andrew_gelman_stats andrew_gelman_stats-2011 andrew_gelman_stats-2011-794 knowledge-graph by maker-knowledge-mining
Source: html
Introduction: Eytan Adar writes: I was just going through the latest draft of your paper with Anthony Unwin . I heard part of it at the talk you gave (remotely) here at UMich. I’m curious about your discussion of the Baby Name Voyager . The tool in itself is simple, attractive, and useful. No argument from me there. It’s an awesome demonstration of how subtle interactions can be very helpful (click and it zooms, type and it filters… falls perfectly into the Shneiderman visualization mantra). It satisfies a very common use case: finding appropriate names for children. That said, I can’t help but feeling that what you are really excited about is the very static analysis on last letters (you spend most of your time on this). This analysis, incidentally, is not possible to infer from the interactive application (which doesn’t support this type of filtering and pivoting). In a sense, the two visualizations don’t have anything to do with each other (other than a shared context/dataset).
sentIndex sentText sentNum sentScore
1 Eytan Adar writes: I was just going through the latest draft of your paper with Anthony Unwin . [sent-1, score-0.086]
2 I heard part of it at the talk you gave (remotely) here at UMich. [sent-2, score-0.069]
3 It’s an awesome demonstration of how subtle interactions can be very helpful (click and it zooms, type and it filters… falls perfectly into the Shneiderman visualization mantra). [sent-6, score-0.794]
4 It satisfies a very common use case: finding appropriate names for children. [sent-7, score-0.214]
5 That said, I can’t help but feeling that what you are really excited about is the very static analysis on last letters (you spend most of your time on this). [sent-8, score-0.711]
6 This analysis, incidentally, is not possible to infer from the interactive application (which doesn’t support this type of filtering and pivoting). [sent-9, score-0.658]
7 In a sense, the two visualizations don’t have anything to do with each other (other than a shared context/dataset). [sent-10, score-0.159]
8 The real problem is that the first visualization does not seem to meet your goal for “graphics as part of a story. [sent-11, score-0.515]
9 ” Or at least it wasn’t obvious to me what the story was. [sent-12, score-0.285]
10 The story you seem excited about is unrelated and it almost seems like you are patching a missing goal from the first visualization by a story told from the second. [sent-13, score-1.046]
11 The outcome: no interactive visualization that you like that satisfies all 6 goals (or at least not in some obvious ways that would serve as guidance for others trying to build infovis systems). [sent-14, score-1.332]
12 My reply: Yes, I am most excited about that static analysis, and I realize that you can’t make those three graphs directly from the Baby Name Voyager. [sent-15, score-0.729]
13 But I still give the Voyager the credit, because I’m guessing that the way Laura Wattenberg found the pattern that is displayed in those three ugly graphs is by playing around with lots of time trends on the interactive graph. [sent-16, score-0.682]
14 So, although the mapping from interactive to static and back is not perfect, I think they worked well together in this instance. [sent-17, score-0.721]
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Introduction: Eytan Adar writes: I was just going through the latest draft of your paper with Anthony Unwin . I heard part of it at the talk you gave (remotely) here at UMich. I’m curious about your discussion of the Baby Name Voyager . The tool in itself is simple, attractive, and useful. No argument from me there. It’s an awesome demonstration of how subtle interactions can be very helpful (click and it zooms, type and it filters… falls perfectly into the Shneiderman visualization mantra). It satisfies a very common use case: finding appropriate names for children. That said, I can’t help but feeling that what you are really excited about is the very static analysis on last letters (you spend most of your time on this). This analysis, incidentally, is not possible to infer from the interactive application (which doesn’t support this type of filtering and pivoting). In a sense, the two visualizations don’t have anything to do with each other (other than a shared context/dataset).
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