Peter Organisciak

I'm an information scientist with expertise in text and data mining, machine learning, crowd systems, and information retrieval.

As faculty in Library and Information Science at the University of Denver, I work on massive-scale text analysis, teaching computers to read and using those methods to track cultural and and historic trends across centuries. I also work with educational psychologists on improving automated measurement in education, particularly in the study of creativity.

See my CV, or find me and the Massive Texts Lab on Github.

Check out online tools: Open Creativity Scoring for scoring tests of creativity, SaDDL for digital library book relationships, and HT+Bookworm for exploring historic language trends.

Recent Research

Scoring creativity with Large-Language models greatly improves on state of the art models.

Studying creativity is challenged by the difficulty of measuring and scoring tests of originality. We improved on automated scoring of one common test, the Alternate Uses Task, to a large degree.
Read the preprint or try the system at Open Creativity Scoring




I write about crowds and text at Sense and Sentences.


Contact me to inquire about data mining and machine learning assistance, or just to chat. I'm based in the Denver area.