Given today’s information and sensory overload, capturing someone’s attention is a high commodity. Researchers at Telefonica Research in Barcelona, Spain recognized that peoples’ attention are available when they are bored. And most often, when people are bored, they turn to their cell phones. This is why the researchers developed a machine-based learning model that detects when mobile phone users are bored and pushes content to them.
The researchers identified usage patterns that were indicative of boredom and confirmed the specific behaviors patterns were related. This data was then used to predict patterns of boredom; the predictions were correct 83% of the time. Interestingly, they also noticed the more bored the participants, the more likely time had passed between the participants sending and receiving phone calls, SMS, or notifications. Importantly, users were significantly more likely to open and engage with content pushed to them on their mobile phones when the model predicted them to be bored.
These findings have major implications for future applications in being able to predict when a user is bored couple and knowing a user’s location could provide content in relation to specific context. New apps are already being developed along these lines. As well boredom detection could be a great way for publishers and marketers to know when to push content or messaging for it to be most receptive.