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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.

The Watson Personality Insights service uses linguistic analytics to extract a spectrum of cognitive and social characteristics from the text data that a person generates through blogs, tweets, forum posts, and more. "

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.

Could "programmatic" technology used in online advertising also be used to automate and personalize the distribution of cultural and editorial content?

"Time is over for shared experiences when watching TV. Based on the answers you give in an app, your listening history, gender, age, or location and time of the day, this video will adjust the story based on your personality taking your mood into account. Two people won't be watching a story unfolding in the same way again and even you might experience a different narrative at another time."

The edit decision list (EDL) system allows you to automatically skip or mute sections of videos during playback, based on a movie specific EDL configuration file. This is useful for those who may want to watch a film in "family-friendly" mode. You can cut out any violence, profanity, Jar-Jar Binks .. from a movie according to your own personal preferences. Aside from this, there are other uses, like automatically skipping over commercials in video files you watch. The EDL file format is pretty bare-bones. There is one command per line that indicates what to do (skip/mute) and when to do it (using pts in seconds).

Help fund the sequel to one of the scariest films in history, the personalized 'Take This Lollipop' experience.

Called EmotionScan, the online feature linking facial expression to personal finance management skills was developed by the Bank of New Zealand in partnership with a psychologist, Dr Stuart Carr, and Swiss emotion software firm nViso.

"I gave them an insight into my personality. They gave me a menu to match my tastes."

Creating a computer "personality" is as much an art as it is a science, and it's a challenge that more and more software designers are grappling with.

Personality via your music collection

From the narrative to the color grading and score.

"Interactive video, personalization and advanced analytics. For all your videos."

"Time is over for shared experiences when watching TV. Based on the answers you give in an app, this video will adjust the story based on your personality and even your mood. Two people won't be watching the same again. "

An adaptive story that takes you on a road trip, as well a personal journey.

Personalised childrens books