Facebook successfully picks depressed patients

Use of more first-person pronouns were one of the indicators

Facebook posts and status updates may reveal more about patients than simply their latest travel destinations.

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By analysing language used on social media, researchers created an algorithm that could predict which users would be diagnosed with depression — three months ahead of their diagnosis.

Mentions of hostility and loneliness, words like "tears" and "feelings", and use of more first-person pronouns were found to be indicators of the condition.

The accuracy of linguistic red flags was comparable to validated self-report depression scales, according to the study in

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