144 resultados para TV news


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This week, Telstra announced it will shortly introduce a new streaming video set top box. For a number of reasons, this is a very smart move.

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More than 14 million Dish Network subscribers have been without Breaking Bad, Mad Men, and The Walking Dead since June when the satellite provider pulled AMC Networks—AMC, Sundance, IFC, and WE tv—from its lineup in a dispute over carriage fees. The tactic is called a blackout, and it’s becoming increasingly common in the television landscape as pay-TV operators and station owners battle over the nearly $5 billion at stake in the next 5 years.

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Digital media have contributed to significant disruptions in the business of audience measurement. Television broadcasters have long relied on simple and authoritative measures of who is watching what. The demand for ratings data, as a common currency in transactions involving advertising and program content, will likely remain, but accompanying measurements of audience engagement with media content would also be of value. Today's media environment increasingly includes social media and second-screen use, providing a data trail that affords an opportunity to measure engagement. If the limitations of using social media to indicate audience engagement can be overcome, social media use may allow for quantitative and qualitative measures of engagement. Raw social media data must be contextualized, and it is suggested that tools used by sports analysts be incorporated to do so. Inspired by baseball's Sabremetrics, the authors propose Telemetrics in an attempt to separate actual performance from contextual factors. Telemetrics facilitates measuring audience activity in a manner controlling for factors such as time slot, network, and so forth. It potentially allows both descriptive and predictive measures of engagement.

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This study seeks to understand the prevailing status of Nepalese media portrayal of natural disasters and develop a disaster management framework to improve the effectiveness and efficiency of news production through the continuum of prevention, preparedness, response and recovery (PPRR) phases of disaster management. The study is currently under progress. It is being undertaken in three phases. In phase-1, a qualitative content analysis is conducted. The news contents are categorized in frames as proposed in the 'Framing theory' and pre-defined frames. However, researcher has looked at the theories of the Press, linking to social responsibility theory as it is regarded as the major obligation of the media towards the society. Thereafter, the contents are categorized as per PPRR cycle. In Phase-2, based on the findings of content analysis, 12 in-depth interviews with journalists, disaster managers and community leaders are conducted. In phase-3, based on the findings of content analysis and in-depth interviews, a framework for effective media management of disaster are developed using thematic analysis. As the study is currently under progress hence, findings from the pilot study are elucidated. The response phase of disasters is most commonly reported in Nepal. There is relatively low coverage of preparedness and prevention. Furthermore, the responsibility frame in the news is most prevalent following human interest. Economic consequences and conflict frames are also used while reporting and vulnerability assessment has been used as an additional frame. The outcomes of this study are multifaceted: At the micro-level people will be benefited as it will enable a reduction in the loss of human lives and property through effective dissemination of information in news and other mode of media. They will be ‘well prepared for', 'able to prevent', 'respond to' and 'recover from' any natural disasters. At the meso level the media industry will be benefited and have their own 'disaster management model of news production' as an effective disaster reporting tool which will improve in media's editorial judgment and priority. At the macro-level it will assist government and other agencies to develop appropriate policies and strategies for better management of natural disasters.

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Journalism education’s role in shaping students’ professional views has been a topic of interest among scholars for the past decade in particular. Increasing numbers of studies are concerned with examining students’ backgrounds and views in order to identify what role exposure to the tertiary environment may play in socializing them into the industry. This study reports on the results of the largest survey of Australian journalism students undertaken to date, with a sample size of 1884 students. The study finds that time spent studying journalism appears to be related to changes in role perceptions and news consumption. Final-year students are significantly more likely to support journalism’s watchdog role and to reject consumer-oriented and ‘loyal’ roles. They also consume more news than first-year students. On the other hand, journalism education appears to have little impact on views of controversial practices, with only marginal differences between final- and first-year students.

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Clustering identities in a video is a useful task to aid in video search, annotation and retrieval, and cast identification. However, reliably clustering faces across multiple videos is challenging task due to variations in the appearance of the faces, as videos are captured in an uncontrolled environment. A person's appearance may vary due to session variations including: lighting and background changes, occlusions, changes in expression and make up. In this paper we propose the novel Local Total Variability Modelling (Local TVM) approach to cluster faces across a news video corpus; and incorporate this into a novel two stage video clustering system. We first cluster faces within a single video using colour, spatial and temporal cues; after which we use face track modelling and hierarchical agglomerative clustering to cluster faces across the entire corpus. We compare different face recognition approaches within this framework. Experiments on a news video database show that the Local TVM technique is able effectively model the session variation observed in the data, resulting in improved clustering performance, with much greater computational efficiency than other methods.

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Despite its rising success, interactive TV (iTV) has found very little attention in the field of HCI. Therefore, the aim of this paper is to investigate the usability of iTV services. It presents the results of a usability test and discusses the implications for further developments. The results show, that prior knowledge of Internet and mobile phones supports the usability of iTV services regarding navigation and text input, while the lack of it leads to great difficulties. Difficult tasks, such as writing a text message, had a success rate of only 20%, while guided tours proofed to be more usable with a success rate of 70%.

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This paper explores the use of public journalism within a community radio news context. It argues that, the central tenets of the public journalism movement can help to frame, more adequately, a news gathering and production approach Tailored to the needs of community media. . Community radio stations generally enjoy strong relationships with their listeners and play an important role in the formation of the community itself (Lowrey et al., 2008). This paper argues that such strong community ties, in conjunction with public journalism news gathering approaches give community radio stations a strong opportunity to produce relevant, local news sourced driven by their listeners. In this regard ,this paper examines a particular case of public journalism used within the The Wire, a national, daily current affairs program broadcast on community radio. In the case study examined here ,public journalism informed story production that were designed to better meet the needs of community radio stations and their audiences.

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Twitter’s hashtag functionality is now used for a very wide variety of purposes, from covering crises and other breaking news events through gathering an instant community around shared media texts (such as sporting events and TV broadcasts) to signalling emotive states from amusement to despair. These divergent uses of the hashtag are increasingly recognised in the literature, with attention paid especially to the ability for hashtags to facilitate the creation of ad hoc or hashtag publics. A more comprehensive understanding of these different uses of hashtags has yet to be developed, however. Previous research has explored the potential for a systematic analysis of the quantitative metrics that could be generated from processing a series of hashtag datasets. Such research found, for example, that crisis-related hashtags exhibited a significantly larger incidence of retweets and tweets containing URLs than hashtags relating to televised events, and on this basis hypothesised that the information-seeking and -sharing behaviours of Twitter users in such different contexts were substantially divergent. This article updates such study and their methodology by examining the communicative metrics of a considerably larger and more diverse number of hashtag datasets, compiled over the past five years. This provides an opportunity both to confirm earlier findings, as well as to explore whether hashtag use practices may have shifted subsequently as Twitter’s userbase has developed further; it also enables the identification of further hashtag types beyond the “crisis” and “mainstream media event” types outlined to date. The article also explores the presence of such patterns beyond recognised hashtags, by incorporating an analysis of a number of keyword-based datasets. This large-scale, comparative approach contributes towards the establishment of a more comprehensive typology of hashtags and their publics, and the metrics it describes will also be able to be used to classify new hashtags emerging in the future. In turn, this may enable researchers to develop systems for automatically distinguishing newly trending topics into a number of event types, which may be useful for example for the automatic detection of acute crises and other breaking news events.