A computer program was developed in an attempt to differentiate the dreams of males from females. Hypothesized gender predictors were based on previous literature concerning both dream content and written language features. Dream reports from home-collected dream diaries of 100 male (144 dreams) and 100 female (144 dreams) adolescent Anglophones were matched for equal length. They were first...
Scientific study of dreams requires the most objective methods to reliably analyze dream content. In this context, artificial intelligence should prove useful for an automatic and non subjective scoring technique. Past research has utilized word search and emotional affiliation methods, to model and automatically match human judges' scoring of dream report's negative emotional tone. The current...
In a scientific study of dream content, artificial intelligence has been utilized to automatically score dream content. An initial attempt focused on scoring for emotional tone of dream reports. The contribution of this thesis demonstrates methods by which accuracy of such a system can be improved beyond text-mining. It was hypothesized that data extraction based on psychological processes will...