Whether we like it or not, deception occurs everyday and everywhere: thousands of trials take place daily around the world; little white lies: "I'm busy that day!" even if your calendar is blank; news "with a twist" (a.k.a. fake news) meant to attract the readers attention or influence people in their future undertakings; misinformation in health social media posts; portrayed identities, on dating sites and elsewhere. Can a computer automatically detect deception in written accounts or in video recordings? In this talk, I will overview a decade of research in building linguistic and multimodal resources and algorithms for deception detection, targeting deceptive statements, trial videos, fake news, identity deception, and health misinformation. I will also show how these algorithms can provide insights into what makes a good lie - and thus teach us how we can spot a liar. As it turns out, computers can be trained to identify lies in many different contexts, and they can often do it better than humans do.
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