From Digital Humanities to Quantum Humanities: Potentials and Applications

TL;DR

This paper explores the potential of quantum computers in digital humanities research, demonstrating how quantum-enhanced data analysis can benefit humanities data processing through a media science case study.

Contribution

It introduces a quantum computing-based data analysis pipeline for digital humanities, combining classical and quantum methods for data preparation, feature engineering, clustering, and classification.

Findings

Quantum computers can enhance humanities data analysis.

A hybrid classical-quantum pipeline is feasible for digital humanities.

Potential improvements in processing large humanities datasets.

Abstract

Quantum computers are becoming real. Therefore, it is promising to use their potentials in different applications areas, which includes research in the humanities. Due to an increasing amount of data that needs to be processed in the digital humanities the use of quantum computers can contribute to this research area. To give an impression on how beneficial such involvement of quantum computers can be when analyzing data from the humanities, a use case from the media science is presented. Therefore, both the theoretical basis and the tooling support for analyzing the data from our digital humanities project MUSE is described. This includes a data analysis pipeline, containing e.g. various approaches for data preparation, feature engineering, clustering, and classification where several steps can be realized classically, but also supported by quantum computers.