News Trends Research Articles

The present in retrospect: Press reporting of UK General Elections, 1918–2015

This article provides a unique content analysis of 100 years of national press coverage of UK General Elections and tests four claims about historical trends in election news reporting in democratic systems: (1) that coverage is becoming more focussed on political leaders at the expense of other political sources; (2) that reporting of the personalities and personal lives of politicians has expanded; (3) that editorial treatment of politicians has become increasingly negative and (4) that news coverage is increasingly obsessed with the conduct of politics rather than its substantive content. Through the detail of this analysis, we identify areas of historical continuity as well as change and challenge overly neat periodisations and simple histories of election news reporting.

A review of mobile robots: Concepts, methods, theoretical framework, and applications

Humanoid robots, unmanned rovers, entertainment pets, drones, and so on are great examples of mobile robots. They can be distinguished from other robots by their ability to move autonomously, with enough intelligence to react and make decisions based on the perception they receive from the environment. Mobile robots must have some source of input data, some way of decoding that input, and a way of taking actions (including its own motion) to respond to a changing world. The need to sense and adapt to an unknown environment requires a powerful cognition system. Nowadays, there are mobile robots that can walk, run, jump, and so on like their biological counterparts. Several fields of robotics have arisen, such as wheeled mobile robots, legged robots, flying robots, robot vision, artificial intelligence, and so on, which involve different technological areas such as mechanics, electronics, and computer science. In this article, the world of mobile robots is explored including the new trends. These new trends are led by artificial intelligence, autonomous driving, network communication, cooperative work, nanorobotics, friendly human–robot interfaces, safe human–robot interaction, and emotion expression and perception. Furthermore, these news trends are applied to different fields such as medicine, health care, sports, ergonomics, industry, distribution of goods, and service robotics. These tendencies will keep going their evolution in the coming years.

An Analysis of News Trends for Libraries in Korea: Based on 1990~2018 News Big Data

An Analysis of News Trends for Libraries in Korea: Based on 1990~2018 News Big Data

Resources aren’t everything, but they do help: assessing local TV health news to deliver substantive and useful health information

ABSTRACT Background This study explores how different station characteristics, especially organizational resources, influence local health news reporting. While some studies have identified general trends in nationwide local health news, no research has closely examined the impact of organizational gatekeeping factors of health news coverage by comparing two local television stations in the same market. Method Researchers used a comparative content analysis to evaluate local TV health news stories (N = 416) from two local television stations from the same market. Informed by gatekeeping theory, several characteristics of health news stories from stations with different organizational resources were analyzed including: length of coverage, location and quantity of stories, health topics, and target health population. Results A series of chi-square analyses indicate that there is a direct correlation between a station’s organizational resources and the length (Cramer’s V = .517), location (V = .369), health topics (V = .410), number, and quality of news sources (V = .424), target health population (V = .173), use of interviews (V = .685), and presence of conflict (V = .262) in local TV health newscasts. Conclusion Organizational resources (e.g. station budget) appear to be strongly related to the two stations’ health news coverage. The station with greater organizational resources provided more developed and localized content with longer, interview-based, conflict-driven, and targeted information geared toward to the public. For health communication researchers, information providers, and health policy-makers, the findings can help enhance their ability to better customize the planning and placement of their local health communication campaigns and outreach efforts.

Analyzing the impact of news trends on research publications and scientific collaboration networks

SummaryScientific collaboration plays a vital role in generating novel ideas and innovative research progress among the researchers. Similarly, news diffusion also has an important role among the research communities. Though the collaboration networks have made an impact in scientific activities and attracted the attention of scientific communities, no work so far analyzed the cause which can determine the future research publications. The objective of this paper is to study influence of news trends on scientific collaboration and research publications. For this purpose, we have collected the top technological news trends and applied the LDA model to identify top research keywords from the articles. The results show that the news trends play a significant role on scientific collaborations and innovative research progress. It is found that the researchers identify their research gap, make future collaborations and does interdisciplinary research. Our results highlight the important role of diffusion of news, which influence the young researchers to generate novel ideas and tend to collaborate more with different scientific communities.

News coverage, digital activism, and geographical saliency: A case study of refugee camps and volunteered geographical information.

The last several decades have witnessed a shift in the way in which news is delivered and consumed by users. With the growth and advancements in mobile technologies, the Internet, and Web 2.0 technologies users are not only consumers of news, but also producers of online content. This has resulted in a novel and highly participatory cyber-physical news awareness ecosystem that fosters digital activism, in which volunteers contribute content to online communities. While studies have examined the various components of this news awareness ecosystem, little is still known about how news media coverage (and in particular digital media) impacts digital activism. In order to address this challenge and develop a greater understanding of it, this paper focuses on a specific form of digital activism, that of the production of digital geographical content through crowdsourcing efforts. Using refugee camps from around the world as a case study, we examine the relationship between news coverage (via Google news), search trends (via Google trends) and user edit contribution patterns in OpenStreetMap, a prominent geospatial data crowdsourcing platform. In addition, we compare and contrast these patterns with user edit patterns in Wikipedia, a well-known non-geospatial crowdsourcing platform. Using Google news and Google trends to derive a measure of thematic public awareness, our findings indicate that digital activism bursts tend to take place during periods of sustained build-up of public awareness deficit or surplus. These findings are in line with two prominent mass communication theories: agenda setting and corrective action, and suggest the emergence of a novel stimulus-awareness-activism framework in today’s participatory digital age. Moreover, these findings further complement existing research examining the motivational factors that drive users to contribute to online collaborative communities. This paper brings us one step closer to understanding the underlying mechanisms that drive digital activism in particular in the geospatial domain.

News Trends on Women's Issues in the Independent Iraqi Press ((News in Al - Zaman newspaper)) model

News Trends on Women's Issues in the Independent Iraqi Press ((News in Al - Zaman newspaper)) model

Trend Analysis for Online Comments

To know the trend of a specific news related to school, the staff firstly tend to search for the comments related to the news, then read and analyze all the comments to find the characteristics of comments related to educational news. Secondly, they will review all the comments to shape the topics and categorized all the comments into the above topics. However, there are two problems exists currently. First of all, current social media platform cannot automatically analyze the trend of comments related to specific school news. Second, staff needs to waste a lot of time reading and judging the topics of comments related to a specific news so as to get the trend of a specific school news. To solve the above problem, we proposed a preparation stage to figure out the characteristics of comments related to educational news, the principles of generating topics related to comments and the principles of judging the topics of comments. After that, we proposed a Trend Analysis of Comment Topics Methodology, it includes four stages, which are collecting comment characteristics, judging comment topics, judging the topic of each comment, analyzing comment trend. This methodology we proposed can assist user to get the trend of specific news related to school efficiently and accurately.

Search engines, news wires and digital epidemiology: Presumptions and facts

BackgroundDigital epidemiology tries to identify diseases dynamics and spread behaviors using digital traces collected via search engines logs and social media posts. However, the impacts of news on information-seeking behaviors have been remained unknown. MethodsData employed in this research provided from two sources, (1) Parsijoo search engine query logs of 48 months, and (2) a set of documents of 28 months of Parsijoo’s news service. Two classes of topics, i.e. macro-topics and micro-topics were selected to be tracked in query logs and news. Keywords of the macro-topics were automatically generated using web provided resources and exceeded 10k. Keyword set of micro-topics were limited to a numerable list including terms related to diseases and health-related activities. The tests are established in the form of three studies. Study A includes temporal analyses of 7 macro-topics in query logs. Study B considers analyzing seasonality of searching patterns of 9 micro-topics, and Study C assesses the impact of news media coverage on users’ health-related information-seeking behaviors. ResultsStudy A showed that the hourly distribution of various macro-topics followed the changes in social activity level. Conversely, the interestingness of macro-topics did not follow the regulation of topic distributions. Among macro-topics, “Pharmacotherapy” has highest interestingness level and wider time-window of popularity. In Study B, seasonality of a limited number of diseases and health-related activities were analyzed. Trends of infectious diseases, such as flu, mumps and chicken pox were seasonal. Due to seasonality of most of diseases covered in national vaccination plans, the trend belonging to “Immunization and Vaccination” was seasonal, as well. Cancer awareness events caused peaks in search trends of “Cancer” and “Screening” micro-topics in specific days of each year that mimic repeated patterns which may mistakenly be identified as seasonality. In study C, we assessed the co-integration and correlation between news and query trends. Our results demonstrated that micro-topics sparsely covered in news media had lowest level of impressiveness and, subsequently, the lowest impact on users’ intents. ConclusionOur results can reveal public reaction to social events, diseases and prevention procedures. Furthermore, we found that news trends are co-integrated with search queries and are able to reveal health-related events; however, they cannot be used interchangeably. It is recommended that the user-generated contents and news documents are analyzed mutually and interactively.

Back to Reality: The Complex Relationship Between Patterns in Immigration News Coverage and Real-World Developments in Dutch and Flemish Newspapers (1999–2015)

Although prior studies investigating immigration news typically documented a dominant focus on negativity and threats, only limited empirical research is available, which scrutinizes the way real-world developments affect these patterns in immigration news. This study aims to fill this void. First, we report results of a large-scale and longitudinal content analysis (N = 4,340,757) of trends in immigration news coverage in two Western European cases, Flanders (the northern, Dutch-speaking, largest region of Belgium) and the Netherlands, from 1999 to 2015. Both the salience of immigration as a news topic on itself and its linkages with three prominent issues (i.e., crime, terrorism, and socioeconomic issues) are explored. Second, this study builds on previous insights by comparing dynamics in immigration news to real-world events and developments. Overall, the results show that the linkage of immigration to issues of crime, terrorism, and the economy in Flemish and Dutch newspapers was considerable throughout the 17-year period under study. Yet there is limited evidence for a close relationship between news and real-life developments; hence, trends in immigration news seem largely unaffected by trends in society.

News Coverage, Digital Activism, and Geographical Saliency: A Case Study of Refugee Camps and Volunteered Geographical Information

The last several decades have witnessed a shift in the way in which news is delivered and consumed by users. With the growth and advancements in mobile technologies, the Internet, and Web 2.0 technologies users are not only consumers of news, but also producers of online content. This has resulted in a novel and highly participatory cyber-physical news awareness ecosystem that fosters digital activism, in which volunteers contribute content to online communities. While studies have examined the various components of this news awareness ecosystem, little is still known about how news media coverage (and in particular digital media) impacts digital activism. In order to address this challenge and develop a greater understanding of it, this paper focuses on a specific form of digital activism, that of the production of digital geographical content through crowdsourcing efforts. Using refugee camps from around the world as a case study, we examine the relationship between news coverage (via Google news), search trends (via Google trends) and user edit contribution patterns in OpenStreetMap, a prominent geospatial data crowdsourcing platform. In addition, we compare and contrast these patterns with user edit patterns in Wikipedia, a well-known non-geospatial crowdsourcing platform. Using Google news and Google trends to derive a measure of thematic public awareness, our findings indicate that digital activism bursts tend to take place during periods of sustained build-up of public awareness deficit or surplus. These findings are in line with two prominent mass communication theories: agenda setting and corrective action, and suggest the emergence of a novel stimulus-awareness-activism framework in today’s participatory digital age. Moreover, these findings further complement existing research examining the motivational factors that drive users to contribute to online collaborative communities. This paper brings us one step closer to understanding the underlying mechanisms that drive digital activism in particular in the geospatial domain.

News trends and web search query of HIV/AIDS in Hong Kong.

BackgroundThe HIV epidemic in Hong Kong has worsened in recent years, with major contributions from high-risk subgroup of men who have sex with men (MSM). Internet use is prevalent among the majority of the local population, where they sought health information online. This study examines the impacts of HIV/AIDS and MSM news coverage on web search query in Hong Kong.MethodsRelevant news coverage about HIV/AIDS and MSM from January 1st, 2004 to December 31st, 2014 was obtained from the WiseNews databse. News trends were created by computing the number of relevant articles by type, topic, place of origin and sub-populations. We then obtained relevant search volumes from Google and analysed causality between news trends and Google Trends using Granger Causality test and orthogonal impulse function.ResultsWe found that editorial news has an impact on “HIV” Google searches on HIV, with the search term popularity peaking at an average of two weeks after the news are published. Similarly, editorial news has an impact on the frequency of “AIDS” searches two weeks after. MSM-related news trends have a more fluctuating impact on “MSM” Google searches, although the time lag varies anywhere from one week later to ten weeks later.ConclusionsThis infodemiological study shows that there is a positive impact of news trends on the online search behavior of HIV/AIDS or MSM-related issues for up to ten weeks after. Health promotional professionals could make use of this brief time window to tailor the timing of HIV awareness campaigns and public health interventions to maximise its reach and effectiveness.

Now You See Me, But You Don't Know: Consumer Processing of Native Advertisements in Online News Sites

ABSTRACTNative advertising has become a growing trend in news outlets to break through the clutter of advertisements to reach consumers. This exploratory study investigates consumers' cognitive processing of native advertisements in U.S. online news sites. Using think aloud techniques, 30 interviews revealed that two-thirds of participants saw native ads in the provided online news sites, but less than half of them were aware of the persuasive intent of the native ads. For those who recognized native advertisements in the news sites, brand elements, and ad disclosures were the most commonly reported identifiers. Furthermore, native advertising does not always generate negative perceptions. Practical and policy implications and future research directions are discussed.

Online Marketing for Media: The Case of Greek News Websites

Nowadays it is quite easy to create a news website and start promoting it online. However, the structure of a significant amount of news websites seems to have been changing, often deviating from trends of past years or even setting their own marketing direction. Based on seven hypotheses related with online marketing characteristics, the researchers gathered data from articles posted on Greek news websites that reported three major events. After visiting the websites for a second time in order to compare the data, they calculated our results. These results show a clearer picture of how the situation currently is for the top twenty Greek news websites according to Αlexa.com. This paper also highlights newer trends in online news reporting, such as the elimination of the “like” button in favour of the shares, and also makes suggestions for further research.

Temporal Topic Modeling to Assess Associations between News Trends and Infectious Disease Outbreaks

In retrospective assessments, internet news reports have been shown to capture early reports of unknown infectious disease transmission prior to official laboratory confirmation. In general, media interest and reporting peaks and wanes during the course of an outbreak. In this study, we quantify the extent to which media interest during infectious disease outbreaks is indicative of trends of reported incidence. We introduce an approach that uses supervised temporal topic models to transform large corpora of news articles into temporal topic trends. The key advantages of this approach include: applicability to a wide range of diseases and ability to capture disease dynamics, including seasonality, abrupt peaks and troughs. We evaluated the method using data from multiple infectious disease outbreaks reported in the United States of America (U.S.), China, and India. We demonstrate that temporal topic trends extracted from disease-related news reports successfully capture the dynamics of multiple outbreaks such as whooping cough in U.S. (2012), dengue outbreaks in India (2013) and China (2014). Our observations also suggest that, when news coverage is uniform, efficient modeling of temporal topic trends using time-series regression techniques can estimate disease case counts with increased precision before official reports by health organizations.

Study on public opinion propagation in self media age based on time delay differential model

With the emergence and popularization of computers, human society has entered the media age. On the one hand, it is beneficial to balance the supervision of public opinion and the construction of judicial responsiveness mechanism; on the other hand, false news increases the pressure of the government, and is not conducive to the establishment and enhancement of the government’s public trust. Therefore, it is very important for the whole society to study the law of the spread of Internet public opinion and then to control it.In this paper, we study the propagation law of Internet public opinion with the object of “ Xiongan New Area ”. Since the media network public opinion has the similar process of exponential growth in the communication process, and will be influenced by external capacity constraints, we establish the Logistic equation, introduce the τ operator time delay differential equation, and finally establish the improved delay differential equation, which can describe the propagation trend of network news from the self media. It provides certain reference for the government to study the development of public opinion.Click here and insert your abstract text.

The content analysis of the news trends on CCTV installation in child-care centers: Focused on the top ten newspapers

The content analysis of the news trends on CCTV installation in child-care centers: Focused on the top ten newspapers

Communicating Ebola through social media and electronic news media outlets: A cross-sectional study.

Social media and electronic news media activity are an important source of information for the general public. Yet, there is a dearth of research exploring the use of Twitter and electronic news outlets during significant worldly events such as the recent Ebola Virus scare. The purpose of this article is to investigate the use of Twitter and electronic news media outlets in communicating Ebola Virus information. A cross-sectional survey of Twitter data and Google News Trend data from 30 September till 29 October, 2014 was conducted. Between 30 September and 29 October, there were approximately 26 million tweets (25,925,152) that contained the word Ebola. The highest number of correlated activity for Twitter and electronic news outlets occurred on 16 October 2014. Other important peaks in Twitter data occurred on 1 October, 6 October, 8 October, and 12 October, 2014. The main influencers of the Twitter feeds were news media outlets. The study reveals a relationship between electronic news media publishing and Twitter activity around significant events such as Ebola. Healthcare organizations should take advantage of the relationship between electronic news media and trending events on social media sites such as Twitter and should work on developing social media campaigns in co-operation with leading electronic news media outlets (e.g. CNN, Yahoo, Reuters) that can have an influence on social media activity.

Framing responsibility for depression: how U.S. news media attribute causal and problem-solving responsibilities when covering a major public health problem

ABSTRACTThis paper analyzes how major U.S. print and broadcast news media framed depression causal and problem-solving responsibilities at individual and societal levels over the past three decades. Results from the content analysis showed that the media placed more causal and problem-solving responsibilities on individuals than the society. However, references to societal solutions increased moderately over time. Organizational differences emerged in news attribution of responsibilities, as print media presented more individual-level causes while broadcast media focused more on solutions at both individual and societal levels. Additionally, local newspapers put more problem-solving responsibilities on individuals than national newspapers, while a cable news channel allocated more time to the discussion of overall depression responsibilities than network TV. Findings are discussed in the context of cultural orientations, organizational constraints, changing practice and trends in health news reporting, and the broader political/social environment in which the news media operate. Practical implications for health journalism, mental health communication and advocacy, and public health policy-making are discussed.

How the machine ‘thinks’: Understanding opacity in machine learning algorithms

This article considers the issue of opacity as a problem for socially consequential mechanisms of classification and ranking, such as spam filters, credit card fraud detection, search engines, news trends, market segmentation and advertising, insurance or loan qualification, and credit scoring. These mechanisms of classification all frequently rely on computational algorithms, and in many cases on machine learning algorithms to do this work. In this article, I draw a distinction between three forms of opacity: (1) opacity as intentional corporate or state secrecy, (2) opacity as technical illiteracy, and (3) an opacity that arises from the characteristics of machine learning algorithms and the scale required to apply them usefully. The analysis in this article gets inside the algorithms themselves. I cite existing literatures in computer science, known industry practices (as they are publicly presented), and do some testing and manipulation of code as a form of lightweight code audit. I argue that recognizing the distinct forms of opacity that may be coming into play in a given application is a key to determining which of a variety of technical and non-technical solutions could help to prevent harm.