E‐commerce resources on the web

Ubiquitous access to internet has resulted in more and more people going online to get their daily dose of news. In a 2010 survey conducted by the Pew Project for Excellence in Journalism, 41% of the respondents said they get most of their news online, 10% more than those who said they got most of their news from a newspaper. A lot of socio-technical factors have contributed to this phenomenal rise in adoption of online news in recent years. One of the biggest reasons why people are increasingly reading news online is because it facilitates discussion with peers (Nguyen 2010), offering different viewpoints which aid in forming a rounded personal opinion about the news story. The Pew survey found that 37% of online news users (and 51% of 18-29 year olds) think that commenting on news stories is an important feature to have. A lot of people tend to shape their opinion by reading discussion comments, reflective articles, blogs and even tweets about the news. Hence, an increasing number of people rely on online sources of news – be it news websites or news aggregator services like Digg, Reddit, Google Reader, Flipboard, Pulse etc. The problem with these news websites and aggregators is that the only way people can gather public opinion is by actively searching through the endless stream of comments and feeds, filtering out spam (which is a growing problem) and then reading the relevant posts. A top trending story on Twitter will typically see multiple tweets per second, and keeping up with the rapid flow of incoming tweets is quite cumbersome and cognitively taxing. Hence it becomes increasingly difficult and time consuming for someone who wants to get the pulse of the people affected by a news story. Furthermore, in certain scenarios people might want to look at more fine grained opinions. Currently, there is no elegant way to extract geographic and demographic impact of a news story. What is the public sentiment in Indonesia about the Arab Spring? How did the public opinion about the Wikileaks disclosures change as the story unfolded during the course of a year? It is very difficult and tedious to observe such patterns using the currently available news providers. This work attempts to solve these problems by proposing a news aggregator platform which pulls news stories from various sources and also aggregates public responses, reflections, opinions and sentiments associated with those stories. This data is presented in ways that are easily understandable so readers can make better sense of the stories unfolding across the globe. Such a news aggregator platform that gathers and display public opinion and sentiments about a story, must deal with various challenges – 1. Opinions are very subjective. Different people feel about a story in different ways. With such an enormous amount of diverse opinions and subjectivity, how can we possibly aggregate the responses into something that makes sense as a whole? ________________________________ Acknowledgements: Prof. Yardi, S. for the guidance Sethi, P. (2013). Public opinion aggregation by annotation and tagging of online news stories. iConference 2013 Proceedings (pp. 891-894). doi:10.9776/13453 Copyright is held by the author. iConference 2013 February 12-15, 2013 Fort Worth, TX, USA 892 2. There isn’t really a unified web standard for expressing opinion (in textual form). Some people tweet in 140 characters, while others write elaborate blog posts. Some websites employ tags which a reader can use to define and classify their public opinion, while others rely on threaded comments and comment ranking systems. How can a platform be flexible enough to adapt to all these varied standards so that it can extract valuable data from various sources? Perhaps the platform can create a new standard of expression on the web which is flexible and comprehensive enough to be used to express diverse views about every news story in the world. 3. How to filter out spam while extracting public opinion? 4. Once the platform has access to the data it needs, how should it be displayed to the reader in a way that makes sense? What forms of visualizations, illustrations and graphical representations can be employed to give the reader a holistic view of how people feel about a story? 5. How can the platform determine and convey effects of geographical, demographic and temporal variations as the story unfolds? These are just a few out of possibly many issues which must be dealt with. Previous research on similar public opinion aggregation services has greatly focused on natural language processing, data mining and text categorization and clustering. Xiaojun (2010) proposed a framework for crawling the web for comments and applying various data mining algorithms on the data to extract relevant information. Diakopoulos and Shamma (2010) used tweets posted in conjunction with the live presidential debate between Barack Obama and John McCain to gauge public opinion. Brody and Diakopoulos (2011) studied the use of word lengthening to detect sentiment in microblogs. This research proposes a solution – The Opinionated Reader, which relies on sentiment tags and annotations associated with a news story. The essential idea is to create a commenting, discussion and sharing plug-in which can be used by news websites and aggregators as a commenting solution for their news pages. Users wanting to share or comment on a news story through the plug-in are asked to tag the news story with sentiment tags and annotate the story with their reaction (happy/positive or sad/negative). These tags and annotations are stored, aggregated and linked to each news story. A mobile application provides the front-end interface for users to access the news stories and the aggregated sentiment associated with each story. The basic architecture is explained as follows: The Opinionated Reader – Mobile/Tablet App The app fetches news articles from various web sources, based on the interests and preferences configured by the user. In every news article, a portion of the screen real estate is reserved for Opinions which shows graphical visualizations and illustrations of the public opinion surrounding the news story. These visualizations include: A Sentiment Graph indicating the popular tags associated with the story (E.g.: “Shocking”, “Inspiring”, “Amusing” etc.). See Figure 1 for example visualization. A Positivity Graph which plots the level of positivity associated with the story on a time scale from when the news broke. See Figure 2 for example visualization. Figure 1. Example Sentiment Graph Figure 2. Example Positivity Graph iConference 2013 February 12-15, 2013 Fort Worth, TX, USA 893 The user can choose to see these visualizations for a particular time period in the evolution history of the news story, or for a specific country. The app also facilitates people to tag and annotate news articles from within its interface. The Opinionated Reader – Commenting and Sharing Web Plug-in These days, a common way of adding discussion and commenting functionality to news websites is by using 3 rd party services (like DISQUS). The Opinionated Reader is a similar service which can be embedded into the news articles of various news websites to enable commenting and sharing. When someone wishes to comment on an article, the comment is directed through this plug-in, which allows the users to annotate the article with the sentiment tags and reactions along with their comments. The Opinionated Reader saves this information along with the commenter’s location and date of comment (See Figure 3). Figure 3. The Opinionated Reader Web Plug-in 'Add Comment' dialog mockup The Opinionated Reader – Back-end The Back-end maintains a database of news items extracted from RSS feeds of various news websites. Each news article is linked with the sentiment tags and reaction/positivity annotations extracted from the comments and annotations gathered by the commenting plug-in. This data is used by the mobile/tablet app to generate visualizations (Sentiment Graph and Positivity Graph). The back-end also performs data mining on the tags and annotations for geographies and tracks the opinions across time. The back end system responds to queries received from the mobile app with the news story and associated tags and annotations, which are then rendered by the mobile app for the user. iConference 2013 February 12-15, 2013 Fort Worth, TX, USA 894 Discussion and Conclusion This design idea is still in a nascent state and has long hours of research, brainstorming, designing and development to go before it can be realized into something tangible. Twitter has grown exponentially in importance as a news source and it would be vastly valuable to integrate Twitter with The Opinionated Reader. Possibilities include use of special hash tags and natural language processing of tweets to extract public sentiment. The current design supports only two reaction annotations – positive and negative. Not every news story fits this annotation paradigm. Further research about human reactions to news stories might unveil interesting insights which would help zero in on a more robust annotation rubric. Lastly, since this service is envisioned to be non-curated and non-moderated, the value served by the app depends on the users themselves. Greater adoption will lead to more annotations and tags, which translates into a more accurate public opinion as presented to the user.

This paper focus on TV news programs and design a content-based news video browsing and retrieval system, NVRS, which is convenient for users to fast browsing and retrieving news video by different categories such as political, finance, amusement, etc. Combining audiovisual features and caption text information, the system automatically segments a complete news program into separate news stories. NVRS supports keyword-based news story retrieval, category-based news story browsing and generates key-frame-based video abstract for each story. Experiments show that the method of story segmentation is effective and the retrieval is also efficient.

This experiment investigated the effects of television news frames on (1) audience interpretations of a political issue, (2) the salience of news frames versus other information in the story, and (3) support for future policy. A sample of 145 adults watched an experimental television news bulletin produced in cooperation with reporters and editors at a national television news program about the enlargement of the European Union. A news story was manipulated to reflect a conflict frame or an economic consequences frame. The two frames provide direction to the audience's thoughts about the issue but do not yield different levels of policy support. Frames in the news are as important as core facts in a news story when citizens conceive of a political issue.

Our goal is to enable viewers to access TV programs based on their content. Towards this end, we present a system that automatically captures and processes TV news programs into a database that can be searched over the internet. Users browse this database by submitting simple English queries. The results of the query is a hyperlinked list of matching news stories. Clicking on any item in the list immediately launches a video of the pertinent part of the news broadcast. We segment TV news broadcasts into distinct news stories. We then index each story as a separate entity. In reply to a query, videos for these news stories are displayed rather than the whole TV program. News program s ar usually accompanied by a transcript in closed caption text. The closed caption text contains markers for story boundaries. Due to the live nature of TV news programs, the closed caption lags the actual audio/video by varying amounts of time up to a few seconds. The closed caption text, thus, has to be shifted to be aligned in time to the video. We use video and audio events to do this synchronization. The closed caption for each story is entered into a database. In response to a query, the database retrieves and ranks the matching closed caption stores. An HTML document is returned to the user which lists: 1) the name and time of the news program that this story belongs to, 2) thumbnails providing a visual summary of the story, 3) closed caption text. To view a news story, the user simply clicks on an item form the list and the video for that story is streamed onto a media player at the user side. This system maintains the manner of presentation of the media, namely video for TV programs, while allowing the common search and selection techniques used on the web.

The issue of the conflict of values in the licensing procedure for broadcasting radio and television programmes is a special case of such a clash in public economic law. The study entitled “Conflict of values in the licensing procedure for broadcasting radio and television programmes in Poland” aimed to conduct analyses to identify the values underlying licensing proceedings for broadcasting radio and television programmes in Poland, examine their potential for conflict and identify ways of resolving disputes arising in this area. The main issue of the article is formulated in the following question: “can the values determining the licensing procedure for broadcasting of radio and television programmes give rise to axiological conflicts, and if so, how should the conflicts be resolved?” The analyses conducted as part of the study led to the conclusion that the Polish broadcasting licensing procedure is determined by a number of values that may clash with one another. The entities responsible for resolving conflicts in practice and specific cases include the National Broadcasting Council and its President at the level of the administrative proceedings and the administrative courts at the level of administrative court proceedings. The settlement is based on the law, which, however, contains a number of general clauses. In order to interpret them correctly and, consequently, fairly resolve the conflict, it is crucial to refer to the fundamental source of all human rights and freedoms, including economic freedom and freedom of expression, paramount in this process – human dignity.

Constructing and application of multimedia TV-news archives

News videos delivered from different sources constitute a huge volume of daily information. These videos, overall, form a huge collection of news stories that are intertwined with various novel and old topic themes. To date, it remains a challenging task on how to automatically extract a concise view of news stories according to topic themes. This doctoral thesis studies the issues in story dependency threading and topical auto-documentary in news stories. Initially, a co-clustering algorithm is proposed to perform the news story clustering by exploiting the duality between stories and multi-modal concepts. Then, the novelty and redundancy detection is performed to capture the relationship among stories of a topic. To facilitate the fast navigation of news topic, a novel topic structure is then proposed to chains the dependencies of stories. A main thread is extracted to highlight the important aspects of a theme. A news video editing optimization algorithm can be directly applied to automatically select suitable video and speech contents from the original video source to create an edited video documentary.

Media coverage of political actors and debates is a crucial avenue for voters to learn about political parties and their policies. However, nowadays party-media agenda-setting is increasingly shaped by large-scale transformations and the fragmentation of political communication across various party channels (e.g., press releases, social media, speeches) and media types (e.g., newspapers, television, online news), potentially affecting the provision of political information. This article examines these dynamics using large-scale textual data from political parties ( n = 17,677) and media outlets ( n = 90,531) published in the run-up to the Austrian national election in 2019. Building on the measurement of text similarity with state-of-the-art transformer-based models and multiverse analysis, we investigate the success of party messages from press releases, parliamentary speeches, Facebook and Twitter making it into important national newspapers, online news sites as well as television and radio news programs. The article shows that the variety in party channels and media outlets—with their distinct characteristics, modalities, and (technological) affordances—create different flows of information between the parties and the media. Press releases remain crucial tools for parties to get their messages into the media, while social media and parliamentary speeches also matter, albeit with varying effects by party. We also find that online news is more receptive to party messages than print, television, or radio news. Despite these differences, journalistic gate-keeping consistently favors large and government parties across all media types. These findings underscore the need for nuanced research into the interaction between party communication channels and media outlets in contemporary democracies.

Existing research on news video analysis mainly concentrates on structure analysis, semantic concept detection, annotation and search. However, little work has been contributed to news video people community analysis, which is helpful for users to understand the event. In this paper, we propose a novel approach to classify the people appearing in the news video into different communities. In our approach, the people appearing in the news video are first identified by associating their faces with names. The faces are detected from the video frames, and the names are obtained from the text. Then, the people belonging to the same organization are clustered. After that, the relationships between these organizations are determined using sentiment analysis. The sentiment words are diverse in each news story and contain both positive and negative ones. However, we have news title, which is the summary of the story and the sentiment of which is clear, to help us to mine the relationships between the organizations. At last, social networks are built to classify those people/organizations into different classes, and the people/organizations are ranked in each community according to their influence. The main contributions of the paper are two folds: 1) we propose a novel approach to present the news video event according to communities; 2) we propose to use the sentiment analysis and social network to classify the news people/organizations. The experimental results on the selected news topics demonstrate that the proposed approach is effective.

In this paper, we present a schema for content-based analysis of broadcast news video. First, we separate commercials from news using audiovisual features. Then, we automatically organize news programs into a content hierarchy at various levels of abstraction via effective integration of video, audio, and text data available from the news programs. Based on these news video structure and content analysis technologies, a TV news video Library is generated, from which users can retrieve definite news story according to their demands.

A survey of a Midwestern community supported a public health model of crime reporting and found respondents saying media pay too much attention to crime. Respondents provided modest support for cultivation theory, with no differences found for effects of newspapers and television. Violence is popular in America. It is ubiquitous. It leads to boffo box office. It is a popular topic in political campaigns. It is a cheap and easy way to sell newspapers or bump up ratings. This paper seeks to address sociological effects of violence in media, to discuss how violence is generally covered by news media on a level, to assess feelings of residents of a Midwestern university town regarding news coverage and analyze survey results from both cultivation effects and public health reporting perspectives. Violence in media Violence in media is a longstanding issue. In early research, George Gerbner noted violence in 66 percent of approximately 3,000 American films produced from 1950 to 1961. He also observed, in 1950s, that more than 75 percent of television drama contained acts of violence and it predominated in 56 percent of programs. In 1967 and 1968, he recorded that 80 percent of television programming contained violent portrayals.(1) A three-year study sponsored by National Cable Television Association found that violence continues to be prevalent. Prime time broadcast programs containing violent content increased by 14 percent between 1994 and 1998 and similar content increased by 10 percent on cable stations during same time frame(1). The percentage of prime time broadcast and cable programs with violence ranged from 58 percent in year one to 61 percent in years two and three. Researchers found that a minimum of six violent incidents occur in each hour of typical violent program.(2) But violent content is not limited to entertainment programming. also is a dominant topic of news broadcasts. Paul Klite, Robert Bardwell and Jason Salzman found that crime stories consumed about a third of total time devoted to news. They found that violent crimes are most frequently aired and that though infrequent among crime types, is most commonly covered crime on television newscasts. On 56 stations, more than half crime coverage relates to murder, they wrote.(3) John McManus was interested to learn whether, in making news decisions, television news would be treated as a commodity, following an economic model, or a public service, following a journalistic model. He found that television news, in large part, was simply a regurgitation of newspaper content. This observation provides evidence that newspapers play an influential role in news agenda-setting process not only of their own organizations, but in that of broadcast news outlets as well. McManus found economic model dominated three stations he observed. There was little attention paid to innovation in news gathering.(4) Crime news is a staple of journalism, and reporting it has been considered a public duty of press. Nevertheless, Walter Jaehnig and his colleagues found newspapers emphasize relatively infrequent violent crimes.(5) A 1994 study by Center for Media and Public Affairs showed that news stories regarding crimes more than tripled between 1990 and 1994. Gerbner reported that local TV news crime reports [doubled] in past two years [1995-96].(6) Phyllis Kaniss notes that today's journalists identify strongly with power structures-city and county officers, police and fire departments, housing authorities and so forth. The news that emerges from these sources is often bad news - news of crime, indigence, health problems and so forth.(7) One study showed that newspapers in St. Louis greatly distorted reality of criminal activity. E.T. Jones found that the typical murder had slightly more than 90 times as much attention as average major crime. …

Index to Volme 62, 2018

In this study it is argued that the well-known Palmgreen and Rayburn model of uses and gratifications based on a expectancy-value perspective can be utilized for the analysis of radio listeners' use of radio programmes. This model was originally developed from research on television news. It seems necessary to adjust this model to increase its generalizability regarding intercultural studies and the use of different mass media. This research was done among Black radio listeners in the PWV area. From the results it seems that the majority of the respondents were able to satisfy their needs for information, education and entertainment through selective exposure to radio programmes.

It's no secret that the representation of migrant groups in the media has been particularly problematic, as has been their access to mainstream media, and both issues have attracted a great deal of research. Far less attention has been paid by researchers to how these groups respond when they experience such difficulties, and the various forms of media they use to engage with a variety of issues pertinent to them and their settlement experiences. This article uses data from two projects: Australia's first, and to date only, national study of community radio audiences; and a more recent case study of a community radio station undertaken in the course of research into talkback radio audiences. It reveals that community radio stations and programs provide migrant communities with a space in which they can discuss and negotiate their civic and social rights and responsibilities. Drawing on the reflections of audience members who listen to and call specific radio programs, this article explores the under-examined but vital role performed by these stations and programs in the social and civic lives of immigrants. It reveals that ethnic community radio programs are helping some audience members to formulate notions of good citizenship, and thus engage with democratic processes, which is vital to feeling socially included. The research reveals immigrants are using community radio proactively to reach out to and connect with the broader Australian community, while also reminding themselves of their homeland, culture and language. However, this article warns that researchers have largely focused on the ‘good news story’ of community broadcasting and suggests that a more critical approach to future research is warranted.

This study challenges whether the television (TV) news story has changed due to the advancement in technologies and adaption of production methods from a Fordist to a post-Fordist routine. Textual analysis of 40 years of producing the “news package” appears to reveal minimal changes to the length and framework; however, there seems to be significant changes to the “genetic” construction. While at first, the changes appear to be driven by technology, it may be reasonable to question whether or not technological advancement is responsible. This essay looks at the construction of a TV news story from a microlevel of production as well as examines possible causes for the progressive alterations.