ABSTRACT
Research in visualization often revolves around visualizing information. However, visualization is a process that extends over time from initial exploration to hypothesis confirmation, and even to result presentation. It is rare that the final phases of visualization are solely about information. In this paper we present a more biased kind of visualization, in which there is a message or set of assumptions behind the presentation that is of interest to both the presenter and the viewer, and emphasizes points that the presenter wants to convey to the viewer. This kind of persuasive visualization -- presenting data in a way that emphasizes a point or message -- is not only common in visualization, but also often expected by the viewer. Persuasive visualization is implicit in the deliberate emphasis on interestingness and also in the deliberate use of graphical elements that are processed preattentively by the human visual system, which automatically groups these elements and guiding attention so that they "stand out". We discuss how these ideas have been implemented in the Morpherspective system for automated generation of information graphics.
- Bertin, J. (trans. by Berg, W.J.) 1983. Semiology of Graphics, The University of Wisconsin Press Google ScholarDigital Library
- Casner, S.M. 1991. A Task-Analytic Approach to the Automated Design of Graphic Presentations. ACM Transactions on Graphics, 10(2), ACM, 111--151 Google ScholarDigital Library
- Chih, C.H. 2006. Fluid Hierarchies: Automated Generation of Emphatic Information Graphics, Ph.D. Thesis, UCLA Google ScholarDigital Library
- Cialdini, R.B. 1993. Influence: the Psychology of Persuasion, William MorrowGoogle Scholar
- Fasciano, M. and Lapalme, G. 1996. PostGraphe: a System for the Generation of Statistical Graphics and Text. Proceedings of the 8th International Workshop on Natural Language Generation (INLG-96), 51--60Google Scholar
- Fasciano, M. and Lapalme, G. 2000. Intentions in the Coordinated Generation of Graphics and Text from Tabular Data. Knowledge and Information Systems, 2(3), Springer-Verlag, 310--39 Google ScholarDigital Library
- Fogg, B.J. 1994. Persuasive Technology, Morgan KaufmannGoogle Scholar
- Fujishiro, I., Ichikawa, Y., Furuhata, R., and Takeshima, Y. 2000. GADGET/IV: a Taxonomic Approach to Semi-Automatic Design of Information Visualization Applications Using Modular Visualization Environment. Proceedings of IEEE Visualization 2000, IEEE Computer Society, 77--83 Google ScholarDigital Library
- Hilderman, R.J. and Hamilton, H.J. 2000. Principles for Mining Summaries Using Objective Measures of Interestingness. Proceedings 12th IEEE International Conference on Tools in Artificial Intelligence, IEEE, 72--81 Google ScholarDigital Library
- Huff, D. 1993. How to Lie with Statistics, W.W. Norton and Company Google ScholarDigital Library
- Jones, G.E. 1994. How to Lie with Charts, Authors Choice Press Google ScholarDigital Library
- Keim, D.A. 1997. Visual Techniques for Exploring Databases. Invited Tutorial in International Conference on Knowledge Discovery in Databases (KDD '97)Google Scholar
- Kleinberg, J. and Papadimitriou, C., Raghavan, P. 1998. A Microeconomic View of Data Mining. Data Mining and Knowledge Discovery, 2, 311--324 Google ScholarDigital Library
- Kosslyn, S.M. 1993. Elements of Graph Design, W.H. Freeman & CompanyGoogle Scholar
- Mackinlay, J.D. 1986. Automating the Design of Graphical Presentations of Relational Information. ACM Transactions on Graphics, 5(2), ACM, 110--141 Google ScholarDigital Library
- Mackinlay, J.D. 1986. Automatic Design of Graphical Presentations, Ph.D. Thesis, Stanford University, 1986 Google ScholarDigital Library
- Monmonier, M. 1996. How to Lie with Maps, The University of Chicago PressGoogle Scholar
- Padmanabhan, B. and Tuzhilin, A. 1999. Unexpectedness as a Measure of Interestingness in Knowledge Discovery. Decision Support Systems, 27(3), Elsevier, 303--318 Google ScholarDigital Library
- Robinson, A. H. 1967. The thematic maps of Charles Joseph Minard. Imago Mundi, 21:95--108Google ScholarCross Ref
- Roth, S.F., Kolojejchick, J., Mattis, J., and Goldstein, J. 1994. Interactive Graphic Design Using Automatic Presentation Knowledge. CHI '94 Conference Proceedings, ACM, 112--117, 476 Google ScholarDigital Library
- Roth, S.F. and Mattis, J. 1990. Data Characterization for Intelligent Graphics Presentation. CHI '90 Conference Proceedings, ACM, 193--200 Google ScholarDigital Library
- Roth, S.F. and Mattis, J. 1991. Automating the Presentation of Information. Proceedings. Seventh IEEE Conference on Artificial Intelligence Applications 1991, IEEE Computer Society Press, 90--97Google ScholarCross Ref
- The SAGE Visualization Group, http://www.cs.cmu.edu/~sage/Google Scholar
- Silberschatz, A. and Tuzhilin, A. 1996. What Makes Patterns Interesting in Knowledge Discovery Systems. IEEE Transactions on Knowledge and Data Engineering, 8(6), IEEE, 970--974 Google ScholarDigital Library
- Simon, H. A. 1971. Designing Organizations for an Information-Rich World, The Johns Hopkins PressGoogle Scholar
- Simon, H. A. 1996. The Sciences of the Artificial (3rd ed.), The MIT Press Google ScholarDigital Library
- Tufte, E.R. 2001. The Visual Display of Quantitative Information (2nd edition), Graphics Press Google ScholarDigital Library
- Tufte, E.R. 1990. Envisioning Information, Graphics Press Google ScholarDigital Library
- Tufte, E.R. 1997. Visual Explanations, Graphics PressGoogle Scholar
- Ware, C. 2004. Information Visualization: Perception for Design, Morgan Kaufmann Google ScholarDigital Library
- Wilkinson, L. 1999. The Grammar of Graphics, Springer-Verlag Google ScholarDigital Library
- Zhou, M.X. and Feiner, S.K. 1996. Data Characterization for Automatically Visualizing Heterogeneous Data. Proceedings, IEEE Symposium on Information Visualization 1996, IEEE Computer Society Press, 13--20, 117 Google ScholarDigital Library
- Zhou, M.X. and Feiner, S.K. 1998. Automated Visual Presentation: From Heterogeneous Information to Coherent Visual Discourse. Journal of Intelligent Information Systems, 11(3), Kluwer Academic Publishers, 205--234 Google ScholarDigital Library
Index Terms
- The persuasive phase of visualization
Recommendations
Metaphoric Transfer Effect in Information Visualization Using Glyphs
VINCI '15: Proceedings of the 8th International Symposium on Visual Information Communication and InteractionMetaphor is the underlying mechanism of information communication. Although metaphors are ubiquitous in information visualization designs, different connotations influence users' information processing dissimilarly. However, visual metaphors imply ...
A survey, classification and analysis of perceptual concepts and their application for the effective visualisation of complex information
APVis '04: Proceedings of the 2004 Australasian symposium on Information Visualisation - Volume 35Information visualisation has become increasingly important in science, engineering and commerce as a tool to convey and explore complex sets of information. This paper introduces a visualisation schema which uses visual attributes as the principle ...
Comments