Researchers track phone movements to predict personality traits

In a first, researchers have used our smartphones and their movement tracking sensors in order to predict our personality traits.

Scientists from RMIT University in Australia used data from our phones’ accelerometer sensors that track our movements throughout the day for step-counting and similar apps, and predicted five personality traits of the phone owner.

“Activity like how quickly or how far we walk, or when we pick up our phones up during the night, often follows patterns and these patterns say a lot about our personality type,” said one of the researchers Flora Salim.

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As per Science Alert, the team analyzed 52 people’s phone habits for over a year. Each participant was given a phone with sensing and collection software on it that gave the team the accelerometer data on when and how much the phone was moving.

The number and time of days of all calls and messages were also tracked and the participants also filled out a Big Five survey to score their personalities. The results were analyzed based on the Big Five personality traits, which include extraversion, openness, agreeableness, conscientiousness, and neuroticism, as per Science Daily.

The team discovered from the study that people with regular movements on weekday evenings were usually more introverted, while extroverts showed random patterns. Agreeable people too had more random activity patterns and were busier on weekends and weekday evenings than others. Inventive and curious people made and received fewer calls as compared to others.

Also, friendly and compassionate females made more outgoing calls than others, whereas conscientious, organized people tend not to contact the same person often in a short space of time. Sensitive or neurotic females often checked or moved with their phones regularly well into the night, past midnight, whereas sensitive or neurotic males did the opposite.

Talking about the applications for the research, lead author Nan Gao said, “There are applications for this technology in social media with friend recommendations, online dating matches and targeted advertising, but I think the most exciting part is what we can learn about ourselves.”