Peter Organisciak

Associate Professor, Research Methods and Information Science, University of Denver

I work on creativity and AI, as well as massive-scale text analysis. I'm on research sabbatical until September 2024, building new and interesting things.

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

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Artificial data can address class imbalance in digital library classifiers.

We seek to identify whole-part relationships between books, such as when one story is published in another anthology. This type of relationship is hard to infer from cataloguing metadata, but we find that constructing artificial books can teach a deep neural network classifier what the relationship looks like. Read the chapter

Research access over sensitive or restricted texts can be encouraged through non-expressive distribution strategies.

Text analysis in the digital humanities is challenged by legal hurdles, which make it difficult to access and especially to redistribute datasets of modern texts. We explore principles of non-expressive and non-consumptive access as one solution to enabling research access to sensitive texts. Read the chapter

Writing

See my papers on Google Scholar. I once wrote about crowds and text at Sense and Sentences.

Consulting

Contact me to inquire about creativity and AI, data mining and machine learning assistance. I like playful projects and am based in the Denver area.