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reviews Azimi says they started from a point that had already been well established by previous studies, that we humans are generally not good at detecting deception. And that's when we're face-to-face with each other. Trying to tell when we're being conned is even more difficult when we're using text. The study used a dataset of 1600 reviews of Chicago hotels. Some of them were real; others were fake. The reviews were presented to 400 subjects: each subject got eight reviews to read: a balanced set of two positive fake, two positive real, two negative fake and two negative real, presented in a random order. The reviews were written by real people who were given information about the hotel and told to work it into the review. The characteristics of the con Azimi, Chan and Krasnikov's study suggests that we're no better with text than we are in person, although the liar's tools may be different when he or she is writing, as opposed to talking. When it came to faking a review, length was important to believability, as was detail. A long, negative review of a hotel, complete with lots of information, tended to convince participants. A lengthy, positive review, on the other hand, was regarded as suspicious, and participants tended to trust writers that kept their glowing reviews short. Finally, the study authors wanted to see whether there was a certain type of person that was more susceptible, or more capable of detecting fakes. So they selected participants that conformed to the Big Five personality types: extroversion, agreeableness, openness, conscientiousness and neuroticism. It turns out that people who display openness, and tend to be adventurous and intellectually curious, are better at spotting fake reviews than other personality types. Extroverted people, on the other hand, tend to have a harder time identifying a fake review. The fake reviews written for Azimi's study were put together by humans, but increasingly, fake reviews are being written by machines. In the past, these bogus endorsements or critiques have been relatively easy to spot, but programs like ChatGPT and other neural networks are now being used to generate realistic reviews that can swamp a business's website. high quality imitation bagsreplica designer bags wholesale

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