Researchers have used data from mobile phone accelerometers the tiny sensors tracking phone movement for step-counting and other apps to predict people’s personality traits.
RMIT University computer scientist Associate Professor Flora Salim said previous studies had predicted personality types using phone call and messaging activity logs, but this study showed adding accelerometer data improved accuracy.
“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 Salim, a leading expert in human mobility data.
Key findings from the study:
- People with consistent movements on weekday evenings were generally more introverted, while extroverts displayed more random patterns, perhaps meeting up with different people and taking up unplanned options.
- Agreeable people had more random activity patterns and were busier on weekends and weekday evenings than others.
- Friendly and compassionate females made more outgoing calls than anyone else.
- Conscientious, organized people didn’t tend to contact the same person often in a short space of time.
- Sensitive or neurotic females often checked their phones or moved with their phones regularly well into the night, past midnight. Sensitive or neurotic males did the opposite.
- More inventive and curious people tended to make and receive fewer phone calls compared to others.
The results were analysed in accordance with the Big Five personality traits, which are:
- Extraversion: how energetic, sociable and talkative you are.
- Openness: how curious and inventive you are.
- Agreeableness: how friendly and compassionate, rather than suspicious and hostile, you are to others.
- Conscientiousness: how organized, efficient and careful you are.
- Neuroticism: how nervous and sensitive, rather than confident and secure, you are.
The study was conducted on a public dataset gathered from participants. As findings may vary in a different group, the team will next collect data from Australian participants to prove the effectiveness of their research.