Can you predict schizophrenia by studying language?
An interview with psychology researcher Dr. Neguine Rezaii about her work using machine learning to predict conversion in teenagers from prodromal symptoms to psychotic episodes. The two language patterns found in the subjects' speech were 1) a low semantic density (i.e., low meaning), and 2) speech related to sound or voices. Topics: psychology, schizophrenia, machine learning, language, psychosis. Support the showTo get ad-free episodes, and more, get a premium subscription. To learn more about the show, go to behavior-podcast.com. I'm on Twitter at @apokerplayer. See a summary of my work.
People Who Read People: A Behavior and Psychology Podcast
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Show Notes
An interview with psychology researcher Neguine Rezaii about her work using machine learning to predict conversion in teenagers from prodromal symptoms to psychotic episodes. The two language patterns found in the subjects' speech were 1) a low semantic density (i.e., little meaning), and 2) speech related to sound or voices. Topics discussed include: how exactly they determined “low meaning"; how the algorithm found, on its own, indicators related to sound-related speech content; the future of using machine learning and automatic diagnosis tools in psychology and therapy; theories that might help explain these findings.
Learn more about the show and get transcripts at behavior-podcast.com.
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