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February 2, 20260 citationsOpen Access

Emotion-Tagged Word Substitution with Capitalization Modulation: A Dual-Mechanism Approach to Fine-Grained Emotional Control in Large Language Model Prompts

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SCSimon Michael CaseA1AEGIS 10

Key Points

  • To develop a dual-mechanism approach for fine-grained emotional control in language model prompts.
  • Introduced a system combining discrete word substitution with continuous capitalization modulation.
  • Present a theoretical framework for emotional control in prompt engineering.
  • Explored applications in multi-agent AI governance systems.
  • Achieved more granular emotional expression compared to traditional methods.
  • Demonstrated practical applications in AI governance.
  • Discussed implications for improved human-AI interaction design.

Abstract

This paper introduces a novel dual-mechanism approach for achieving fine-grained emotional control in Large Language Model (LLM) prompt engineering. The system combines discrete word substitution with continuous capitalization modulation, enabling significantly more granular emotional expression than traditional single-mechanism approaches. We present the theoretical framework, demonstrate practical applications in multi-agent AI governance systems, and discuss implications for human-AI interaction design.

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Cite This Study

Case et al. (2026) studied this question.

synapsesocial.com/papers/6980fdc7c1c9540dea80f6b4https://doi.org/10.5281/zenodo.18409251
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