SymbolFinder: Brainstorming Diverse Symbols Using Local Semantic Networks

Описание: SymbolFinder: Brainstorming Diverse Symbols Using Local Semantic Networks
Savvas Petridis, Hijung Valentina Shin, Lydia B Chilton

UIST'21: ACM Symposium on User Interface Software and Technology
Session: Summarization & Semantics

Abstract
Visual symbols are the building blocks for visual communication. They convey abstract concepts like reform and participation quickly and effectively. When creating graphics with symbols, novice designers often struggle to brainstorm multiple, diverse symbols because they fixate on a few associations instead of broadly exploring different aspects of the concept. We present SymbolFinder, an interactive tool for finding visual symbols for abstract concepts. SymbolFinder molds symbol-finding into a recognition rather than recall task by introducing the user to diverse clusters of words associated with the concept. Users can dive into these clusters to find related, concrete objects that symbolize the concept. We evaluate SymbolFinder with two studies: a comparative user study, demonstrating that SymbolFinder helps novices find more unique symbols for abstract concepts with significantly less effort than a popular image database and a case study demonstrating how SymbolFinder helped design students create visual metaphors for three cover illustrations of news articles.

DOI:: https://doi.org/10.1145/3472749.3474757
WEB:: https://uist.acm.org/uist2021/

Video Previews of the UIST 2021 Technical Papers Program