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

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.

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Publication Details

Journal
Information and Learning Sciences
Published
2024-08-12
DOI
https://doi.org/10.1108/ils-02-2024-0016
Citations
2
Primary Topic
Misinformation and Its Impacts
Type
article
Field-Weighted Citation Impact
2.26
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article

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

Heather Ford, Jianlong Zhou, Simon Knight, Isabella Bowdler
2 citations
Information and Learning Sciences
Misinformation and Its Impacts
2.26
article

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

Heather Ford, Jianlong Zhou, Simon Knight, Isabella Bowdler
article en
2 citations

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.

Information and Learning SciencesVol. 125(11/12)
University of Technology Sydney (AU), University College London (GB)
Openalex Percentile: Top 10%
Misinformation and Its Impacts
2.26
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A visual scoping review of how knowledge graphs and search engine results page designs represent uncertainty and disagreement — Heather Ford, Jianlong Zhou, et al. · Information and Learning Sciences (2024) | TGRS Research Map | TGRS