Search (232 results, page 1 of 12)

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Date

14. 8.2002 11:47:22

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Abstract

Google News and other newsbots have automated the process of news selection, providing Internet users with a virtually limitless array of news and public information dynamically culled from thousands of news organizations all over the world. In order to help users cope with the resultant overload of information, news leads are typically accompanied by three cues: (a) the name of the primary source from which the headline and lead were borrowed, (b) the time elapsed since the story broke, and (c) the number of related articles written about this story by other news organizations tracked by the newsbot. This article investigates the psychological significance of these cues by positing that the information scent transmitted by each cue triggers a distinct heuristic (mental shortcut) that tends to influence online users' perceptions of a given news item, with implications for their assessment of the item's relevance to their information needs and interests. A large 2 x 3 x 6 withinsubjects online experiment (N = 523) systematically varied two levels of the source credibility cue, three levels of the upload recency cue and six levels of the number-ofrelated-articles cue in an effort to investigate their effects upon perceived message credibility, newsworthiness, and likelihood of clicking on the news lead. Results showed evidence for source primacy effect, and some indication of a cue-cumulation effect when source credibility is low. Findings are discussed in the context of machine and bandwagon heuristics.

Date

7. 3.2007 16:22:24

Object

Google news

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Date

19. 1.2019 17:42:22

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Date

22. 7.1996 19:53:48

Source

Library Hi Tech News. 1995, no.128, S.1-4

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Abstract

News is information about recent events of general interest, especially as currently reportes by newspapers, periodicals, radio or television. News is the quintessential multimedia data. While newspaper editors (human and/or algorithmic) may still define the core content of electronic news, new communication technologies will enable the integration of news from a wide variety of sources and provide access to supplemental material from enormous archives of electronic news data (text, photos, and video) in digital libraries as well as the continual streams of newly created data. The goal of electronic news delivery within this context is, however, distiguishable from both news news groups and document retrieval. Electronic news promises to deliver to the reader an edited collage of recent events from wide domains in a manner that is both comprehensive and personalized. As part of a long-term research project into the design of future news delivery systems, we have developed an overall architecture and several prototypes. These prototypes are presented in the article, along with a discussion of issues related to the presentation metaphor and to the functionality of electronic news delivery services. A prototype was demonstrated at the 1995 G-7 Economic Summit in Halifax, Canada, integrating newspaper text and photographs with television news video clips across an ATM network

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Abstract

Although the Internet has become a major source for accessing news, there is little research regarding users' experience with news sites. We conducted an experiment to test a comprehensive model of user experience with news sites that was developed previously by means of an online survey. Level of adoption (novel or adopted site) was controlled with a between-subjects manipulation. We collected participants' answers to psychometric scales at 2 times: after presentation of 5 screenshots of a news site and directly after 10 minutes of hands-on experience with the site. The model was extended with the prediction of users' satisfaction with news sites as a high-level design goal. A psychometric measure of trust in news providers was developed and added to the model to better predict people's intention to use particular news sites. The model presented in this article represents a theoretically founded, empirically tested basis for evaluating news websites, and it holds theoretical relevance to user-experience research in general. Finally, the findings and the model are applied to provide practical guidance in design prioritization.

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Abstract

Examines the problem of a compelling online news delivery system by focusing on how mass media audiences and online users differ in their assessment of news. It employed a 2-wave USA national survey to study the perception of interactivity in mass media and computer networks and its relationship to the assessment of news. The 1st wave looked a national probability sample, ahile the 2nd targeted viewers of NBC Nightly News who responded to the show via e-mail. NBC respondents rated mass media to be less interactive, while they rated computer communication more interactive than the national sample. The NBC group also rated mass media news less important and of lower quality than did the national sample. Interactivity ratings did not predict mass media credibility assessment for either group. However, respondents who defined interactivity as cybernetic feedback or who contacted NBC by e-mail rated computer communication to be more credible than thos who did not

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Abstract

Electronic news has long held the promise of personalized and dynamic delivery of current event new items, particularly for Web users. Although wlwctronic versions of print news are now widely available, the personalization of that delivery has not yet been accomplished. In this paper, we present a methodology of associating news documents based on the extraction of feature phrases, where feature phrases identify dates, locations, people and organizations. A news representation is created from these feature phrases to define news objects that can then be compared and ranked to find related news items. Unlike tradtional information retrieval, we are much more interested in precision than recall. That is, the user would like to see one or more specifically related articles, rather than all somewhat related articles. The algorithm is designed to work interactively the the user using regular web browsers as the interface

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Abstract

As the Web has become a major channel of information dissemination, many newspapers expand their services by providing electronic versions of news information on the Web. However, most investors find it difficult to search for the financial information of interest from the huge Web information space-information overloading problem. In this article, we present a personal agent that utilizes user profiles and user relevance feedback to search for the Chinese Web financial news articles on behalf of users. A Chinese indexing component is developed to index the continuously fetched Chinese financial news articles. User profiles capture the basic knowledge of user preferences based on the sources of news articles, the regions of the news reported, categories of industries related, the listed companies, and user-specified keywords. User feedback captures the semantics of the user rated news articles. The search engine ranks the top 20 news articles that users are most interested in and report to the user daily or on demand. Experiments are conducted to measure the performance of the agents based on the inputs from user profiles and user feedback. It shows that simply using the user profiles does not increase the precision of the retrieval. However, user relevance feedback helps to increase the performance of the retrieval as the user interact with the system until it reaches the optimal performance. Combining both user profiles and user relevance feedback produces the best performance

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Abstract

We study the news reading behavior of several hundred thousand users on 65 highly visited news sites. We focus on a specific phenomenon: users reading several articles related to a particular news development, which we call story-focused reading. Our goal is to understand the effect of story-focused reading on user engagement and how news sites can support this phenomenon. We found that most users focus on stories that interest them and that even casual news readers engage in story-focused reading. During story-focused reading, users spend more time reading and a larger number of news sites are involved. In addition, readers employ different strategies to find articles related to a story. We also analyze how news sites promote story-focused reading by looking at how they link their articles to related content published by them, or by other sources. The results show that providing links to related content leads to a higher engagement of the users, and that this is the case even for links to external sites. We also show that the performance of links can be affected by their type, their position, and how many of them are present within an article.

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Abstract

The proliferation of film and television sites on the Internet reflects the high entertainment value of this resource. Provides a list of sites which should be popular with both academic and public users focusing on WWW sites. These include: general link sites; organizations; individual films and genres; film directors; film reviews; film studios; television networks; television news; television news and discussion groups

Source

College and research libraries news. 56(1995) no.6, S.397-400

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Abstract

Gives details of USA newspapers available on the Internet. Many of the sites add hyperlinks and multimedia to their sites. Most are currently free, as advertising generates revenue, but pressure on this may force some to become fee-based. Describes indexes and personalised Internet news services

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Abstract

Most on-line news sources are electronic versions of "ink-on-paper" newspapers. These are versions that have been filtered, from the mass of news produced each day, by an editorial board with a given community profile in mind. As readers, we choose the filter rather than choose the stories. New technology, however, provides the potential for personalized versions to be filtered automatically from this mass of news on the basis of user profiles. People read the news for many reasons: to find out "what's going on," to be knowledgeable members of a community, and because the activity itself is pleasurable. Given this, we ask the question, "How much filtering is acceptable to readers?" In this study, an evaluation of user preference for personal editions versus community editions of on-line news was performed. A personalized edition of a local newspaper was created for each subject based on an elliptical model that combined the user profile and community profile as represented by the full edition of the local newspaper. The amount of emphasis given the user profile and the community profile was varied to test the subjects' reactions to different amounts of personalized filtering. The task was simply, "read the news," rather than any subject specific information retrieval task. The results indicate that users prefer the coarse-grained community filters to fine-grained personalized filters

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Abstract

Virtually all UK and US newspapers and the vast majority of regional and even local titles are now represented on the web. Indeed, the Yahoo news and media directory lists no less than 114 UK newspapers online (as of November 1998). Broadcasters from the BBC and Sky downwards, and all the famous news agencies (Press Association, Reuters etc.) also boast comprehensive Internet services. With such an array of sources available, the future of mass access to the Internet, possibly via TV terminals, suggests that more and more people may soon opt for this medium to receive the bulk of their news information. This paper gives an overview of the characteristics of the medium illustrated with examples of how these are being used to both facilitate and enhance the content and dissemination of the news product. These characteristics include hyperlinking to external information sources, providing archive access to past reports, reader interactivity and other features not possible to incorporate into more passive media such as the hardcopy newspaper. From a survey of UK and US news providers it is clear that American newspapers are exploiting the advantages of web information dissemination to a far greater extent than their British counterparts, with the notable exception of The Electronic Telegraph. UK broadcasters, however, generally appear to have adapted better to the new medium, with the BBC rivaling CNN in its depth and extent of news coverage, use of links and other elements.

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Abstract

In this article we report on an experiment that tested how useful library-based guidelines are for measuring the integrity of information in the era of fake news. We found that the usefulness of these guidelines depends on at least three factors: weighting indicators (criteria), clear instructions, and context-specificity.

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Abstract

In this article we report on an experiment that tested how useful library-based guidelines are for measuring the integrity of information in the era of fake news. We found that the usefulness of these guidelines depends on at least three factors: weighting indicators (criteria), clear instructions, and context-specificity.

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Abstract

Multisource web news portals provide various advantages such as richness in news content and an opportunity to follow developments from different perspectives. However, in such environments, news variety and quantity can have an overwhelming effect. New-event detection and topic-tracking studies address this problem. They examine news streams and organize stories according to their events; however, several tracking stories of an event/topic may contain no new information (i.e., no novelty). We study the novelty detection (ND) problem on the tracking news of a particular topic. For this purpose, we build a Turkish ND test collection called BilNov-2005 and propose the usage of three ND methods: a cosine-similarity (CS)-based method, a language-model (LM)-based method, and a cover-coefficient (CC)-based method. For the LM-based ND method, we show that a simpler smoothing approach, Dirichlet smoothing, can have similar performance to a more complex smoothing approach, Shrinkage smoothing. We introduce a baseline that shows the performance of a system with random novelty decisions. In addition, a category-based threshold learning method is used for the first time in ND literature. The experimental results show that the LM-based ND method significantly outperforms the CS- and CC-based methods, and category-based threshold learning achieves promising results when compared to general threshold learning.

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Abstract

In this work, we explore the types of triggers that spark trends on Twitter, introducing a typology with the following 4 types: news, ongoing events, memes, and commemoratives. While previous research has analyzed trending topics over the long term, we look at the earliest tweets that produce a trend, with the aim of categorizing trends early on. This allows us to provide a filtered subset of trends to end users. We experiment with a set of straightforward language-independent features based on the social spread of trends and categorize them using the typology. Our method provides an efficient way to accurately categorize trending topics without need of external data, enabling news organizations to discover breaking news in real-time, or to quickly identify viral memes that might inform marketing decisions, among others. The analysis of social features also reveals patterns associated with each type of trend, such as tweets about ongoing events being shorter as many were likely sent from mobile devices, or memes having more retweets originating from a few trend-setters.

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Source

College and research libraries news. 54(1993) no.3, S.139-140