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Other literature type . 2026
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Research . 2026
License: CC BY SA
Data sources: Datacite
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Research . 2026
License: CC BY SA
Data sources: Datacite
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Emotion-Tagged Word Substitution with Capitalization Modulation: A Dual-Mechanism Approach to Fine-Grained Emotional Control in Large Language Model Prompts

Authors: Case, Simon Michael; 10, AEGIS;

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

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.

Keywords

LLM prompt engineering, emotion tagging, word substitution, multi-agent systems, capitalization modulation, AI governance

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green