Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.
DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.
In everyday life, judgments people make about others are based on brief excerpts of interactions, known as thin slices. Inferences stemming from such minimal information can be quite accurate, and nonverbal behavior plays an important role in the impression formation. Because protagonists are strangers, employment interviews are a case where both nonverbal behavior and thin slices can be predictive of outcomes. In this work, we analyze the predictive validity of thin slices of real job interviews, where slices are defined by the sequence of questions in a structured interview format. We approach this problem from an audio-visual, dyadic, and nonverbal perspective, where sensing, cue extraction, and inference are automated. Our study shows that although nonverbal behavioral cues extracted from thin slices were not as predictive as when extracted from the full interaction, they were still predictive of hirability impressions with R^2 values up to 0.34, which was comparable to the predictive validity of human observers on thin slices. Applicant audio cues were found to yield the most accurate results.