Piece Of News Research Articles

The Stanford Global Health Media Fellowship: Training the Next Generation of Physician Communicators to Fight Health Misinformation.

ProblemThe COVID-19 pandemic and the spread of related health misinformation, especially on social media, have highlighted the need for more health care professionals to produce and share accurate health information to improve health and health literacy. Yet, few programs address this problem by training health care professionals in the art of science writing and medical journalism.ApproachCreated in 2011, the Stanford Global Health Media Fellowship aims to train medical students and residents in public communication strategies. Each year, 1 physician-in-training is selected to complete the fellowship, which includes 3 rotations: (1) 1 academic quarter at Stanford’s Graduate Program in Journalism, (2) 3 to 5 months with a national news network (previously NBC and ABC, now CNN), and (3) a placement at an international site. During the year-long program, fellows also complete a capstone project tackling a global health equity issue.OutcomesSince 2011, 10 fellows have completed the program, and they have acquired skills in reporting, writing, multimedia, social media, and medical communications. During the news network rotation, they have completed more than 200 medical news pieces and improved the quality of the health information in a myriad of other pieces. Alumni have continued to write and report on medical stories throughout residency, other fellowships, and as practicing physicians. One alumnus is now a medical news producer at CNN.Next StepsExpanding high-quality training in medical journalism for physicians through partnerships with journalism schools; communications departments; and local, national, and international journalists can greatly improve physicians’ ability to communicate with the public. It also has the potential to greatly improve the health information the public receives. Educators should consider embedding mass health communications training in medical education curricula and increasing opportunities for physicians to engage with diverse public audiences.

Robust Sentimental Class Prediction Based on Cryptocurrency-Related Tweets Using Tetrad of Feature Selection Techniques in Combination with Filtered Classifier

Individual mental feelings and reactions are getting more significant as they help researchers, domain experts, businesses, companies, and other individuals understand the overall response of every individual in specific situations or circumstances. Every pure and compound sentiment can be classified using a dataset, which can be in the form of Twitter text by various Twitter users. Twitter is one of the vital platforms for individuals to participate and share their ideas about different topics; it is also considered to be one of the most famous and the biggest website for micro-blogging on the Internet. One of the key purposes of this study is to classify pure and compound sentiments based on text related to cryptocurrencies, an innovative way of trading and flourishing daily. The cryptocurrency market incurs many fluctuations in the coins’ value. A small positive or negative piece of news can sensate the whole scenario about the specific cryptocurrencies. In this paper, individuals’ pure and compound sentiments based on cryptocurrency-related Twitter text are classified. The dataset is collected through the Twitter API. In WEKA, the two deployment schemes are compared; firstly, straight with single feature selection technique (Tweet to lexicon feature vector), and secondly, a tetrad of feature selection techniques (Tweet to lexicon feature vector, Tweet to input lexicon feature vector, Tweet to SentiStrength feature vector, and Tweet to embedding feature vector) are used to purify the data LibLINEAR (LL) classifier, which contains fast algorithms for linear classification using L2-regularization L2-loss support vector machines (Dual SVM). The LL classifier differs in that it can potentially alleviate the sum of the absolute values of errors rather than the sum of the squared errors and is typically much speedier. Based on the overall performance parameters, the deployment scheme containing the tetrad of feature selection techniques with the LL classifier is considered the best choice for the purpose of classification. Among machine learning techniques, LL produces effective results and gives an efficient performance compared to other prevailing techniques. The findings of this research would be beneficial for Twitter users as well as cryptocurrency traders.

The Relevance of Discursive Strategies to Information Evaluation Practices

Recent work across disciplines has examined the current post-truth climate and various types of information disorders which have permeated the internet. Scholars have made significant progress in defining and theorizing information literacy and its various aspects, as well as in designing programs to help students acquire the relevant skills for evaluating information. Nevertheless, further exploration is needed, for example to understand the roles of criteria in information evaluation. The present study draws on scholarship in discourse and rhetoric studies to suggest how discursive strategies, a key concept in these convergent areas, can inform approaches to information evaluation. To illustrate this improved approach, this study explores the case of a recent piece of fake news that involves both text and image and has circulated widely as a digital flyer on social media.

Is it possible to introduce an interview to the Korean Medical Licensing Examination to assess professional attributes?: a survey-based observational study

PurposeThis study aimed to gather opinions from medical educators on the possibility of introducing an interview to the Korean Medical Licensing Examination (KMLE) to assess professional attributes. Specifically following topics were dealt with: the appropriate timing and tool to assess unprofessional conduct; the possiblity of prevention of unprofessional conduct by introducing an interview to the KMLE; and the possibility of implementation of an interview to the KMLE.MethodsA cross-sectional study approach based on a survey questionnaire was adopted. We analyzed 104 pieces of news about doctors’ unprofessional conduct to determine the deficient professional attributes. We derived 24 items of unprofessional conduct and developed the questionnaire and surveyed 250 members of the Korean Society of Medical Education 2 times. Descriptive statistics, cross-tabulation analysis, and Fisher’s exact test were applied to the responses. The answers to the open-ended questions were analyzed using conventional content analysis.ResultsIn the survey, 49 members (19.6%) responded. Out of 49, 24 (49.5%) responded in the 2nd survey. To assess unprofessional conduct, there was no dominant timing among basic medical education (BME), KMLE, and continuing professional development (CPD). There was no overwhelming assessment tool among written examination, objective structured clinical examination, practice observation, and interview. Response rates of “impossible” (49.0%) and “possible” (42.9%) suggested an interview of the KMLE prevented unprofessional conduct. In terms of implementation, “impossible” (50.0%) was selected more often than “possible” (33.3%).ConclusionProfessional attributes should be assessed by various tools over the period from BME to CPD. Hence, it may be impossible to introduce an interview to assess professional attributes to the KMLE, and a system is needed such as self-regulation by the professional body rather than licensing examination.

War-torn Afghanistan and cancer care: where to focus?

We read with great interest the news piece in The Lancet Oncology about the risks faced by cancer treatment facilities during the crisis in Ukraine. 1 Burki TK Consequences of the crisis in Ukraine on cancer care. Lancet Oncol. 2022; (published online March 3.)https://doi.org/10.1016/S1470-2045(22)00130-9 Summary Full Text Full Text PDF Scopus (0) Google Scholar In this Comment, we would like to draw attention towards Afghanistan, which has been a hotspot for military conflicts for four decades. The resultant political turmoil has had a deleterious impact on the health-care sector, and led to an ongoing humanitarian crisis. Afghanistan's health-care system is on the verge of collapse—95% of families are suffering from acute food insecurity and a severe scarcity of essential health facilities, medications, and vaccinations. 2 Rasa MS 95% of Afghanistan's population faces acute hunger: WFP report. https://8am.af/eng/95-of-afghanistans-population-faces-acute-hunger-wfp-report/Date: 2022 Date accessed: March 1, 2022 Google Scholar Between January and July, 2021, about 26 health facilities were damaged and 31 health-care employees injured during a peak of political unrest, which included the death of 12 health personnel. 3 ReliefWebStatement on Afghanistan by Dr Ahmed Al-Mandhari, WHO Regional Director for the Eastern Mediterranean. https://reliefweb.int/report/afghanistan/statement-afghanistan-dr-ahmed-al-mandhari-who-regional-director-easternDate: 2021 Date accessed: March 4, 2022 Google Scholar

Women’s News Coverage in Local Mass Media: A Case of Regional Head Election 2018

The mass media can play a crucial role in election campaigns because it can influence people's points of view of a candidate, including how they responded to women candidates. This paper aims to analyze how the local media portrayed women candidates in the Local Executive Election (Pilkada) 2018 and the factors that drive it. Unlike most previous studies, which focused on women in legislative candidacy and analyzed the national mass media, this study focuses on women's candidacy in the local executive election by observing the local mass media. The author believes that the differences in the electoral system between the legislative election and the local executive one and the differences of the media scop will produce different findings. Using the explanatory sequential mixed method, the author combined the quantitative method followed up with the qualitative one to interpret this study's data. The author took a sample of 140 pieces of news from local mass media during March-23 June 2018, which was chosen by a non-probability sampling method with a quota technique. This study did not reveal any biased coverage toward women candidates due to four factors: the type of election that women participate in; the social-political capital of women candidates; the condition that women's active political participation is not a novelty; and the alignment of media to the more extensive political agenda. Therefore, it can be concluded that the neutrality of the media does not necessarily cause unbiased coverage, yet by the logic of the media, which makes the media are not passive conduits.

Sentiment Analysis of Financial news

Sentiment Analysis deals with the computational treatment of opinions of expressed in written handbooks. The addition of the formerly mature semantic technologies to the field has proven to increase the results delicacy. In this a semantically- enhanced methodology for the reflection of sentiment opposition in fiscal news is presented. The term" Sentiment Analysis" was first defined in 2003 by Nasukawa and Yi as “ determining the subjectivity opposition ( positive or negative) and opposition strength ( explosively positive, mildly positive, weakly positiveetc.) of a given review textbook; in other words- determining the opinion of the pen.” Turney’s pioneering work on Sentiment Analysis applied an unsupervised approach to classify review data into positive class and negative class. The sum aggregate of information entered by the investors is reflected through the stock price of the enterprises. Through this process, information is converted from a textual form to a numerical form. This process of conversion is veritably useful, because it allows information to be fluently epitomized and enables us to compare the sentiments of news with the request returns. There may be variations about the exact meaning of a piece of news, but there can not be any variation about request returns. The fiscal news that makes a positive impact on the stock request returns is good and the bone that makes a negative impact on stock request returns is bad. In comparison to the work done in sentiment bracket applied to the review sphere or product reviews, veritably little work has been done in the field of operation of these ways in the fiscal sphere using unsupervised approach. This paper tries to address this exploration gap. The overall purpose of the study is to propose a semantic exposure grounded unsupervised approach for chancing sentiments strength of fiscal textbook.

Identifying Frames of the COVID-19 Infodemic: Thematic Analysis of Misinformation Stories Across Media.

The word "infodemic" refers to the deluge of false information about an event, and it is a global challenge for today's society. The sheer volume of misinformation circulating during the COVID-19 pandemic has been harmful to people around the world. Therefore, it is important to study different aspects of misinformation related to the pandemic. This paper aimed to identify the main subthemes related to COVID-19 misinformation on various platforms, from traditional outlets to social media. This paper aimed to place these subthemes into categories, track the changes, and explore patterns in prevalence, over time, across different platforms and contexts. From a theoretical perspective, this research was rooted in framing theory; it also employed thematic analysis to identify the main themes and subthemes related to COVID-19 misinformation. The data were collected from 8 fact-checking websites that formed a sample of 127 pieces of false COVID-19 news published from January 1, 2020 to March 30, 2020. The findings revealed 4 main themes (attribution, impact, protection and solutions, and politics) and 19 unique subthemes within those themes related to COVID-19 misinformation. Governmental and political organizations (institutional level) and administrators and politicians (individual level) were the 2 most frequent subthemes, followed by origination and source, home remedies, fake statistics, treatments, drugs, and pseudoscience, among others. Results indicate that the prevalence of misinformation subthemes had altered over time between January 2020 and March 2020. For instance, false stories about the origin and source of the virus were frequent initially (January). Misinformation regarding home remedies became a prominent subtheme in the middle (February), while false information related to government organizations and politicians became popular later (March). Although conspiracy theory web pages and social media outlets were the primary sources of misinformation, surprisingly, results revealed trusted platforms such as official government outlets and news organizations were also avenues for creating COVID-19 misinformation. The identified themes in this study reflect some of the information attitudes and behaviors, such as denial, uncertainty, consequences, and solution-seeking, that provided rich information grounds to create different types of misinformation during the COVID-19 pandemic. Some themes also indicate that the application of effective communication strategies and the creation of timely content were used to persuade human minds with false stories in different phases of the crisis. The findings of this study can be beneficial for communication officers, information professionals, and policy makers to combat misinformation in future global health crises or related events.

Ecocollapse Fiction and Cultures of Human Extinction. By Sarah E. McFarland

The Guardian just published the first good piece of news on climate change I’ve read in years. We haven’t maintained the decline in global emissions from early 2020 or passed a Green New Deal. So, what’s the good news? Six out of ten Americans are finally “alarmed or concerned” about climate change. Reading anything these days, whether it is the news or a new novel, may feel unbearable not only because we’re facing multiple social and ecological crises, but also because we’re faced with our own resistance to human extinction. Sarah E. McFarland’s Ecocollapse Fiction and Cultures of Human Extinction makes the necessary move of addressing this reticence (if not refusal) in writers and readers as another form of human exceptionalism. Climate fiction, she argues, blinkers us with the “traditional generic conventions that display a predilection for happy endings by imagining primitivist communities of human survivors with the means of...

History of Music – A Further Approach

Abstract This essay emerged from an article in the press this year, regarding the ‘infamous’ decision of Oxford University to ‘give up teaching classical music in the name of political correctness’! My first thought was to take this journalistic excess seriously. However, knowing the prestige of this famous university, I wanted to know the real facts that caused this piece of news… and I soon found out the true data. Firstly: It is not – it cannot be! – about the elimination of classical music from the current academic and artistic activity. It is about the globalisation of musicologists’ interest and efforts toward the contemporary musical phenomenon. Secondly: The project called ‘Towards a Global History of Music’ was indeed initiated by the University of Oxford, but it was adopted and carried out by five other European universities, along with several internationally renowned musicologists outside the academic sphere. Thirdly: The project took place between 2013-2017, and in the years that followed, the main coordinator, Professor Reinhard Strohm, edited and published three volumes of studies on music from all over the world, in the past and nowadays, signed by researchers of the most diverse ages and backgrounds. Fourthly: They admit that the idea about a global musical history is not new - it goes back to more than two centuries ago, to the time of the Enlightenment of the 18th century. Fifth: What the historians, musicologists, ethnomusicologists, sociologists in question firmly and constructively assert is the correlation of the data provided by the observations and findings on the musical phenomenon of humanity. They thus insist on overcoming Eurocentric conceptions, in other words, approaching the musical phenomenon from anywhere in the world, without automatically relating it to models or units of measurement exclusively generated by European values or history. Moreover, a comparison between various musical phenomena in the world can help to explain and understand some realities, circumstances and, consequently, the elimination of some prejudices.

The framing of news reports on the Catalonian referendum in two leading British newspapers

Even though the independence referendum held in 2017 in Catalonia was unsuccessful, the large role of the media together with easy, fast international broadcasting and the fear of a possible mimic effect in other regions made the entire world observe and discuss the event. The purpose of this article is to analyse the media coverage of the referendum in two benchmark British newspapers, The Guardian and The Telegraph. Based on hypotheses that the news coverage regarding the Catalonian referendum might be prone to the dissemination of information according to the editorial position of the newspapers, this research has analysed 188 news pieces by using framing analysis. The first hypothesis, that both newspapers adapted their versions of the story to readers according to the predisposition of the different editorial trends of each newspaper, was not confirmed. The results allow us to conclude that in the news of the benchmark British press regarding the illegal referendum in Catalonia, fair journalistic coverage prevailed.

Role of Media in Strengthening Pakistan’s Image with Respect to Security

Purpose: Because national security is indeed a delicate subject in Pakistan, it is expected from the press to play a beneficial role in this respect. This study assessed the role of media in strengthening Pakistan’s image with respect to security.
 Design/Methodology/Approach
 The study is qualitative in nature, the researchers utilized survey method by employing close ended questionnaire as data collection tool. SPSS has been used for data analysis. Statistical analysis has been done using chi-square test.
 Findings: As per the findings of the study, the participants were found to have felt unsafe in Pakistan after hearing a piece of particular news, but they do think Pakistan is a safe country.
 Implications/Originality/Value: Media independence is a wonderful thing in a functioning democracy, but when it comes to sensitive topics like "national security", it is assumed that the media must only stick to their job of informing instead of dictating the processes.

Description of the Distribution Law and Non-Linear Dynamics of Growth of Comments Number in News and Blogs Based on the Fokker-Planck Equation

The article considers stationary and dynamic distributions of news by the number of comments. The processing of the observed data showed that static distribution of news by the number of comments relating to that news obeys a power law, and the dynamic distribution (the change in number of comments over time) in some cases has an S-shaped character, and in some cases a more complex two-stage character. This depends on the time interval between the appearance of a comment at the first level and a comment attached to that comment. The power law for the stationary probability density of news distribution by the number of comments can be obtained from the solution of the stationary Fokker-Planck equation, if a number of assumptions are made in its derivation. In particular, we assume that the drift coefficient μ(x) responsible in the Fokker-Planck equation for a purposeful change in the state of system x (x is the current number of comments on that piece of news) linearly depends on the state x, and the diffusion coefficient D(x) responsible for a random change depends quadratically on x. The solution of the unsteady Fokker-Planck differential equation with these assumptions made it possible to obtain an analytical equation for the probability density of transitions between the states of the system per unit of time, which is in good agreement with the observed data, considering the effect of the delay time between the appearance of the first-level comment and the comment on that comment.

Pragmatic mechanisms of manipulation in Russian online media: How clickbait works (or does not)

Our study investigates clickbait – ambiguous misleading headlines, aimed at exploiting readers’ curiosity gap. Clickbait has two unequally conspicuous interpretations, where the first interpretation is false with respect to the article content, while the second interpretation is correct content-wise, but considerably less obvious. We aim at identifying linguistic structures and pragmatic mechanisms employed in creating Russian clickbait, as well as testing the effectiveness of clickbait headlines experimentally. To answer our research questions, we compiled, annotated and analyzed a corpus of Russian clickbait headlines, as well as designed and ran an online experiment. We demonstrate that the main device employed in creating clickbait is a false generalized conversational implicature (GCI), created by flouting Gricean maxims of Quantity, Manner, or Relevance, which is subsequently canceled by the content of the article. We identify language-specific contexts conducive to their occurrence, and show how journalists explore semantic, syntactic, and referential peculiarities of the Russian language to create GCIs inherent in clickbait. Finally, we demonstrate that not all clickbait headlines are effective: in order to attract clicks, clickbait must not be obviously false and must increase the potential appeal and importance of insufficiently engaging news pieces on topics that do not require specialized knowledge.

Widening the North/South Divide? Representations of the role of the EU during the Covid-19 crisis in Spanish media

Abstract In this article we study the discursive construction of the EU managerial role in the early stages of the Covid-19 pandemic in four Spanish newspapers: two published in mainland Spain – El Mundo and El País – and two published in Catalonia – La Vanguardia and ARA. By doing a qualitative study of newspapers, this article aims to identify which discourse strategies are used when informing about the actions and decisions taken in European political and economic fora. The analysis identifies the three main generic frames which are used in news pieces: morality (mostly as a call for solidarity), economic (mostly as preventing possible harm), and conflict (focused on divide(s) within (EU)rope). The activation of these frames in the news pieces contribute to an implicit legitimation of the existence of (EU)rope as based on two core values – solidarity and cooperation – together with a delegitimation of the actions performed by some European institutions.

Online Rumor Diffusion Model Based on Variation and Silence Phenomenon in the Context of COVID-19.

In the era of mobile internet, information dissemination has made a new leap in speed and in breadth. With the outbreak of the coronavirus disease 2019 (COVID-19), the COVID-19 rumor diffusion that is not limited by time and by space often becomes extremely complex and fickle. It is also normal that a piece of unsubstantiated news about COVID-19 could develop to many versions. We focus on the stagnant role and information variants in the process of rumor diffusion about COVID-19, and through the study of variability and silence in the dissemination, which combines the effects of stagnation phenomenon and information variation on the whole communication system in the circulation of rumors about COVID-19, based on the classic rumor SIR (Susceptible Infected Recovered) model, we introduce a new concept of “variation” and “oyster”. The stability of the new model is analyzed by the mean field equation, and the threshold of COVID-19 rumor propagation is obtained later. According to the results of the simulation experiment, whether in the small world network or in the scale-free network, the increase of the immure and the silent probability of the variation can effectively reduce the speed of rumor diffusion about COVID-19 and is conducive to the dissemination of the truth in the whole population. Studies have also shown that increasing the silence rate of variation can reduce COVID-19 rumor transmission more quickly than the immunization rate. The interesting discovery is that at the same time, a higher rumor infection rate can bring more rumors about COVID-19 but does not always maintain a high number of the variation which could reduce variant tendency of rumors. The more information diffuses in the social group, the more consistent the version and content of the information will be, which proves that the more adequate each individual information is, the slower and less likely rumors about COVID-19 spread. This consequence tells us that the government needs to guide the public to the truth. Announcing the true information publicly could instantly contain the COVID-19 rumor diffusion well rather than making them hidden or voiceless.

The Role of Information in Classical and Modern Paradigms

Information is a key concept of our time. We know that a piece of news can change or transform our thoughts, our emotions, and our actions in both individual and social respects. The emerging concept of information is broader than its traditional usage. Unlike artificial systems, living systems are affected by the information they receive. This study outlines the concept of information as it appears in integrated conceptions of the natural and human world: in so-called “paradigms,” classical as well as modern.

Memory-Guided Multi-View Multi-Domain Fake News Detection

The wide spread of fake news is increasingly threatening both individuals and society. Great efforts have been made for automatic fake news detection on a <i>single</i> domain (e.g., politics). However, correlations exist commonly across multiple news domains, and thus it is promising to simultaneously detect fake news of <i>multiple</i> domains. Based on our analysis, we pose two challenges in multi-domain fake news detection: 1) <bold/><i>domain shift</i><bold/>, caused by the discrepancy among domains in terms of words, emotions, styles, etc. 2) <bold/><i>domain labeling incompleteness</i><bold/>, stemming from the real-world categorization that only outputs one single domain label, regardless of topic diversity of a news piece. In this paper, we propose a Memory-guided Multi-view Multi-domain Fake News Detection Framework (M <inline-formula><tex-math notation="LaTeX">$^{3}$</tex-math></inline-formula> FEND) to address these two challenges. We model news pieces from a multi-view perspective, including semantics, emotion, and style. Specifically, we propose a Domain Memory Bank to enrich domain information which could discover potential domain labels based on seen news pieces and model domain characteristics. Then, with enriched domain information as input, a Domain Adapter could adaptively aggregate discriminative information from multiple views for news in various domains. Extensive offline experiments on English and Chinese datasets demonstrate the effectiveness of M <inline-formula><tex-math notation="LaTeX">$^{3}$</tex-math></inline-formula> FEND, and online tests verify its superiority in practice. Our code is available at <uri>https://github.com/ICTMCG/M3FEND</uri>.

«Ирландская сага»: в поисках дефиниции объекта

Using the term saga in Russian and European criticism is studied. The term denotes Old Irish epic tales. The relation between oral and written narrative traditions is described. Under investigation is the semantic content of the Russian term with the following: 1. the English (saga) and the German (die Sage) scholarly texts describing the same denotates 2. the Icelandic notion saga having a much wider semantic field in the original tradition (though not in mediaeval studies) 3. the semantic field of the original term scél having tale or story as one of its meanings. The work also states the recursive semantic shift tale, story → an event worthy of making a tale of, a piece of news. The shift is also evident in the semantic evolution of the Russian term istoriya. The conclusion points out the relativity of the frame of the term saga as a mediaeval literature’s genre and the necessity to appeal to a scholar’s intuition.

Fake News in Social Networks

We model the spread of news as a social learning game on a network. Agents can either endorse or oppose a claim made in a piece of news, which itself may be either true or false. Agents base their decision on a private signal and their neighbors' past actions. Given these inputs, agents follow strategies derived via multi-agent deep reinforcement learning and receive utility from acting in accordance with the veracity of claims. Our framework yields strategies with agent utility close to a theoretical, Bayes optimal benchmark, while remaining flexible to model re-specification. Optimized strategies allow agents to correctly identify most false claims, when all agents receive unbiased private signals. However, an adversary's attempt to spread fake news by targeting a subset of agents with a biased private signal can be successful. Even more so when the adversary has information about agents' network position or private signal. When agents are aware of the presence of an adversary they re-optimize their strategies in the training stage and the adversary's attack is less effective. Hence, exposing agents to the possibility of fake news can be an effective way to curtail the spread of fake news in social networks. Our results also highlight that information about the users' private beliefs and their social network structure can be extremely valuable to adversaries and should be well protected.