| Abstrakt: |
Researchers at Purdue University have conducted a study on the effects of gender, age, and blindness on word usage in dreams. Using automatic content analysis software, they found that differences in these characteristics are associated with different frequencies of word usage in dream reports. The study concluded that machine learning techniques can accurately predict binary characteristics of dreamers based on the content of their dreams. This research has been peer-reviewed and provides valuable insights into the relationship between waking life and dreaming. [Extracted from the article] |
