Can the patterns of mobile phone movement predict someone’s personality type? Scientists say “yes”
05/11/2020 / By Arsenio Toledo / Comments
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Can the patterns of mobile phone movement predict someone’s personality type? Scientists say “yes”

Researchers from Australia’s RMIT University have found that the way a person moves their phone around may be able to predict what kind of personality they have.

The researchers did this by using mobile phone accelerometers, or tiny sensors that can track a phone’s movements. According to study co-author Flora Salim, a computer scientist and expert in human mobility data at RMIT, the study builds off of earlier works that predicted personality types using messaging activity and phone call logs, improving accuracy by adding the accelerometer data.

“Activity like how quickly or how far we walk, or when we pick up our phones during the night, often follows patterns and these patterns say a lot about our personality type,” she added.

Previous studies done on the subject have shown that there is a correlation between physical activity and human personality. Using this, Salim and her team analyzed the physical activity of the participants from different dimensions, such as regularity, diversity and dispersion of the physical activity.

Phone movements good indicators for some personality traits

Salim and her team analyzed the phone habits of 52 people between March 2010 and July 2011. The researchers provided each participant with a mobile phone with pre-installed software that allowed the researchers to gather information on when and how much the participants moved it. The software also tracked how many times the phone was used to give and receive calls and text messages.

The participants were also asked to complete a personality test. The researchers chose to align with the “Big Five” personality traits that have been used by psychology since the 1980s as a way of classifying five “dominant parts” of a person’s personality.

  • Openness – How curious or how cautious a person is.
  • Conscientiousness – How organized and efficient or easy-going and laid back a person is.
  • Extraversion – How outgoing or reserved a person is.
  • Agreeableness – How empathetic and compassionate or suspicious and detached a person is.
  • Neuroticism – How confident and secure or nervous and sensitive a person is.

Afterward, the team created a list of activities related to phone activity that they believed might be able to determine personality traits. For example, they argued that physical activity on weekend nights might be a good way to predict a person’s extraversion score, and the number of calls a person makes might be able to predict agreeableness. (Related: Creative people are vastly more aware and observant than everyone else, noticing things in the world around them that other people miss.)

After the team collated relevant data, they found that phone movements were, in fact, able to determine some personality traits. Particularly, the phone data was good at predicting a person’s conscientiousness, extraversion and neuroticism. The phone logs, however, weren’t as useful at predicting openness and agreeableness.

People who were more conscientious were less likely to contact the same person in a short amount of time. More introverted people, on the other hand, had similar phone movement patterns, especially on weekday evenings. Extroverted people had more random patterns. Meanwhile, sensitive females were more likely to check their phones well into the night.

Nan Gao, a doctorate student at RMIT and lead author of the study, said that the potential applications of their research were very exciting.

“Many of our habits and behaviors are unconscious but, when analyzed, they tell us a lot about who we really are so we can understand ourselves better, resist social pressure to conform and to empathize with others,” said Gao. “Most importantly, being who we truly are can make our experience of life richer, more exciting and more meaningful.”

Sources include:

ScienceDaily.com

ScienceAlert.com

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