The competing-complementarity engagement of news media with online social media

The rapid growth of online social media networks like Facebook and Twitter is strongly influencing news media to engage with such networks for generating newsworthy content, accessing mass audiences for news consumption and using the platforms for news distribution. While both media’s complement each other as sources of news and information, they also compete against each other as news repositories and are observed vying for the same audiences. We call this phenomenon the competing-complementarity (C-C) engagement. To investigate the C-C relationship we use Fidler’s “mediamorphosis” concept to explain the metamorphosis of news media in the online domain. We make two contributions to Fidler’s concept by offering an additional principle “mass user migration” to address the characteristics of metamorphosis and an additional driver “transcended social engagement” to show the force that propels it. Besides, we also propose four accelerators that influence metamorphosis. Theoretical analysis of news media’s metamorphosis indicates its affinity to online social media. We apply niche and gratification theories to explain complementarity, and displacement effects on media consumption habits to trace competition between both media’s.

Screen Distribution and the New King Kongs of the Online World

Like music and the news media before it, the film and television business is now facing its time of digital disruption. Major changes are being brought about in global online distribution of film and television by new players, such as Google/YouTube, Apple, Amazon, Yahoo!, Facebook, Netflix and Hulu, some of whom massively outrank in size and growth the companies that run film and television today. Content, Hollywood has always asserted, is King. But the power and profitability in screen industries have always resided in distribution. Incumbents in the screen industries tried to control the emerging dynamics of online distribution, but failed. The new, born digital, globally focused, players are developing TV network-like strategies, including commissioning content that has widened the net of what counts as television. Content may be King, but these new players may become the King Kongs of the online world.

Quality based frame selection for face clustering in news video

Clustering identities in a broadcast video is a useful task to aid in video annotation and retrieval. Quality based frame selection is a crucial task in video face clustering, to both improve the clustering performance and reduce the computational cost. We present a frame work that selects the highest quality frames available in a video to cluster the face. This frame selection technique is based on low level and high level features (face symmetry, sharpness, contrast and brightness) to select the highest quality facial images available in a face sequence for clustering. We also consider the temporal distribution of the faces to ensure that selected faces are taken at times distributed throughout the sequence. Normalized feature scores are fused and frames with high quality scores are used in a Local Gabor Binary Pattern Histogram Sequence based face clustering system. We present a news video database to evaluate the clustering system performance. Experiments on the newly created news database show that the proposed method selects the best quality face images in the video sequence, resulting in improved clustering performance.