies and witnessed or anticipated consequences were reported by a variety of media sources worldwide. The news media are an important public health information resource, as media outlets contribute to directing public understanding and shaping priority public health surveillance issues. Our findings raise important questions around how journalists decide which aspects of public health crises to report on and how these issues are discussed.

Predicting Kyasanur forest disease in resource-limited settings using event-based surveillance and transfer learning

In recent years, the reports of Kyasanur forest disease (KFD) breaking endemic barriers by spreading to new regions and crossing state boundaries is alarming. Effective disease surveillance and reporting systems are lacking for this emerging zoonosis, hence hindering control and prevention efforts. We compared time-series models using weather data with and without Event-Based Surveillance (EBS) information, i.e., news media reports and internet search trends, to predict monthly KFD cases in humans. We fitted Extreme Gradient Boosting (XGB) and Long Short Term Memory models at the national and regional levels. We utilized the rich epidemiological data from endemic regions by applying Transfer Learning (TL) techniques to predict KFD cases in new outbreak regions where disease surveillance information was scarce. Overall, the inclusion of EBS data, in addition to the weather data, substantially increased the prediction performance across all models. The XGB method produced the best predictions at the national and regional levels. The TL techniques outperformed baseline models in predicting KFD in new outbreak regions. Novel sources of data and advanced machine-learning approaches, e.g., EBS and TL, show great potential towards increasing disease prediction capabilities in data-scarce scenarios and/or resource-limited settings, for better-informed decisions in the face of emerging zoonotic threats.

The Spectacle of “Patriotic Violence” in Romania: Populist Leader George Simion’s Mediated Performance

Political actors who adapt their performance to the logic of politainment gain visibility and success in the public sphere. Such is the case of George Simion, an emerging politician and leader of the newest parliamentary party, the Alliance for the Union of Romanians (AUR), a populist radical right party that proved especially attractive to Romanian diaspora voters. This study focuses on the discursive and stylistic dimensions of Simion’s newsworthiness and mediatization. Additionally, a multiplatform analysis of his populist communication content and style aims to determine degrees of populism. As such, we propose a mixed-methods multimodal approach that combines corpus linguistics and semi-automated content analysis with thematic coding and visual semiotic analysis. The media-reported performance analysis focuses on content (<em>n</em> = 963) produced by three popular online news media outlets (<em>Digi24.ro</em>, <em>Adevărul.ro</em>, and <em>Antena3.ro</em>) between May 13th 2015 and April 30th 2022, while the analysis of Simion’s discourse examines his Telegram channel’s feed (738 messages and 383 images) between March 15th 2021 and April 30th 2022, and his authored texts published in <em>Adevărul.ro</em> (<em>n</em> = 116) between July 8th 2014 and April 30th 2022. The results indicate that news media reports are defined by conflict (aggression, violence), scandalization, negativity, emotionality, and by a prevalent use of arresting quotes that employ colloquial language (sarcasm, vulgarity). Simion’s celebrity populism is styled through an “ideal candidate,” “populist campaigner” image and framed through the emotional glorification (unionism, patriotism, Orthodoxy) of a potentially united “homeland,” a democratic space that reflects the unadulterated will of ordinary Christian-Orthodox Romanians whose sovereignty is currently undermined by corrupt political elites. He invokes historical narratives (e.g., founding fathers, retrospective utopia) reinforced through othering the EU and ethnic/sexual minorities as forces that threaten the purity of “the people.”

An Assessment of Horse-Drawn Vehicle Incidents from U.S. News Media Reports within AgInjuryNews

Some old-order Anabaptist communities rely on animal-drawn vehicles for transportation and farm work. This research examines reports involving horse-drawn vehicles found in the AgInjuryNews dataset, which provides a publicly accessible collection of agricultural injury reports primarily gathered from news media. The goals of this research are to characterize the reports and to compare results with previous research to assess the utility of using AgInjuryNews to examine horse-drawn vehicle incidents. A total of 38 reports representing 83 victims were identified. Chi-square tests comparing victim and incident traits for fatal and nonfatal injuries were significant for the victim’s role in the incident, vehicle type, presence of a motor vehicle, rear-ending by a motor vehicle, spooked horses, a victim being run over or struck by a vehicle, and a victim being ejected or falling from a vehicle. Additional analysis of incidents involving horse-drawn farm equipment showed that a significantly higher proportion of off-road incidents were fatal compared to on-road incidents. The proportion of fatal injuries in the AgInjuryNews dataset was approximately 10 times higher than observed in a study using Pennsylvania Department of Transportation (DOT) data. Compared to previous research, the AgInjuryNews reports contained a higher proportion of incidents where a motor vehicle rear-ended a horse-drawn vehicle, and fewer cases of horse-drawn vehicles being struck by motor vehicles while crossing or entering a main road and making left turns. Reports of buggy crashes found in AgInjuryNews differed from those found in a Nexis Uni search in that the bulk of the articles from Nexis Uni referred to cases involving criminal charges for impaired driving or hit-and-run crashes. While it is evident that the reports included in the sample are incidents that media sources find compelling rather than comprehensive injury surveillance, it is possible to gain new insights using the AgInjuryNews reports.

Pathogen spreading during the COVID‐19 pandemic: Understanding a global phenomenon

AbstractThis study examined news media reports published during the early months of the COVID‐19 pandemic that described people spitting, coughing, and otherwise spreading respiratory fluids to other people and objects. A search of a news archive yielded more than 800 news articles published during March, April, and May, 2020, from which N = 325 cases of intentional pathogen spreading were identified. This was during the early part of the pandemic when the world was still trying to reach an understanding of how to deal with the pandemic. Collected news articles showed that cases of intentional pathogen spreading were reported to have occurred in 14 countries on 5 continents on most days (78.3%) of the 3‐month period considered. In 43% of cases, perpetrators claimed to be infected with the SARS‐CoV‐2 virus. Frontline key workers, passersby, and retail workers were the most frequent targets. The findings suggest that more needs to be learned about intentional pathogen spreading behavior, with the goals of reducing its occurrence in future pandemics and protecting vulnerable targets.

News to me: far-right news sharing on social media

ABSTRACT News sharing on social media is ubiquitous and extends across demographics, platforms, and political ideologies. Online far-right communities are no exception, with a barrage of embedded news stories populating the social media feeds of far-right users. This has potentially profound implications for liberal democracy, especially given the propensity for far-right communities to spread disinformation via ‘fake news’. Yet, we do not know enough about how news content is embedded into far-right discourses, nor the extent to which the practice may contribute to the digital transmission of far-right ideologies. Accordingly, this paper investigates how far-right communities share news media to promulgate illiberalism on social media platforms. The paper aims to uncover the dominant discursive devices deployed to integrate news media reports into far-right discourses. To achieve this aim, this paper applies critical discourse analysis alongside conceptualisations of legitimacy and far-right ideology to an original dataset of social media posts in an Australian context. It finds that news sharing in far-right online circles may legitimise and reify far-right ideology through the juxtaposition of mainstream news media indicating the validity of far-right grievances. The paper also introduces a prototype model of news sharing legitimisation.

The Role of National Media Reporting in Supporting Defense Diplomacy Activities to Improve National Defense

One of the problems of the Republic of Indonesia's National Defense is that the minimum defense force has not been fulfilled, so policy and budgetary support are needed to increase this force, including defense equipment. This support is required from the legislature (DPR-RI), the executive (especially Bappenas and the Ministry of Finance), as well as positive public aspirations, one of the indicators of which is the direction of national mass media coverage. Regarding this effort, Defense Minister Prabowo Subianto carried out defense diplomacy activities by making a series of visits abroad, which raised pros and cons at home. Pointed starting from this background, this research aims to analyze how national online news media reports framing news regarding a series of visits to Indonesian defense diplomacy activities conducted by Defense Minister Prabowo Subianto for the October 2019-November 2021 period; and what is the impact of online news media coverage in helping support from stakeholders in supporting defense diplomacy activities to improve national defense. This research approach is qualitative. Research period October 2019-November 2021. Primary data collection techniques are through in-depth interviews with eight sources and analyzing the framing of 15 news related to 15 news in three online news media (Kompas.com. Detik.com, and Tribunnews.com). Secondary data collection techniques through library research. The results of the study show that the framing of national online news media is positive, which can be interpreted as playing a role in supporting the defense diplomacy activities carried out by Defense Minister Prabowo in the form of a series of overseas visits for the period October 2019November 2021; and positive framing by the national online news media as the aspirations of the community (public) has had a positive impact on the attitude of stakeholders (DPR-RI, Bappenas, Ministry of Finance) by responding positively to the Ministry of Defense's policies to meet the needs of the TNI's leading weaponry equipment to improve national defense