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Soon, An Online Polygraph Will Spot Liars on Social Media


Some smart folks are developing an online algorithm a sort of polygraph that could spot liars from the words they write on internet dating profiles, Facebook messages or Twitter posts.

It is tricky enough to id The study, published in ‘Computers in Human Behavior’, detailed the findings of an online game that she created to measure truthful and deceptive communications between two people.

The system parsed the words in those conversations, hoping to extract context from millions of bits of data in many messages — described as language-action cues — just as people get context from seeing physical cues that indicate if someone is telling the truth or lying.

The experiments revealed a person could spot lies in messages about 50% of the time, while a machine-learning approach could identify deception with an accuracy rate ranging from 85 to 100%.
Researchers created an online game designed to identify language cues that unmask deceivers and truthtellers.

The game randomly assigned players to play the roles of “The Saint” and “The Sinner”. As sinners and saints interacted via computers, researchers captured the conversations and used machine learning to scrutinise patterns of words and writing.

Some fascinating language tendencies emerged from that analysis. The lying sinners were found to be less expressive, but they used more decorative words per message.

They displayed more negative emotions and appeared more anxious when they communicated with truthtellers. Deceivers also took less time to respond and used more words of insight, such as “think” and “know”, and they tended to use more words of certainty, including “always” or “never”
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Conversely, truthtellers used more words of speculation, such as “perhaps” and “guess”, and they took longer to respond to inquiries. They expressed more reflective thinking with words like “should” and “could”.
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Researchers also calculated time lags between every sentence, and even parts of a sentence, by placing time stamps on the words. That precise breakdown clearly showed how much a person paused during interactions — another language-action cue.
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