scholarly journals NewsFinder: Automating an AI News Service

AI Magazine ◽  
2012 ◽  
Vol 33 (2) ◽  
pp. 43
Author(s):  
Joshua Eckroth ◽  
Liang Dong ◽  
Reid G. Smith ◽  
Bruce G. Buchanan

NewsFinder automates the steps involved in finding, selecting, categorizing, and publishing news stories that meet relevance criteria for the Artificial Intelligence community. The software combines a broad search of online news sources with topic-specific trained models and heuristics. Since August 2010, the program has been used to operate the AI in the News service that is part of the AAAI AITopics website.

2018 ◽  
Author(s):  
Amanda Amberg ◽  
Darren N. Saunders

AbstractCancer research in the news is often associated with sensationalising and inaccurate reporting, giving rise to false hopes and expectations. The role of study selection for cancer-related news stories is an important but less commonly acknowledged issue, as the outcomes of primary research are generally less reliable than those of meta-analyses and systematic reviews. Few studies have investigated the quality of research that makes the news and no previous analyses of the proportions of primary and secondary research in the news have been found in the literature. The main aim of this study was to investigate the nature and quality of cancer research covered in online news reports by four major news sources from USA, UK and Australia. We measured significant variation in reporting quality, and observed biases in many aspects of cancer research reporting, including the types of study selected for coverage, and in the spectrum of cancer types, gender of scientists, and geographical source of research represented. We discuss the implications of these finding for guiding accurate, contextual reporting of cancer research, which is critical in helping the public understand complex science and appreciate the outcomes of publicly funded research, avoid undermining trust in science, and assist informed decision-making.


CCIT Journal ◽  
2012 ◽  
Vol 5 (2) ◽  
pp. 168-185
Author(s):  
Agustoni Agustoni ◽  
Fitri Maya Sari

With the rapid development of Internet, more and more also emerging sites or blogs that provide a wide range of online news articles. An article, before it can be published, originally sent by the reporter to editor to be sorted. Sorting type of news is relatively easily done by humans, but if the case was brought to a level of segregation in automation with computers will bring its own problems, although for a shorter story. Text mining is one way that is expected to solve the above problems. With text mining, can be searched words that can represent the content of news articles, then its category is determined based on the frequency of words contained in it. Stage by the author on the study are: (i) development of a database for the keyword vector, (ii) sorting of news sources based on the database of step (i). This paper is expected to help the electronic editorial system to be able to sort or find out the category of a news article without the need of an editor that saves time and cost of doing business on the model of an electronic news service on-line internet based.


PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0247553
Author(s):  
Laura Moorhead ◽  
Melinda Krakow ◽  
Lauren Maggio

Journalists’ health and science reporting aid the public’s direct access to research through the inclusion of hyperlinks leading to original studies in peer-reviewed journals. While this effort supports the US-government mandate that research be made widely available, little is known about what research journalists share with the public. This cross-sectional exploratory study characterises US-government-funded research on cancer that appeared most frequently in news coverage and how that coverage varied by cancer type, disease incidence and mortality rates. The subject of analysis was 11436 research articles (published in 2016) on cancer funded by the US government and 642 news stories mentioning at least one of these articles. Based on Altmetric data, researchers identified articles via PubMed and characterised each based on the news media attention received online. Only 1.88% (n = 213) of research articles mentioning US government-funded cancer research included at least one mention in an online news publication. This is in contrast to previous research that found 16.8% (n = 1925) of articles received mention by online mass media publications. Of the 13 most common cancers in the US, 12 were the subject of at least one news mention; only urinary and bladder cancer received no mention. Traditional news sources included significantly more mentions of research on common cancers than digital native news sources. However, a general discrepancy exists between cancers prominent in news sources and those with the highest mortality rate. For instance, lung cancer accounted for the most deaths annually, while melanoma led to 56% less annual deaths; however, journalists cited research regarding these cancers nearly equally. Additionally, breast cancer received the greatest coverage per estimated annual death, while pancreatic cancer received the least coverage per death. Findings demonstrated a continued misalignment between prevalent cancers and cancers mentioned in online news media. Additionally, cancer control and prevention received less coverage from journalists than other cancer continuum stages, highlighting a continued underrepresentation of prevention-focused research. Results revealed a need for further scholarship regarding the role of journalists in research dissemination.


Author(s):  
Kevin Wise ◽  
Hyo Jung Kim ◽  
Jeesum Kim

A mixed-design experiment was conducted to explore differences between searching and surfing on cognitive and emotional responses to online news. Ninety-two participants read three unpleasant news stories from a website. Half of the participants acquired their stories by searching, meaning they had a previous information need in mind. The other half of the participants acquired their stories by surfing, with no previous information need in mind. Heart rate, skin conductance, and corrugator activation were collected as measures of resource allocation, motivational activation, and unpleasantness, respectively, while participants read each story. Self-report valence and recognition accuracy were also measured. Stories acquired by searching elicited greater heart rate acceleration, skin conductance level, and corrugator activation during reading. These stories were rated as more unpleasant, and their details were recognized more accurately than similar stories that were acquired by surfing. Implications of these results for understanding how people process online media are discussed.


2018 ◽  
Vol 13 (1) ◽  
pp. 36-38
Author(s):  
Elizabeth Margaret Stovold

A Review of: Schaferm, S., Sulflow, M., & Muller, P. (2017). The special taste of snack news: an application of niche theory to understand the appeal of Facebook as a source for political news. First Monday, 22(4-3). http://dx.doi.org/10.5210/fm.v22i4.7431 Abstract Objective – To investigate Facebook as a source of exposure to political news stories and to compare the reasons for using Facebook as a news source and the gratifications obtained, compared with other news sources. Design – Survey questionnaire. Setting – Facebook. Subjects – 422 German Facebook users. Methods – An online survey was developed to investigate the use of Facebook as a news source compared with other sources. Specific research questions were informed by the ‘theory of niche’ (Dimmick, 2003) which examines the coexistence and competition between different media outlets by examining the breadth, overlap and superiority of one platform over another. The survey was distributed using a ‘snowball’ technique between July and August 2015. The survey was shared by 52 student research assistants on their Facebook profiles. They asked their friends to complete the survey and share it with their own networks. Main results – The mean (M) age of the 422 respondents was 23.5 years (SD=8.25). The majority were female (61%) with a high school degree (89%). TV news and news websites were the most frequently used sources of political news. Facebook ranked third, ahead of newspapers, search engines, magazines, email provider websites, and Twitter. The mean score for the importance of Facebook as a news sources was 2.46 (SD=1.13) on a scale of 1 to 5, where 1 is low and 5 is high. This fell in the middle of the range when compared with the top ranked source assessed by importance (TV news, M 4.40, SD=0.88) and the lowest (email providers, M 1.92, SD=0.97). Users rarely visited Facebook with the purpose of finding news (M 1.59, SD=0.73). However, they estimated around 24% of the posts they see were concerned with political news, and when encountered, these stories are frequently read (M 3.53, SD=1.18). However, the level of interaction as measured by liking, commenting, sharing or status updates was low (M 1.94 SD=1.09; M 1.37, SD=0.79; M 1.51, SD=0.85 and M 1.4, SD=0.78 respectively). The ‘gratification’ categories where Facebook as a news source scored the highest were for killing time (M 2.97, SD=1.29), entertainment (M 2.92, SD=1.05), and surveillance (M 2.77, SD=1.01). When compared to newspapers and TV news, it was found that Facebook has a lower score for niche breadth, meaning that it serves a specific rather than general news function. Facebook also had a lower overlap score when compared with the other media, thereby performing a complementary function, while TV news and newspapers perform similarly. TV news scored better for providing balanced information, surveillance and social utility while Facebook scored highest for killing time. There was no difference in the category of entertainment. There was a similar picture when comparing Facebook with newspapers. Conclusion – The authors conclude that while users do not actively seek political news through Facebook, they are exposed to political news through this medium. Respondents did not consider the news to be well balanced, and that currently Facebooks’ niche is restricted to entertainment and killing time. The authors note that this may be disappointing for news organisations, but there is potential to expose large audiences to political news when they are not actively seeking it. The findings represent a specific time point in a changing landscape and future research will need to take these changes into account. Comparisons with other online news sources and the use of objective measures to validate self-reported data would be valuable areas for future research.


2021 ◽  
Vol 13 (20) ◽  
pp. 11328
Author(s):  
Alfonso Vara-Miguel ◽  
Cristina Sánchez-Blanco ◽  
Charo Sádaba Sádaba Chalezquer ◽  
Samuel Negredo

Digital news publishers strive to balance revenue streams in their business models: as standard advertising declines, alternatives for sustaining digital journalism arise in the forms of sponsored content, user donations and payments—one-off purchases, subscriptions or memberships, public or private grants, electronic commerce, events and consulting. An exhaustive study found 2874 active online news publications in Spain, and it observed the adoption of such models in early 2021. Advertising remains the most popular source of income for digital news operations (85.8%) and most sites rely on just one or two revenue streams (74.5%). We compare the cases in our census by their origin (digital-native or non-native), geography (local/regional or national/global) and topic scope (generalist or specialized). We find that traditional, national and specialized online media have a broader and more innovative revenue mix than digital-native, regional or local and general-interest news outlets. The comprehensiveness of this pioneering study sheds light for the first time on the risk that the lack of diversification and innovation in funding sources may imperil the financial sustainability of some online news operations in Spain, mostly those with a smaller scope and no backing from a traditional business, according to the results we present here.


Media-N ◽  
2018 ◽  
Vol 13 (1) ◽  
Author(s):  
Rick Valentin

The Top Two News Words project began in 2007 as a gallery piece featuring a computer and dot matrix printer linked to an online parsing routine which gathered headlines from fifteen major news sources hourly, and analyzed and reduced these headlines to the two most frequently occurring words. The resulting pairs were printed each hour on a continuous sheet of computer paper, creating a linear document of the 24/7/365 news cycle. Since 2008, the online component of the piece has been running automatically, without its physical half, publishing hourly word pairs via RSS and on Twitter and building an online archive of nearly 90,000 hours of news. Top Two News Words has consistently evoked questions of bias from its audience: “Why only these sources? Why only sources in English? Who are you to decide what is a major news source?” This is, of course, one of the desired outcomes of the project. A deeper question, which is reflected in the recent controversy and surprise over Facebook’s use of human curators for trending topics, is why don’t we investigate for bias in supposedly neutral online news aggregators such as Google? And, is it even possible to filter news programmatically without bias? I seek to use this project to illustrate the simple concept that curation, bias and reduction are not the antithesis of awareness in a world of continuous, direct news but are an essential part of navigating and understanding this world.


2019 ◽  
Vol 19 (3) ◽  
pp. 50-58
Author(s):  
T. A. Fomina ◽  
E. D. Butsyk

The paper attempts to describe a number of linguistic and pragmatic aspects of modeling the anti-Russian discourse in the English language media headlines. The authors focus on the coverage of the Skripal poisoning case and the specific language means employed by a range of English-language news sources, such as The Guardian, BBC, CNN, Politico, The Mirror, The Daily Mail, The New Zealand Herald, The Herald. The results of the study indicate that one of the most effective and widespread media manipulation techniques is misinformation accompanied by a discrepancy between the headline and the content of the article. The research seeks to classify manipulation techniques according to the way of their actualization in the language and the degree of misinformation: full fabrication, partial fabrication, manipulated content, selective quoting, false connection, emphasizing communication relevant elements by means of the actual division of the sentence. The implementation of such manipulation techniques is aimed at shaping public opinion on the incident at issue in order to promote a negative image of Russia and its leader in terms of their alleged involvement in the Skripal attack.


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