Researchers at Telefonica Research in Spain have developed an algorithm that enables a smartphone to determine whether or not its user is bored.
The algorithm is designed to look at the mobile activity of the user and consider factors such as the last time the user had a call or text, the time of day, and the level of smartphone use. Such data provides a reliable prediction of boredom 83 percent of the time, according to the researchers.
Using machine learning to infer the state of mind of people, and doing so reliably via a smartphone, could be powerful. For example, an app could predict the user is bored, know the location of the user, and then try to provide content it thinks the user would like in that particular context.
The researchers determined characteristics of boredom using an Android app to ask study participants to rate their level of boredom several times a day over two weeks; the responses were compared with other data captured from the phones. To validate the algorithm, researchers developed another Android app that inferred on its own whether the user was bored and, when it did, sent an alert to their phone asking if they wanted to read an article on BuzzFeed's news app.
The researchers plan to present their work at the ACM UbiComp2015 ubiquitous computing conference in Japan next week.
From Technology Review
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