Abstract
Power relationships express one party's dominance, control, influence, and authority over the other. In this article, and using state-of-the-art AI tools, we show that power relationships can be automatically identified in textual data. Generating thousands of synthetic utterances expressing either dominance or compliance, we trained/ran three models that showed good classification performance. Moreover, using GPT-4, we present a novel method for presenting power asymmetry in conversations and visualizing the dynamics of power relationships over time. This methodology is presented and illustrated by analyzing a case study-The play Pygmalion by George Bernard Show.
Original language | American English |
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Pages (from-to) | 1112-1122 |
Number of pages | 11 |
Journal | Digital Scholarship in the Humanities |
Volume | 39 |
Issue number | 4 |
DOIs | |
State | Published - 1 Dec 2024 |
Keywords
- digital humanities
- GPT-4
- power dynamics
- power relationships
- Pygmalion
All Science Journal Classification (ASJC) codes
- Information Systems
- Language and Linguistics
- Linguistics and Language
- Computer Science Applications