Understanding peace through the world news.
Ontology highlight
ABSTRACT: Supplementary information
The online version contains supplementary material available at 10.1140/epjds/s13688-022-00315-z.
SUBMITTER: Voukelatou V
PROVIDER: S-EPMC8777429 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:IntroductionNews media play an important role in raising public awareness, framing public opinions, affecting policy formulation, and acknowledgment of public health issues. Traditional qualitative content analysis for news sentiments and focuses are time-consuming and may not efficiently convey sentiments nor the focuses of news media.MethodsWe used descriptive statistics and state-of-art text mining to conduct sentiment analysis and topic modeling, to efficiently analyze over 3 million Reuters news articles during 2007-2017 for identifying their coverage, sentiments, and focuses for public health issues. Based on the top keywords from public health scientific journals, we identified 10 major public health issues (i.e., "air pollution," "alcohol drinking," "asthma," "depression," "diet," "exercise," "obesity," "pregnancy," "sexual behavior," and "smoking").ResultsThe news coverage for seven public health issues, "Smoking," "Exercise," "Alcohol drinking," "Diet," "Obesity," "Depression," and "Asthma" decreased over time. The news coverage for "Sexual behavior," "Pregnancy," and "Air pollution" fluctuated during 2007-2017. The sentiments of the news articles for three of the public health issues, "exercise," "alcohol drinking," and "diet" were predominately positive and associated such as "energy." Sentiments for the remaining seven public health issues were mainly negative, linked to negative terms, e.g., diseases. The results of topic modeling reflected the media's focus on public health issues.ConclusionsText mining methods may address the limitations of traditional qualitative approaches. Using big data to understand public health needs is a novel approach that could help clinical and translational science awards programs focus on community-engaged research efforts to address community priorities.
| S-EPMC8057471 | biostudies-literature
Project description:BackgroundDue to the COVID-19 pandemic, health information related to COVID-19 has spread across news media worldwide. Google is among the most used internet search engines, and the Google Trends tool can reflect how the public seeks COVID-19-related health information during the pandemic.ObjectiveThe aim of this study was to understand health communication through Google Trends and news coverage and to explore their relationship with prevention and control of COVID-19 at the early epidemic stage.MethodsTo achieve the study objectives, we analyzed the public's information-seeking behaviors on Google and news media coverage on COVID-19. We collected data on COVID-19 news coverage and Google search queries from eight countries (ie, the United States, the United Kingdom, Canada, Singapore, Ireland, Australia, South Africa, and New Zealand) between January 1 and April 29, 2020. We depicted the characteristics of the COVID-19 news coverage trends over time, as well as the search query trends for the topics of COVID-19-related "diseases," "treatments and medical resources," "symptoms and signs," and "public measures." The search query trends provided the relative search volume (RSV) as an indicator to represent the popularity of a specific search term in a specific geographic area over time. Also, time-lag correlation analysis was used to further explore the relationship between search terms trends and the number of new daily cases, as well as the relationship between search terms trends and news coverage.ResultsAcross all search trends in eight countries, almost all search peaks appeared between March and April 2020, and declined in April 2020. Regarding COVID-19-related "diseases," in most countries, the RSV of the term "coronavirus" increased earlier than that of "covid-19"; however, around April 2020, the search volume of the term "covid-19" surpassed that of "coronavirus." Regarding the topic "treatments and medical resources," the most and least searched terms were "mask" and "ventilator," respectively. Regarding the topic "symptoms and signs," "fever" and "cough" were the most searched terms. The RSV for the term "lockdown" was significantly higher than that for "social distancing" under the topic "public health measures." In addition, when combining search trends with news coverage, there were three main patterns: (1) the pattern for Singapore, (2) the pattern for the United States, and (3) the pattern for the other countries. In the time-lag correlation analysis between the RSV for the topic "treatments and medical resources" and the number of new daily cases, the RSV for all countries except Singapore was positively correlated with new daily cases, with a maximum correlation of 0.8 for the United States. In addition, in the time-lag correlation analysis between the overall RSV for the topic "diseases" and the number of daily news items, the overall RSV was positively correlated with the number of daily news items, the maximum correlation coefficient was more than 0.8, and the search behavior occurred 0 to 17 days earlier than the news coverage.ConclusionsOur findings revealed public interest in masks, disease control, and public measures, and revealed the potential value of Google Trends in the face of the emergence of new infectious diseases. Also, Google Trends combined with news media can achieve more efficient health communication. Therefore, both news media and Google Trends can contribute to the early prevention and control of epidemics.
| S-EPMC8691414 | biostudies-literature
Project description:The importance of hope in promoting conciliatory attitudes has been asserted in the field of conflict resolution. However, little is known about conditions inducing hope, especially in intractable conflicts, where reference to the outgroup may backfire. In the current research, five studies yielded convergent support for the hypothesis that hope for peace stems from a general perception of the world as changing. In Study 1, coders observed associations between belief in a changing world, hope regarding peace, and support for concessions. Study 2 revealed the hypothesized relations using self-reported measures. Studies 3 and 4 established causality by instilling a perception of the world as changing (vs. unchanging) using narrative and drawing manipulations. Study 5 compared the changing world message with a control condition during conflict escalation. Across studies, although the specific context was not referred to, the belief in a changing world increased support for concessions through hope for peace.
| S-EPMC4674745 | biostudies-literature
Project description:This study promotes the news repertoire framework as an analytical approach best suited for studying news engagement on social media (SM), considering its multifaceted nature. To demonstrate the theoretical benefits of this proposal, the study seeks to (1) identify user profiles based on SM news viewing and sharing, and news consumption on other platforms; (2) determine profile predictors; and (3) evaluate their possible outcomes. A panel study (N = 1786) demonstrated the emergence of identifiable profiles, attributed to differences in SM use and political interest. In addition, profiles embodied different effects on political participation over time. A second study (N = 86) was conducted thereafter, in which users' Facebook news feed use was analyzed to determine differences in news supply according to profiles. Findings that could not have been achieved using the more common unidimensional news consumption methods are discussed in light of new theoretical gains provided by the repertoire approach.
| S-EPMC9315192 | biostudies-literature
Project description:This article argues that an artificial superintelligence (ASI) emerging in a world where war is still normalised constitutes a catastrophic existential risk, either because the ASI might be employed by a nation-state to war for global domination, i.e., ASI-enabled warfare, or because the ASI wars on behalf of itself to establish global domination, i.e., ASI-directed warfare. Presently, few states declare war or even war on each other, in part due to the 1945 UN Charter, which states Member States should "refrain in their international relations from the threat or use of force", while allowing for UN Security Council-endorsed military measures and self-defense. As UN Member States no longer declare war on each other, instead, only 'international armed conflicts' occur. However, costly interstate conflicts, both hot and cold and tantamount to wars, still take place. Further, a New Cold War between AI superpowers looms. An ASI-directed/enabled future conflict could trigger total war, including nuclear conflict, and is therefore high risk. Via conforming instrumentalism, an international relations theory, we advocate risk reduction by optimising peace through a Universal Global Peace Treaty (UGPT), contributing towards the ending of existing wars and prevention of future wars, as well as a Cyberweapons and Artificial Intelligence Convention. This strategy could influence state actors, including those developing ASIs, or an agential ASI, particularly if it values conforming instrumentalism and peace.Supplementary informationThe online version contains supplementary material available at 10.1007/s00146-021-01382-y.
| S-EPMC8748529 | biostudies-literature
Project description:The data article presents a dataset and a tool for news-based monitoring of sustainable development goals defined by the United Nations. The presented dataset was created by structured queries of the GDELT database based on the categories of the World Bank taxonomy matched to sustainable development goals. The Google BigQuery SQL scripts and the results of the related network analysis are attached to the data to provide a toolset for the strategic management of sustainability issues. The article demonstrates the dataset on the 6th sustainable development goal (Clean Water and Sanitation). The network formed based on how countries appear in the same news can be used to explore the potential international cooperation. The network formed based on how topics of World Bank taxonomy appear in the same news can be used to explore how the problems and solutions of sustainability issues are interlinked.
| S-EPMC8047166 | biostudies-literature
Project description:CONTEXT: Prior research has faulted the US News and World Report hospital specialty rankings for excessive reliance on reputation, a subjective measure of a hospital's performance. OBJECTIVE: To determine whether and to what extent reputation correlates with objective measures of research productivity among cancer hospitals. DESIGN: A retrospective observational study. SETTING: Automated search of NIH Reporter, BioEntrez, BioMedline and Clinicaltrials.gov databases. PARTICIPANTS: The 50 highest ranked cancer hospitals in 2013's US News and World Report Rankings. EXPOSURE: We ascertained the number of NCI funded grants, and the cumulative funds received by each cancer center. Additionally, we identified the number of phase I, phase II, and phase III studies published and indexed in MEDLINE, and registered at clinicaltrials.gov. All counts were over the preceding 5 years. For published articles, we summed the impact factor of the journals in which they appeared. Trials were attributed to centers on the basis of the affiliation of the lead author or study principal investigator. MAIN OUTCOME: Correlation coefficients from simple and multiple linear regressions for measures of research productivity and a center's reputation. RESULTS: All measures of research productivity demonstrated robust correlation with reputation (mean r-squared ?=?0.65, median r-squared?=?0.68, minimum r-squared?=?.41, maximum r-squared?=?0.80). A multivariable model showed that 93% of the variation in reputation is explained by objective measures. CONCLUSION: Contrary to prior criticism, the majority of reputation, used in US News and World Rankings, can be explained by objective measures of research productivity among cancer hospitals.
| S-EPMC4172593 | biostudies-other
Project description:The rapid growth of technology has massively increased the amount of text data. The data can be mined and utilized for numerous natural language processing (NLP) tasks, particularly text classification. The core part of text classification is collecting the data for predicting a good model. This paper collects Kurdish News Dataset Headlines (KNDH) for text classification. The dataset consists of 50000 news headlines which are equally distributed among five classes, with 10000 headlines for each class (Social, Sport, Health, Economic, and Technology). The percentage ratio of getting the channels of headlines is distinct, while the numbers of samples are equal for each category. There are 34 distinct channels that are used to collect the different headlines for each class, such as 8 channels for economics, 14 channels for health, 18 channels for science, 15 channels for social, and 5 channels for sport. The dataset is preprocessed using the Kurdish Language Processing Toolkit (KLPT) for tokenizing, spell-checking, stemming, and preprocessing.
| S-EPMC10147969 | biostudies-literature
Project description:This study aims to bring about a novel approach to the analysis of Sustainable Development Goals (SDGs) based solely on the appearance of news. Our purpose is to provide a monitoring tool that enables world news to be detected in an SDG-oriented manner, by considering multilingual as well as wide geographic coverage. The association of the goals with news basis the World Bank Group Topical Taxonomy, from which the selection of search words approximates the 17 development goals. News is extracted from The GDELT Project (Global Database of Events, Language and Tone) which gathers both printed as well as online news from around the world. 60 851 572 relevant news stories were identified in 2019. The intertwining of world news with SDGs as well as connections between countries are interpreted and highlight that even in the most SDG-sensitive countries, only 2.5% of the news can be attributed to the goals. Most of the news about sustainability appears in Africa as well as East and Southeast Asia, moreover typically the most negative tone of news can be observed in Africa. In the case of climate change (SDG 13), the United States plays a key role in both the share of news and the negative tone. Using the tools of network science, it can be verified that SDGs can be characterized on the basis of world news. This news-centred network analysis of SDGs identifies global partnerships as well as national stages of implementation towards a sustainable socio-environmental ecosystem. In the field of sustainability, it is vital to form the attitudes and environmental awareness of people, which strategic plans cannot address but can be measured well through the news.
| S-EPMC7868610 | biostudies-literature
Project description:Amid the flood of fake news on Coronavirus disease of 2019 (COVID-19), now referred to as COVID-19 infodemic, it is critical to understand the nature and characteristics of COVID-19 infodemic since it not only results in altered individual perception and behavior shift such as irrational preventative actions but also presents imminent threat to the public safety and health. In this study, we build on First Amendment theory, integrate text and network analytics and deploy a three-pronged approach to develop a deeper understanding of COVID-19 infodemic. The first prong uses Latent Direchlet Allocation (LDA) to identify topics and key themes that emerge in COVID-19 fake and real news. The second prong compares and contrasts different emotions in fake and real news. The third prong uses network analytics to understand various network-oriented characteristics embedded in the COVID-19 real and fake news such as page rank algorithms, betweenness centrality, eccentricity and closeness centrality. This study carries important implications for building next generation trustworthy technology by providing strong guidance for the design and development of fake news detection and recommendation systems for coping with COVID-19 infodemic. Additionally, based on our findings, we provide actionable system focused guidelines for dealing with immediate and long-term threats from COVID-19 infodemic.
| S-EPMC8627595 | biostudies-literature