The Community for Technology Leaders
RSS Icon
Subscribe
Issue No.12 - Dec. (2011 vol.17)
pp: 2231-2240
Jessica Hullman , University of Michigan School of Information
Nick Diakopoulos , Rutgers University School of Information and Communication
ABSTRACT
Narrative visualizations combine conventions of communicative and exploratory information visualization to convey an intended story. We demonstrate visualization rhetoric as an analytical framework for understanding how design techniques that prioritize particular interpretations in visualizations that "tell a story" can significantly affect end-user interpretation. We draw a parallel between narrative visualization interpretation and evidence from framing studies in political messaging, decision-making, and literary studies. Devices for understanding the rhetorical nature of narrative information visualizations are presented, informed by the rigorous application of concepts from critical theory, semiotics, journalism, and political theory. We draw attention to how design tactics represent additions or omissions of information at various levels−the data, visual representation, textual annotations, and interactivity−and how visualizations denote and connote phenomena with reference to unstated viewing conventions and codes. Classes of rhetorical techniques identified via a systematic analysis of recent narrative visualizations are presented, and characterized according to their rhetorical contribution to the visualization. We describe how designers and researchers can benefit from the potentially positive aspects of visualization rhetoric in designing engaging, layered narrative visualizations and how our framework can shed light on how a visualization design prioritizes specific interpretations. We identify areas where future inquiry into visualization rhetoric can improve understanding of visualization interpretation.
INDEX TERMS
Rhetoric, narrative visualization, framing effects, semiotics, denotation, connotation.
CITATION
Jessica Hullman, Nick Diakopoulos, "Visualization Rhetoric: Framing Effects in Narrative Visualization", IEEE Transactions on Visualization & Computer Graphics, vol.17, no. 12, pp. 2231-2240, Dec. 2011, doi:10.1109/TVCG.2011.255
REFERENCES
[1] P. B. Andersen, What semiotics can and cannot do for HCI, Knowledge-Based Systems, vol. 14, 2000.
[2] R. Barthes, Image-Music-Text, Hill and Wang, 1978.
[3] S. Bateman, R. L. M, C. Gutwin, A. Genest, D. Mcdine, and C. Brooks, Useful Junk? The Effects of Visual Embellishment on Comprehension and Memorability of Charts, CHI'10, 2010.
[4] J. Bertin, Semiology of Graphics: Diagrams, Networks, Maps, 1st ed. Univ. of Wisconsin Press, 1984.
[5] M. Bloch, A. Cox, J. Craven McGinty, and K. Quealy, “A Peek Into Netflix Queues.” The New York Times, 2010. http://www.nytimes.com/interactive/2010/ 01/10/nyregion20100110-netflix-map.html .
[6] M. Bloch, S. Carter, and A. McLean, “Mapping America: Every City, Every Block.” The New York Times, 2010. http://projects.nytimes.com/census/2010explorer .
[7] I. Bogost, Persuasive Games: The Expressive Power of Videogames, The MIT Press, 2007.
[8] S. K. Card, J. Mackinlay, and B. Shneiderman, Readings in Information Visualization: Using Vision to Think, 1st ed. Morgan Kaufmann, 1999.
[9] J. B. Carroll, Human cognitive abilities: a survey of factor-analytic studies, Cambridge University Press, 1993.
[10] D. Chandler, Semiotics: The Basics, Routledge, 2001.
[11] N. Chinchor and W.A. Pike, The Science of Analytic Reporting. Information Visualization, vol. 8, 2009.
[12] D. Chong and J. N. Druckman, Framing Theory, Ann. Rev. Polit. Sci. vol. 10, 2007.
[13] W. S. Cleveland and R. McGill, Graphical Perception: Theory, Experimentation, and Application to the Development of Graphical Methods, J. of the Amer. Stat. Assoc., vol. 79, no. 387, 1984.
[14] W. S. Cleveland, The Elements of Graphing Data, 2nd ed. Hobart Press, 1994.
[15] C. Conati and H. Maclaren, Exploring the Role of Individual Differences in Information, AVI '08, 2008.
[16] A. Cox, “Budget Forecasts, Compared With Reality”, The New York Times (online), 2010. Available at http://www.nytimes.com/interactive/2010/ 02/02/us/politics20100201-budget-porcupine-graphic.html .
[17] C. S. de Souza, The Semiotic Engineering of Human-Computer Interaction, The MIT Press, 2005.
[18] N. Diakopoulos, F. Kivran-Swaine, and M. Naaman, Playable Data: Characterizing the Design Space of Game-y Infographics, CHI'11, 2011.
[19] J. Henderson and F. Ferreira, The Interface of Language, Vision, and Action: Eye Movements and the Visual World, 1st ed. Psych. Press, 2004.
[20] D. Huff, How to Lie with Statistics, W. W. Norton & Company, 1993.
[21] D. Kahneman, P. Slovic, and A. Tversky, Judgment under Uncertainty: Heuristics and Biases, 1st ed. Cambridge Univ. Press, 1982.
[22] S. M. Kosslyn, Understanding charts and graphs, Appl. Cog. Psych., vol. 3, no. 3, 1989.
[23] B. Kovach and T. Rosenstiel, The Elements of Journalism: What Newspeople Should Know and the Public Should Expect, Rev, upd. ed. Three Rivers Press, 2007.
[24] G. Lakoff, Women, Fire, and Dangerous Things, Univ. of Chicago Press, 1990.
[25] T. Lavin, “How the Recession Changed Us”, The Atlantic, 2010. Available at http://www.theatlantic.com/magazine/archive/ 2011/01/how-the recession-changed-us 8347/
[26] Z. Liu and J. T. Stasko, Mental Models, Visual Reasoning and Interaction in Information Visualization: A Top-down Perspective, IEEE TVCG, vol. 16, no. 6, 2010.
[27] J. Mackinlay, Automating the Design of Graphical Presentations of Relational Information, ACM TOG, vol. 5, 1986.
[28] R.E. Mayer, M. Hegarty, S. Mayer, and J. Campbell, When Static Media Promote Active Learning, J Exp Psych Appl. vol. 11 no. 4, 2005.
[29] D. McCandless, “Poll Dancing: How Accurate are Poll Predictions?” Datablog, 2010. http://www.guardian.co.uk/news/datablog/ 2010/may/06general-election-2010-opinion-polls-information-beautiful#
[30] T. Munzner, A Nested Model for Visualization Design and Validation. IEEE TVCG, vol. 15, no. 6, 2009.
[31] T. E. Nelson and Z. M. Oxley, Issue Framing Effects on Belief Importance and Opinion, J. of Politics, vol. 61, no. 4, 1999.
[32] D. A. Norman, The Invisible Computer: Why Good Products Can Fail, the Personal Computer Is So Complex, and Information Appliances Are the Solution, The MIT Press, 1999.
[33] “Organizational Chart of the Democrats' Health Plan,” The Website of the Republican Majority in Congress, 2009. http://www.gop.gov/resources/library/… house-democrats-health-plan.pdf
[34] R. Palmer, “Do Not Fuck with Graphic Designers,” Flickr, 2009. http://www.flickr.com/photos/robertpalmer 3743826461/
[35] W. E. Saris and P. M. Sniderman, Studies in Public Opinion: Attitudes, Nonattitudes, Measurement Error, and Change, Princeton University Press, 2004.
[36] N. Schwarz, F. Strack, and H.-P. Mai, Assimilation and Contrast Effects in Part-Whole Question Sequences: A Conversational Logic Analysis, The Public Opinion Quart., vol. 55, no. 1, 1991.
[37] N. Schwarz, H.J. Hippler, B. Deutsch, and F. Strack, Response Scales: Effects of Category Range on Reported Behavior and Comparative Judgments, Public Opinion Quart., vol. 49, no. 3, 1985.
[38] E. Segel and J. Heer, Narrative Visualization: Telling Stories with Data, IEEE TVCG, vol. 16, 2010.
[39] M. Skeel, B. Lee, G. Smith, and G. Robertson, Revealing Uncertainty for Information Visualization, AVI '08, 2008.
[40] C.S. Skinner, V.J. Strecher, and H. Hospers, Physicians' recommendations for mammography: do tailored messages make a difference?, Amer. J. of Public Health, vol. 84, no. 1, 1994.
[41] “Speaker Pelosi's National Energy Tax: A Bureaucratic Nightmare,” John Boehner's office via republicanleader.house.gov, 2009. Original removed, available at http://voices.washingtonpost.com/ezra-klein/ 2009/06an_insufficient_respect_for_ch.html .
[42] J. J. Thomas and K. A. Cook, Illuminating the path: The research and development agenda for visual analytics, IEEE Comp. Soc., 2005.
[43] R. Tourangeau, F.G. Conrad, M. P, CouperM.P., C. Redline, and C. Kennedy, The Impact of the Spacing of the Scale Options in a Web Survey, Amer. Assoc. for AAPOR '08, 2008.
[44] E. R. Tufte, Beautiful Evidence, Graphics Press, 2006.
[45] E. R. Tufte, The Visual Display of Quantitative Information, 2nd ed. Graphics Press, 2001.
[46] A. Tversky and D. Kahneman, The Framing of Decisions and the Psychology of Choice, Science, vol. 211, no. 4481, 1981.
[47] “Vehicle Sales,” The Economist, 2010. http://www.economist.com/blogs/dailychart/ 2010/12car_sales.
[48] F. Viegas and M. Wattenberg, Communication-Minded Visualization: A Call to Action, IBM Systems Journal, vol. 45, no. 4, 2006.
[49] F. Viegas, M. Wattenberg, F. van Ham, J. Kriss, and M. McKeon, ManyEyes: a Site for Visualization at Internet Scale. IEEE TVCG, vol. 13, no. 6, 2007.
[50] H. Wainer, Picturing the Uncertain World: How to Understand, Communicate, and Control Uncertainty through Graphical Display. Princeton University Press, 2009.
[51] C. Ware, Visual Thinking: for Design, First Edition. Morgan Kaufmann, 2008.
[52] “When Income Grows, Who Gains?” Economic Policy Institute, 2009. http://www.stateofworkingamerica.org/pages/ interactive#?start=1999&end=2008 .
[53] W. Willett, J. Heer, J. Hellerstein, and M. Agrawala, CommentSpace: Structured Support for Collaborative Visual Analysis, CHI '11, 2011.
[54] J. Zacks and B. Tversky, Bars and lines: a study of graphic communication, Memory & Cognition, vol. 27, no. 6, 1999.
[55] C. Ziemkiewicz and R. Kosara, Embedding Information Visualization Within Visual Representation, Advances in Information and Intelligent Systems, vol. 251, Springer Verlag, 2010
[56] C. Ziemkiewicz and R. Kosara, Preconceptions and individual differences in understanding visual metaphors, EUROVIS, 2009.
18 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool