The Intergroup Bias in the Effects of Facial Feedback on the Recognition of Micro-expressions

Micro-expression is the facial expression that is extremely quick and lasts less than half a second. As a spontaneous expression, it is usually produced when people try to suppress their emotions and can reveal the true emotions of human beings. It plays an important role in lie detection. In recent years, with the progress of neural network technology, the research on micro-expression recognition has made significant progress. However, because our understanding of the psychological process of micro-expression recognition is far from complete, the existing method of recognizing micro-expression still cannot meet the standard of practical application. In the present research, we investigated the effects of facial feedback and social identity of the expresser on the recognition of micro-expressions by one behavioral experiment. The results showed that facial feedback can moderate the intergroup bias in micro-expression recognition, which suggests that humans will imitate other people's facial expressions to different degrees in the recognition of micro-expression. At shorter duration, facial feedback has a stronger effect on the recognition of micro-expression of outgroup members. And at longer duration, facial feedback has a stronger effect on the recognition of micro-expressions of ingroup members. This further suggests that we need to consider the identity of the model and the identity of the coder to obtain more accurate and effective data coding when establishing the micro-expression database.