If you have ever been trading a flurry of text messages with someone and there was an awkward pause, don't assume they are doing some work or have a life, you probably should be suspicious.
An analysis has determined that when people lie in digital messages – texting, social media or instant messaging – they take longer to respond, make more edits and they write shorter responses than usual.
According to Tom Meservy, Brigham Young University professor of information systems and co-author of the paper, humans can detect lies about 54 percent of the time accurately – not much better than a coin flip. It's even harder to tell when someone is lying through a digital message because you can't hear a voice or see an expression. With the many financial, security and personal safety implications of digital deception, he and co-authors set up an experimental instrument that tracked possible cues of online lying.
The researchers created a computer program that carried out online conversations with participants – similar to the experience consumers have with online customer service questions.
More than 100 students from two large universities, one in the southeastern U.S. and one in the southwestern U.S., had conversations with the computer, which asked them 30 questions each.
The participants were told to lie in about half of their responses. The researchers found responses filled with lies took 10 percent longer to create and were edited more than truthful messages.
Meservy says, "Digital conversations are a fertile ground for deception because people can easily conceal their identity and their messages often appear credible. Unfortunately, humans are terrible at detecting deception. We're creating methods to correct that.
"We are starting to identify signs given off by individuals that aren't easily tracked by humans. The potential is that chat-based systems could be created to track deception in real-time."
They cautioned we shouldn't automatically assume someone is lying if they take longer to respond, but the study does provide some general patterns.
Citation: upcoming in ACM Transactions on Management Information Systems, no DOI yet.