Telegnomics, Ousiometrics, and Archetypometrics
Data-driven, computational determination of the essence of meaning, stories, and characters
Co-sponsored by the Berkeley Institute for Data Science and the School of Information
Part 1
From work emerging through the middle of the 20th century, the essence of meaning has become widely accepted as being described by the three orthogonal dimensions of evaluation, potency, and activation (EPA), which were later recast in the context of emotion as valence, arousal, and dominance (VAD). We define ‘ousiometrics’ to be the study of essential meaning in whatever context that meaningful signals are communicated, and ‘telegnomics’ as the study of remotely sensed knowledge.
By re-examining first types and then tokens for the English language, and through the use of automatically annotated histograms — ‘ousiograms’ — we show that:
- The essence of meaning conveyed by words is instead described by a danger-aggression-power-goodness-structure (DPAGS) framework, and
- Across a disparate collection of large-scale corpora, language exhibits a systematic bias toward safe, low-danger words — revealing the primacy of the minimal power-danger-structure (PDS) framework, as well as the hidden structure underneath the Pollyanna principle’s positivity bias.
We construct and test a prototype ‘ousiometer’, a telegnomic instrument that measures ousiometric time series for temporal corpora.
Part 2
Based on a separate data set, we then show how 2000 characters from over 300 fictional stories remarkably conform to the DPAGS framework.
Through an exhaustive analysis and interpretation process, we uncover 6 primary and 6 secondary base archetypes for fictional characters, which we extend to a framework of single, dual, and triple archetypes. These archetypes encompass real personality traits, and the six major archetypes — fools, heroes, angels, demons, traditionalists, and adventurers — align with the three dimensions of essential meaning — power, danger, and structure. We outline typical character distributions for classes of stories.
Finally, to compare characters and complex entities in general, we develop a sophisticated map-and-list visualization. Together, our ousiometric and archetypometrics frameworks help make plain the building blocks of human stories, and have potential to inform a wide variety of communication across biological and artificial life.
Background Reading
Ousiometrics
“Ousiometrics: The essence of meaning aligns with a power-danger-structure framework
instead of valence-arousal-dominance” by Peter Sheridan Dodds et al.
Archetypometrics
Dodds, P. S., Zimmerman, J. W., Beauregard, C. G., Fehr, A. M. A., Fudolig, M. I., Tangherlini, T. R., & Danforth, C. M. (2025). Archetypometrics, a Pragmateia: Empirical Determination of the Fundamental Archetypes of Fictional Characters. Zenodo. https://doi.org/10.5281/zenodo.17128112
Online explorable card collection | Website
The Cultural Analytics Series is a series of lunchtime talks and workshops highlighting research that focuses on the data-driven analysis of cultural phenomena.
| Time | Event |
|---|---|
| 12:15 pm | Pre-talk lunch |
| 12:30 pm | Talk |
Speaker
Peter Dodds
Peter Dodds is a professor of computer science at the University of Vermont and the director of the Vermont Complex Systems Institute. Peter’s research focuses on system-level, big data problems in many areas including language and stories, sociotechnical systems, Earth sciences, biology, and ecology. Peter has created (and constantly evolves) a series of complex systems courses starting with Principles of Complex Systems. He co-runs the Computational Story Lab.
