A visual scoping review of how knowledge graphs and search engine results page designs represent uncertainty and disagreement

Abstract

Purpose

Informational conflict and uncertainty are common features across a range of sources, topics and tasks. Search engines and their presentation of results via search engine results pages (SERPs) often underpinned by knowledge graphs (KGs) are commonly used across tasks. Yet, it is not clear how search does, or could, represent the informational conflict that exists across and within returned results. The purpose of this paper is to review KG and SERP designs for representation of uncertainty or disagreement.

Design/methodology/approach

The authors address the aim through a systematic analysis of material regarding uncertainty and disagreement in KG and SERP contexts. Specifically, the authors focus on the material representation – user interface design features – that have been developed in the context of uncertainty and disagreement representation for KGs and SERPs.

Findings

Searches identified n = 136 items as relevant, with n = 4 sets of visual materials identified from these for analysis of their design features. Design elements were extracted against sets of design principles, highlighting tensions in the design of such features.

Originality/value

The authors conclude by highlighting two key challenges for interface design and recommending six design principles in representing uncertainty and conflict in SERPs. Given the important role technologies play in mediating information access and learning, addressing the representation of uncertainty and disagreement in the representation of information is crucial.

Citation

Knight, S., Bowdler, I., Ford, H. and Zhou, J. (2024), "A visual scoping review of how knowledge graphs and search engine results page designs represent uncertainty and disagreement", Information and Learning Sciences, Vol. 125 No. 11/12, pp. 1030-1053. https://doi.org/10.1108/ILS-02-2024-0016