I completely understand what you mean, John, when you talk about the difficulty of exporting Twitter data. My point was not to critique the NY Times engineers, but to illustrate how we must question what is made invisible in visual representations of data. The engineers made choices for which font colors to use and what words to be made visible at certain points in the visualization. As I look more closely at the map, I see that the size of the words are not represented on the same scale. That is, at 9:50pm the word “Cardinals” has 73 references in the area near New York. At the same time the word “go” received 49 references near Pittsburgh. Yet, “go” is displayed in a font size significantly larger than “Cardinals.” Visual data meant for comparison must be represented on the same scale in order for it to accurate–or, as Tufte would say, for it to function effectively as “beautiful evidence.” The question of scale is one most certainly in the hands of the engineers.

As Bowker and Star and Lakoff and Johnson show us, decisions to make certain items visible means that certain things were necessarily made invisible. The invisible is what I am interested in thinking more about.

Chuck, no, not a hole in my theory at all, but a revelation as to what might be going on with the word Go. As you suspect, at 9:50pm the term “GoDaddy” shows up strong when viewing the map when the “Talking about Ads” category is selected. This raises a whole host of questions, including: how many of the “go” references were referring to GoDaddy but were written as “Go Daddy”—that is, with a space between Go and Daddy. As with the Bruce/Springsteen example, the map is most likely only representing a portion of references to GoDaddy. Of course, we would need to know more about how many times the word “Daddy” appeared following “Go_” to be fully sure.

But it also raises a host of questions about the “people saying ‘go’” category, which I believe is clearly meant to refer to the cheer often heard at sporting events: “Go Steelers!” “Go Cardinals!” “Let’s GO Rangers!” and so on. How many of those “go” references actually refer to GoDaddy and are not part of a cheer? This question makes the whole “people saying ‘go’” category suspect because the data might actually represent something other than the implied meaning of the category.

Oh, and John, if you have any idea how they might have been able to extract the data, I’d be quite interested in learning about that.

I love this analysis, though, and the words that oddly crept into the picture. There were a few references to “faith” at the beginning of the game, which I’m assuming refer to Faith Hill’s performance of the national anthem.

I guess my point is that it is likely some of the problems you identify with this data originated on Twitter’s end.

Cheers,

John