How the transformation of social media platforms and user-experience have redefined the entertainment industry
In a little over a decade, competing social media platforms, including YouTube, ...Facebook, Twitter, Instagram, and Snapchat, have given rise to a new creative industry: social media entertainment. Operating at the intersection of the entertainment and interactivity, communication and content industries, social media entertainment creators have harnessed these platforms to generate new kinds of content separate from the century-long model of intellectual property control in the traditional entertainment industry.
Social media entertainment has expanded rapidly and the traditional entertainment industry has been forced to cede significant power and influence to content creators, their fans, and subscribers. Digital platforms have created a natural market for embedded advertising, changing the worlds of marketing and communication in their wake. Combined, these factors have produced new, radically shifting demands on the entertainment industry, posing new challenges for screen regimes, media scholars, industry professionals, content creators, and audiences alike.
Stuart Cunningham and David Craig chronicle the rise of social media entertainment and its impact on media consumption and production. A massive, industry-defining study with insight from over 100 industry insiders, Social Media Entertainment explores the latest transformations in the entertainment industry in this time of digital disruption.
The Kinect sensing devices have been widely used in current Human-Computer Interaction entertainment. A fundamental issue involved is to detect users' motions accurately and quickly. In this paper, ...we tackle it by proposing a linear algorithm, which is augmented by feature interaction. The linear property guarantees its speed whereas feature interaction captures the higher order effect from the data to enhance its accuracy. The Schatten-p norm is leveraged to integrate the main linear effect and the higher order nonlinear effect by mining the correlation between them. The resulted classification model is a desirable combination of speed and accuracy. We propose a novel solution to solve our objective function. Experiments are performed on three public Kinect-based entertainment data sets related to fitness and gaming. The results show that our method has its advantage for motion detection in a real-time Kinect entertaining environment.
IEEE 802.11ax-2019 will replace both IEEE 802.11n-2009 and IEEE 802.11ac-2013 as the next high-throughput WLAN amendment. In this article, we review the expected future WLAN scenarios and use cases ...that justify the push for a new PHY/MAC IEEE 802.11 amendment. After that, we overview a set of new technical features that may be included in the IEEE 802.11ax-2019 amendment, and describe both their advantages and drawbacks. Finally, we discuss some of the network-level functionalities that are required to fully improve the user experience in next-generation WLANs and note their relation with other ongoing IEEE 802.11 amendments.
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