Anchored in a Data Storm: How Anchoring Bias Can Affect User Strategy, Confidence, and Decisions in Visual Analytics

Cognitive biases have been shown to lead to faulty decision-making. Recent research has demonstrated that the effect of cognitive biases, anchoring bias in particular, transfers to information visualization and visual analytics. However, it is still unclear how users of visual interfaces can be anchored and the impact of anchoring on user performance and decision-making process. To investigate, we performed two rounds of between-subjects, in-laboratory experiments with 94 participants to analyze the effect of visual anchors and strategy cues in decision-making with a visual analytic system that employs coordinated multiple view design. The decision-making task is identifying misinformation from Twitter news accounts. Participants were randomly assigned one of three treatment groups (including control) in which participant training processes were modified. Our findings reveal that strategy cues and visual anchors (scenario videos) can significantly affect user activity, speed, confidence, and, under certain circumstances, accuracy. We discuss the implications of our experiment results on training users how to use a newly developed visual interface. We call for more careful consideration into how visualization designers and researchers train users to avoid unintentionally anchoring users and thus affecting the end result.

[1]  Jay Pratt,et al.  Confirmation bias in visual search. , 2015, Journal of experimental psychology. Human perception and performance.

[2]  Daniel A. Keim,et al.  Information Visualization and Visual Data Mining , 2002, IEEE Trans. Vis. Comput. Graph..

[3]  Jonathan Sidi,et al.  heatmaply: an R package for creating interactive cluster heatmaps for online publishing , 2017, Bioinform..

[4]  Tamara Munzner,et al.  Visualization Analysis and Design , 2014, A.K. Peters visualization series.

[5]  Sandra González-Bailón,et al.  Bit by bit: social research in the digital age , 2019, The Journal of Mathematical Sociology.

[6]  Cedric E. Ginestet ggplot2: Elegant Graphics for Data Analysis , 2011 .

[7]  Isaac Cho,et al.  The Anchoring Effect in Decision-Making with Visual Analytics , 2017, 2017 IEEE Conference on Visual Analytics Science and Technology (VAST).

[8]  William Ribarsky,et al.  CrystalBall: A Visual Analytic System for Future Event Discovery and Analysis from Social Media Data , 2017, 2017 IEEE Conference on Visual Analytics Science and Technology (VAST).

[9]  Sylvia Pantaleo Warning , 1933 .

[10]  André Calero Valdez,et al.  Priming and Anchoring Effects in Visualization , 2018, IEEE Transactions on Visualization and Computer Graphics.

[11]  David G. Rand,et al.  Crowdsourcing Judgments of News Source Quality , 2018 .

[12]  Sinan Aral,et al.  The spread of true and false news online , 2018, Science.

[13]  Tobias Isenberg,et al.  A Systematic Review on the Practice of Evaluating Visualization , 2013, IEEE Transactions on Visualization and Computer Graphics.

[14]  D. Kahneman,et al.  Heuristics and Biases: The Psychology of Intuitive Judgment , 2002 .

[15]  John R. Geddes,et al.  Positive Imagery-Based Cognitive Bias Modification as a Web-Based Treatment Tool for Depressed Adults , 2015, Clinical psychological science : a journal of the Association for Psychological Science.

[16]  Fionn Murtagh,et al.  Ward’s Hierarchical Agglomerative Clustering Method: Which Algorithms Implement Ward’s Criterion? , 2011, Journal of Classification.

[17]  André Calero Valdez,et al.  A Framework for Studying Biases in Visualization Research , 2017 .

[18]  Suhang Wang,et al.  Fake News Detection on Social Media: A Data Mining Perspective , 2017, SKDD.

[19]  William Wright,et al.  Argument Mapper: Countering Cognitive Biases in Analysis with Critical (Visual) Thinking , 2017, 2017 21st International Conference Information Visualisation (IV).

[20]  M. Sheelagh T. Carpendale,et al.  Empirical Studies in Information Visualization: Seven Scenarios , 2012, IEEE Transactions on Visualization and Computer Graphics.

[21]  Gabriele Piccoli,et al.  Cognitive Anchoring of Color Cues on Online Review Ratings , 2017, AMCIS.

[22]  Tal Galili,et al.  dendextend: an R package for visualizing, adjusting and comparing trees of hierarchical clustering , 2015, Bioinform..

[23]  Tore Ellingsen,et al.  Anchoring and cognitive ability , 2010 .

[24]  Isaac Cho,et al.  Can You Verifi This? Studying Uncertainty and Decision-Making About Misinformation Using Visual Analytics , 2018, ICWSM.

[25]  A. Tversky,et al.  Judgment under Uncertainty: Heuristics and Biases , 1974, Science.

[26]  P. Cochat,et al.  Et al , 2008, Archives de pediatrie : organe officiel de la Societe francaise de pediatrie.

[27]  Svitlana Volkova,et al.  Separating Facts from Fiction: Linguistic Models to Classify Suspicious and Trusted News Posts on Twitter , 2017, ACL.

[28]  David G. Rand,et al.  Implausibility and Illusory Truth: Prior Exposure Increases Perceived Accuracy of Fake News but Has No Effect on Entirely Implausible Statements , 2017 .

[29]  Adam Loy,et al.  Model Choice and Diagnostics for Linear Mixed-Effects Models Using Statistics on Street Corners , 2015, 1502.06988.

[30]  Alex Endert,et al.  Warning, Bias May Occur: A Proposed Approach to Detecting Cognitive Bias in Interactive Visual Analytics , 2017, 2017 IEEE Conference on Visual Analytics Science and Technology (VAST).

[31]  Miriam J. Metzger,et al.  The science of fake news , 2018, Science.

[32]  Keith Andrews Evaluation Comes in Many Guises , 2008 .

[33]  Susan Athey,et al.  The Econometrics of Randomized Experiments , 2016, 1607.00698.

[34]  Eric McManama,et al.  Manual anchoring biases in slant estimation affect matches even for near surfaces , 2015, Psychonomic bulletin & review.

[35]  Noah D. Goodman,et al.  The anchoring bias reflects rational use of cognitive resources , 2018, Psychonomic bulletin & review.

[36]  Catherine Plaisant,et al.  The challenge of information visualization evaluation , 2004, AVI.

[37]  Jay Pratt,et al.  Biasing spatial attention with semantic information: an event coding approach , 2018, Psychological research.

[38]  Daniel A. Keim,et al.  The Role of Uncertainty, Awareness, and Trust in Visual Analytics , 2016, IEEE Transactions on Visualization and Computer Graphics.

[39]  Alan Dix,et al.  Decision Making Under Uncertainty in Visualisation , 2015 .