Fuzzy Linkography: Automatic Graphical Summarization of Creative Activity Traces

TL;DR

Fuzzy linkography automates the creation of linkographs from creative activity traces using a fuzzy semantic similarity model, enabling scalable analysis of design moves across diverse creative processes.

Contribution

This paper introduces fuzzy linkography, a novel automated method for constructing linkographs, reducing manual effort and broadening application scope in creative activity analysis.

Findings

Successfully applied to text-to-image prompting journeys

Effective in analyzing LLM-supported ideation sessions

Applicable to researcher publication histories

Abstract

Linkography -- the analysis of links between the design moves that make up an episode of creative ideation or design -- can be used for both visual and quantitative assessment of creative activity traces. Traditional linkography, however, is time-consuming, requiring a human coder to manually annotate both the design moves within an episode and the connections between them. As a result, linkography has not yet been much applied at scale. To address this limitation, we introduce fuzzy linkography: a means of automatically constructing a linkograph from a sequence of recorded design moves via a "fuzzy" computational model of semantic similarity, enabling wider deployment and new applications of linkographic techniques. We apply fuzzy linkography to three markedly different kinds of creative activity traces (text-to-image prompting journeys, LLM-supported ideation sessions, and researcher publication histories) and discuss our findings, as well as strengths, limitations, and potential future applications of our approach.