The Attraction Effect in Information Visualization

The attraction effect is a well-studied cognitive bias in decision making research, where one's choice between two alternatives is influenced by the presence of an irrelevant (dominated) third alternative. We examine whether this cognitive bias, so far only tested with three alternatives and si...

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Vydáno v:IEEE transactions on visualization and computer graphics Ročník 23; číslo 1; s. 471 - 480
Hlavní autoři: Dimara, Evanthia, Bezerianos, Anastasia, Dragicevic, Pierre
Médium: Journal Article
Jazyk:angličtina
Vydáno: United States IEEE 01.01.2017
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Institute of Electrical and Electronics Engineers
Témata:
Alternatives
asymmetric dominance effect
Attraction
attraction effect
Bias
Cognition
cognitive bias
Cognitive science
Companies
Computer Science
Data visualization
Decision making
decoy effect
Education
Human-Computer Interaction
Information visualization
Scientific visualization
Uncertainty
Visualization
attraction effect
decoy effect
Index Terms—Information visualization
asymmetric dominance effect
cognitive bias
decision-making
ISSN:1077-2626, 1941-0506
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Popis
Shrnutí:The attraction effect is a well-studied cognitive bias in decision making research, where one's choice between two alternatives is influenced by the presence of an irrelevant (dominated) third alternative. We examine whether this cognitive bias, so far only tested with three alternatives and simple presentation formats such as numerical tables, text and pictures, also appears in visualizations. Since visualizations can be used to support decision making - e.g., when choosing a house to buy or an employee to hire - a systematic bias could have important implications. In a first crowdsource experiment, we indeed partially replicated the attraction effect with three alternatives presented as a numerical table, and observed similar effects when they were presented as a scatterplot. In a second experiment, we investigated if the effect extends to larger sets of alternatives, where the number of alternatives is too large for numerical tables to be practical. Our findings indicate that the bias persists for larger sets of alternatives presented as scatterplots. We discuss implications for future research on how to further study and possibly alleviate the attraction effect.
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ISSN:1077-2626
1941-0506
DOI:10.1109/TVCG.2016.2598594