#perceptiveradio

[newdigitalformats]

"Storytelling techniques within traditional broadcast media have not made major advances in recent years due to the linear and relatively rigid approach to narrative despite advances in the technology that delivers the content. This research proposes the concept of ‘perceptive media’ in which the content creators have at their disposal different tools and sensors to allow for the subtle adaption of the narrative without any direct interactions from the audience members. The concept is demonstrated through the creation of a ‘perceptive radio’ that is able to play specially designed content that adapts to the physical and social context in which the radio resides."

[newdigitalformats]

We show that easily accessible digital records of behavior, Facebook Likes, can be used to automatically and accurately predict a range of highly sensitive personal attributes including: sexual orientation, ethnicity, religious and political views, personality traits, intelligence, happiness, use of addictive substances, parental separation, age, and gender. The analysis presented is based on a dataset of over 58,000 volunteers who provided their Facebook Likes, detailed demographic profiles, and the results of several psychometric tests. The proposed model uses dimensionality reduction for preprocessing the Likes data, which are then entered into logistic/linear regression to predict individual psychodemographic profiles from Likes. The model correctly discriminates between homosexual and heterosexual men in 88% of cases, African Americans and Caucasian Americans in 95% of cases, and between Democrat and Republican in 85% of cases. For the personality trait “Openness,” prediction accuracy is close to the test–retest accuracy of a standard personality test. We give examples of associations between attributes and Likes and discuss implications for online personalization and privacy.

[newdigitalformats]

We show that easily accessible digital records of behavior, Facebook Likes, can be used to automatically and accurately predict a range of highly sensitive personal attributes including: sexual orientation, ethnicity, religious and political views, personality traits, intelligence, happiness, use of addictive substances, parental separation, age, and gender.

[newdigitalformats]

"Device and Sensors Working Group is to create client-side APIs that enable the development of Web Applications and Web Widgets that interact with devices hardware, sensors, services and applications such as the camera, microphone, proximity sensors, native address books, calendars and native messaging applications. "