The Experts below are selected from a list of 20952 Experts worldwide ranked by ideXlab platform

Hongfei Yan - One of the best experts on this subject based on the ideXlab platform.

  • ECIR - Comparing twitter and traditional media using topic models
    Lecture Notes in Computer Science, 2011
    Co-Authors: Wayne Xin Zhao, Jing Jiang, Jianshu Weng, Ee-peng Lim, Hongfei Yan
    Abstract:

    Twitter as a new form of social media can potentially contain much useful information, but content analysis on Twitter has not been well studied. In particular, it is not clear whether as an information source Twitter can be simply regarded as a faster News feed that covers mostly the same information as traditional News media. In This paper we empirically compare the content of Twitter with a traditional News Medium, New York Times, using unsupervised topic modeling. We use a Twitter-LDA model to discover topics from a representative sample of the entire Twitter. We then use text mining techniques to compare these Twitter topics with topics from New York Times, taking into consideration topic categories and types. We also study the relation between the proportions of opinionated tweets and retweets and topic categories and types. Our comparisons show interesting and useful findings for downstream IR or DM applications.

John Mcmanus - One of the best experts on this subject based on the ideXlab platform.

Linda Kimmel - One of the best experts on this subject based on the ideXlab platform.

  • adult science learning from local television Newscasts
    Science Communication, 2006
    Co-Authors: Jon D. Miller, Eliene Augenbraun, Julia Schulhof, Linda Kimmel
    Abstract:

    American adults learn about science and health from numerous sources including television. The Pew studies demonstrate that half of American adults watch a local television News show three times a week or more, making local television News the most widely used News Medium. This study examines the impact of a program to increase the use of science and health stories in local Newscasts. The results show substantial story recall and information retention. The analysis suggests that science and health stories in local television Newscasts may either enhance viewers’ existing science/health schemas or foster the development of new schemas for less well-known constructs.

An Nguyen - One of the best experts on this subject based on the ideXlab platform.

  • FACING “THE FABULOUS MONSTER”: The traditional media's fear-driven innovation culture in the development of online News
    Journalism Studies, 2008
    Co-Authors: An Nguyen
    Abstract:

    This paper presents a critical review of the evolution of online News since the 1990s, mapping its development into two stages that are driven by the same factor: the fear-driven defensive innovation culture among traditional media. Being threatened by the penetration of the Internet, traditional media hastily established their online presence in the 1990s but then, under the many uncertainties resulting from this rush online and the urge to defend rather than expand markets, have been reluctant to and/or unable to invest resources into developing an online News artefact which achieves its full potential. Online News has been shoe horned into the same professional and business model that is at odds with its remarkable potential. Industrial developments in 2005 and 2006, however, suggest that as the Internet has established itself as a major News Medium, traditional medianow even more threatened and urged to take actions to make up lost timeare on the verge of a new, more vigorous and rigorous development stage of online News.

  • Online News in Australia: patterns of uses and gratifications
    2005
    Co-Authors: An Nguyen, Elizabeth Ferrier, Mark Western, Susan Mckay
    Abstract:

    Key findings from the first national survey of the current state of play of online News consumption in Australia indicate that (1) the Internet as a News Medium has reached a mainstream status in terms of audience sizes, although its penetration is still within a higher socio-economic segment of the society; (2) many distinctive features of online News have been substantially used and appreciated; and (3) from the perspective of innovation diffusion theory, online News has a notable potential to foster further adoption in the years ahead.

  • The current status and potential development of online News consumption
    2003
    Co-Authors: An Nguyen
    Abstract:

    The author argues that the Internet will become a major News Medium in the years ahead based on a review of current patterns of online News consumption and modelling major structural factors influencing this adoption.

  • The current status and potential development of online News consumption: A structural approach
    First Monday, 2003
    Co-Authors: An Nguyen
    Abstract:

    In reviewing the current pattern of online News consumption across the globe and modelling major structural factors influencing this adoption, the author argues that the Internet, already a very important source of News, will become a major News Medium in the years ahead.

Wayne Xin Zhao - One of the best experts on this subject based on the ideXlab platform.

  • ECIR - Comparing twitter and traditional media using topic models
    Lecture Notes in Computer Science, 2011
    Co-Authors: Wayne Xin Zhao, Jing Jiang, Jianshu Weng, Ee-peng Lim, Hongfei Yan
    Abstract:

    Twitter as a new form of social media can potentially contain much useful information, but content analysis on Twitter has not been well studied. In particular, it is not clear whether as an information source Twitter can be simply regarded as a faster News feed that covers mostly the same information as traditional News media. In This paper we empirically compare the content of Twitter with a traditional News Medium, New York Times, using unsupervised topic modeling. We use a Twitter-LDA model to discover topics from a representative sample of the entire Twitter. We then use text mining techniques to compare these Twitter topics with topics from New York Times, taking into consideration topic categories and types. We also study the relation between the proportions of opinionated tweets and retweets and topic categories and types. Our comparisons show interesting and useful findings for downstream IR or DM applications.