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What makes an What makes a face What makes a vis Beyond Memorability: Visualization Impact image memorable? memorable? memorable? Recognition and Recall Comprehension Borkin, M., Bylinskii, Z., Kim, N.W., Bainbridge C.M., Yeh, C.S.,


  1. What makes an What makes a face What makes a vis Beyond Memorability: Visualization Impact image memorable? memorable? memorable? Recognition and Recall Comprehension Borkin, M., Bylinskii, Z., Kim, N.W., Bainbridge C.M., Yeh, C.S., Borkin, D., Pfister, H., & Oliva, A. Engagement IEEE Transactions on Visualization and Computer Graphics, 2015 Aesthetics vs. vs. vs. Memory Memory Perception Perception Presented by Julieta Martinez 1 2 3 4 Let’s play a game What makes a If you see a repeated visualization, clap visualization memorable? Seriously, get ready to clap 5 6 7 8 9 10 11 12 13 14 15 16

  2. memory check Data likely to be a That’s it. Thanks! false positive attention check 17 18 19 20 Government Infographic “These particular web sites were chosen because each contained a large number of static visualizations that could be automatically scraped without requiring a large manual clean-up effort.” News Science 21 22 23 24 data-ink ratio? = bad bad bad medium “The annotations were done by ten Harvard University undergraduates who had completed the Harvard introductory visualization course” 25 26 27 28 … it is colorful … it has a pictogram A visualization is Results (M=1.93 vs. M=1.14) memorable if… Thus, all results are presented with and without pictograms 29 30 31 32

  3. … it has low data-ink ratio … it is visually dense Some questions remain ● What visual elements do ● Same data people use to ● More labels ○ store into memory? ● Less participants (33) ○ retrieve from memory? ● More time ● Does giving more time ● + Eye tracking make a difference? ● + Word descriptions ● What do people remember? 33 34 35 36 Step 1: Encode Step 2: Recognize Step 3: recall 37 38 39 40 Does giving more time make a difference? What do people look at? Evaluating recall Titles help! So does redundancy! “Percent of people born on ● Quality was rated from 0 to 3 each day of the year. X-axis Encoding ○ 0 → incorrect or incoherent is month Y-axis is day. Most Titles improve recall quality popular birthdays are in late ○ 3 → visualization topic, what data or summer and early fall.” information is presented in the Description quality visualization, the main message of Description quality “this was a chart of most the visualization, and one additional common birthdays. the darker the color the more specific detail about the visualization common the birthday. september was the darkest Recognition month” Most recognizable Least recognizable 41 42 43 44 Strengths Weaknesses Beyond Memorability: Visualization Recognition and Recall ● First dataset of its kind ● Data is very skewed ● High quality, transparent ● Who would think tables Strengths and research. All the data is are memorable? Borkin, M., Bylinskii, Z., Kim, N.W., Bainbridge C.M., Yeh, C.S., Borkin, D., Pfister, H., & Oliva, A. available online. ● Infographics != infovis IEEE Transactions on Visualization and Computer Graphics, 2015 weaknesses ● Props for collecting verbal ● Maybe scientific descriptions of visualizations are visualizations → machine inherently harder to learning (: understand Presented by Julieta Martinez 45 46 47 48

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