Graphic Sociology

Figures 1 and 2 from "Who Gives a Tweet?" by André, Bernstein, and Luther CSCW paper

What works

A new study will be presented in a couple weeks at CSCW by researchers in Human-Computer Interaction and Social Computing that used 43,000 ratings of tweets to explain what content twitter readers find useful.

In short, worthwhile tweets:
1. Are informative NOT boring
2. Are funny
3. Are concise (even shorter than 140 characters!)
4. Are hyper-timely
5. Avoid whining and navel gazing (Tweets about meals past, present, or future are ‘boring’)
6. Avoid using too much twitter mark-up like @ replies, hashtags, multiple links)

The graphics do a good job of providing a visual overview of the study’s findings. With my brief textual synopsis and the two graphics here I bet many of you reading this will feel like there is no need to go read the study itself. Just in case that’s true, you should know that in the author’s discussion section, they note that their raters were volunteers who were not randomly chosen and skewed towards the tech crowd. Perhaps there’s reason to believe that tech people would be more likely to appreciate informative tweets? Not sure. But I can say from my own research that there is a noticeable portion of the twitterverse that appreciates food-related tweets. Even within that sub-group, people tend to appreciate tweets about recipes or with pictures over tweets that just say, “I had a great #sandwich at lunch! Fresh mozzarella rocks.” A recipe is informative. A recounting of lunch or a whiny tweet about missing lunch is boring at best and annoying at worst.

The thing I like best about this piece is that many of the findings apply to communication in general, not just tweets. Folks, it’s probably true that whether you are tweeting or talking, nobody wants to know what you had for lunch unless they want to have what you’re having. And if they do, they’ll probably ask. No need to volunteer. Also: brevity is the soul of wit; and wit is wonderful.

As an aesthetic point, I think they got the colors about right. Red represents the not-worthy or bad votes that ought to stop; blue represents the neutral position; and green represents the good tweets tweeps should go for.

What needs work

This graphic came without a title and I added “Which tweets are worth reading?” because it was really hard to interpret the graphs at first glance without a title. There is enough information for interpretation in the caption, but I think a caption should not stand in for a title.

The title is the first thing we see.
The graph is the second thing we see.
The caption is the third thing we see.
In order to understand the graph, then, it’s logical to have a title first so that readers’ don’t get frustrated that they have no idea what these colorful bars represent (the axes only get us halfway there in this case).

The title follows their own recommendations: questions work well as tweets. I figured I would try it here as a title, see what happens.

References

P. André, M. Bernstein, and K. Luther. (In press). “Who Gives A Tweet: Evaluating Microblog Content Value.” To appear in CSCW ’12: Proceedings of the 2012 ACM Conference on Computer Supported Cooperative Work. (Best Paper Award honorable mention; top 5% of submissions)

Worldwide Texting Trends | by shanesnow for Mashable using Pew Internet research

What works

What I like most about this graphic is that it summarizes great research from Pew that many folks would not have perused by reading Pew’s publicly available reports. That’s always one of the reasons I tout information graphics – they make information accessible and interesting to people who don’t have the drive/access/time to read full reports and the graphics often give more detail than do executive summaries. Clearly, any summary cannot give all the granularity of the report, but I assume most people do not read full reports. This comprehensive visual summary packs in more information than would a journalistic article about the research that have to include the requisite interview with a teen who texts or the parent who pays her bill or the person who was injured by a texting driver (or the guilty driver). Only sprinkled among the vox populi would we see a couple of quotes from a couple of ‘experts’ who conducted the survey. And nobody can summarize all that much in a total of four-ish quotes. I am still weighing the pros and cons of recommending that standard executive summaries be replaced by (accompanied by?) information graphics like this, at least in the case of survey-based reports.

Out with the written executive summary, in with the infographic summary? Please debate.

What needs work

I couldn’t find the actual references so I added some of my own where you can corroborate things like the Finnish PM who broke up with a girlfriend over text and the story of the first text message sent by Neil Papworth. My guess is that the bulk of the information comes from Pew while a lot of the fun facts come from the other sources. But I couldn’t find that out for sure without a great deal of effort (like tracing back every single datapoint in each of the components of this graphic).

The interwebs has a social policy of hyperlinking to sources. Please folks, keep that going someway, somehow. Otherwise we risk plagiarism which is bad in itself (see my dissertation 2011). Additionally, when it is not possible to check facts, exaggerations, methodological mistakes, made up info, and just plain lies are harder to ferret out.

References

Pew Internet and American Life Project
   Report on Mobile Access (7 July 2010)
   Report on Teens and Mobile Phones (20 April 2010)

shanesnow. (18 August 2010) “US and Worldwide Texting Trends” Original post at mashable.

Boyes, Roger. (14 March 2007) How potato love affair with Finnish PM went off the boil. The Sunday Times online.

BBC News Online. (3 December 2002) Hppy Bthdy Txt.

New York mapped by geotagged photos

Just thought this was cool

This map of New York was created by Eric Fisher. He gathered the geotags of the photos uploaded to flickr. The colors work like this: blue photos were taken by locals (deemed to be local because they had taken pictures in the same location over an extended period of time), red indicates photos taken by tourists (people taking photos outside of their frequent-photo-taking-zone), and the yellow ones were indeterminate (taken by people who hadn’t uploaded any photos in the previous 30 days though we guess they might be tourists because they may be the kind of people who only take photos while on vacation).

I like the aesthetic and the method so that’s why I decided to share.

Infographics News

Reading suggestion

I came across a blog that was new to me, all about information graphics with a Euro-slant, though the New York Times is still well-represented. The writer is Chiqui Estaban out of Madrid and somewhat heroically, he posts in English and Castellano. If you can read Spanish, I recommend that version because the English isn’t perfect. But then again, if you are reading this blog, you understand the value of a good image to communicate clearly, so hopefully you can look beyond a few errors in grammar.

Digressive Thought About English on the Interwebs

The fact that Sr. Esteban publishes in not only his native language but also in English makes me wonder if it is time for one of the contexts blogs to start a discussion about the primacy of English online. It’s harder to detect if English is your native tongue, but in other places, making a website requires knowing another language, hiring a translator, or using google translate (or Yahoo!s Babel Fish, etc.). And for a blog that is posted everyday, that is tedious (and therefore, may not happen). There is a much larger conversation here. English speakers have hidden privileges online (borrowing and repurposing that term from Lipsitz) that make their e-productions more international than they likely know.

References

Esteban, Chiqui. Infographic News.

Lipsitz, George. (1998) “The Possessive Investment in Whiteness”. Temple University Press.

Greenhouse gas emissions | World Resource Institue and Google's Public Data Explorer

What works

The World Resource Institute has partnered with Google to create an interactive portal for creating visualizations based on publicly available data. Google has been in the business of doing this sort of thing at least since the time they acquired Trendalyzer from Scottish-based gapminder.org in 2007. To be sure, gapminder.org is still a going concern of its own and IBM also offers free web-based visualization services through their Many Eyes program.

The focus of the trendalyzer is to show change over time and they succeed in making it quite easy to watch panel data change over time.

What needs work

BUT…I find that this particular graphic is a great example of a misleading reliance on time as the key ‘context’ variable. So the graphic above breaks down greenhouse gas emissions by US state over the course of the year. If you have already clicked over to the World Resource Institute and watched the animation of these bars pumping up and down (more up than down) and trading places with each other over time, you will surely have been fascinated. I watched it three times in a row. But I was stuck wondering what the take away was meant to be. Clearly, there is the first order take away that the bars pretty much grow over time, they do not shrink. If I were the World Resource Institute, getting that message out would be important to me. But I would hope for more than just the bullhorn approach, “More is BAD! More is BAD!” which is kind of how this hits me at the moment.

One of the biggest problems with this graphic is: not all US states are the same size. Of course Texas emits more greenhouse gases than most states – many more people live there than in, say, Kentucky, Iowa, Oregon, etc. But the World Resource Institute chose to display per capita emissions with the bubble approach (which has almost no redeeming value in my opinion because I cannot even see half of the bubbles. Maybe they all could have been reduced by half or more? And maybe instead of going with colors on a spectrum, the worst could have been red, the best could have been green, and most everyone else could have been some shade of grey? It’s just not possible to hold 50 changing variables in your active cognitive space at once. Reducing it to three variables – the good, the bad and the mediocre – could actually increase retention and pattern recognition.)

Greenhouse Gas Emissions Per Capita, US 2007 | World Resource Institute and Google

But back to the bar graph at the top. For the purposes of greenhouse gas emissions, it makes the most sense to interpret size as population not square miles, so that’s what I am going to do. In an attempt to be helpful, I threw together a bar graph of the top 10 most populous US states (using 2009 population estimates) in good old Excel. Note that our friend Texas is not the most populous state by about 12 million people – that is a lot of people. California is the biggest and they emit way less than Texas. New York is the third most populous state and we emit far less than our proportional share would suggest. Let’s hope it stays that way because I already find it unpleasant to breathe the air in Manhattan (admittedly, that could be due to many causes besides greenhouse gas emissions).

Most populous US states by size

My suggestion here is clear: prepare a bar graph per state, per capita. And, yes, I would want to see how that changes over time. I would probably watch the animation six times instead of three times. My fantasy is that we could compare not necessarily by state, because that is in many ways arbitrary, but by personal habits. Say we get the most extreme environmentalists – vegan, freegan, won’t even take motorized public transportation, never flies, prefers candles to compact fluorescents, has a composting toilet – to the somewhat average person who has a car but not an SUV, eats meat but not every day, does not pay more for organic food – to the extreme non-environmentalist who owns three houses, drives in an Escalade or something of that nature, flies internationally at least four times a year, pays extra for organic food (but at restaurants), and sends clothes to the dry cleaners twice a week. But that would probably result in a graphic best described as “info-porn”, enticing and exciting but intellectually vacuous.

Summary

The WRI is on to something with their Google partnership. My favorite of their early work is this line graph that does a better job of telling the emissions story than any data broken down by state.

Greenhouse Gas Origins | World Resource Institute and Google

But the other great thing about the new partnership is that they ask for suggestions and set up a google group to manage the roll-out and incorporate nay-sayers like myself.

“By pairing [the Climate Analysis Indicators Tool] CAIT data with Google’s tools, there are new possibilities for people everywhere to take part in using sound data to tell stories that frame environmental problems and solutions. In the future, we hope to include additional data sets that can tell even more stories through Google’s visualization tools.

Suggestions for what you would like to see, or have a question about CAIT-U.S. data? Let us know here or join the conversation at http://groups.google.com/group/climate-analysis-indicators-tool.”

Selling Out: How do musicians earn money online? | Information is Beautiful via Flowing Data

What works

Here’s another graphic from David McCandless atInformation is Beautiful (though I came across it when Nathan Yau wrote it up at Flowing Data) which was originally motivated by McCandless reading a piece written by independent recording artist Faza at The Cynical Musician. After the infographic hit the blogosphere, Faza ended up receiving some sort of secondhand criticism which he then countered by trying to explain what he was up to in a follow-up blog (see below for all the blogs in question).

Here’s how he described what he was originally trying to figure out:

“Most of what I write (apart from broader policy or economic issues) is aimed at the independent artist. I’m one myself, so I know the pain all too well. I know that deep down the independent artist hopes for the day when they are making enough money to be able to concentrate solely on their art.

The independent artist does not have a huge fanbase – the evolution of the Internet thus far has not changed this. The independent artist has few resources and usually cannot afford a huge marketing push. The independent artist’s financial situation largely depends on getting the most from her limited fanbase with the least expenditure possible. The biggest bang for the buck, if you will.”

This was in response to folks who pointed out that the future of the music is the past (ie live performance) or that the the profitability of music is not just in the ticket sales but the merchandise! Rightio. But Faza pointed out that for truly independent folks who do not have the resources to get out there and market themselves, going on tour and selling a bunch of tickets (and merch) probably isn’t going to happen. And, selling band t-shirts online is tougher than selling them at concerts, so the interwebs aren’t exactly making a huge difference there either.

10.000 ft view

One more thing before we get to the graphic itself. When I was fiddling with it in photoshop I realized that I had a greater appreciation of it when I started with the 10,000 foot view and then slowly zoomed in.

The colors are good. For some reason, black + some bright color is a good idea when it comes to contemporary cultural products like music and fashion. Smacks of a certain dynamism and ‘cool’ factor, which is just the spot this graphic is aiming to hit. Of course, the black + bright color = cultural cool formula will change and it doesn’t mean there are not many other components that could add up to cultural cool. Just saying, I think the basic strategy with the full bleed black background and a single bright color (100% M) is working here. The growing circles also do a good job of making the point that streaming music will not pay the bills and neither will selling downloads on napster or other similar sorts of sites.

The most surprising fact for me was that self-pressing a CD and selling it directly to consumers was more rapidly profitable than any of these other options. New respect for all the folks in New York and LA who have stopped me and tried to get me to buy their music while I’m walking down the street/beach.

What needs work

My biggest issue with this graphic is the the little pie charts are really where it’s at – they are not part of the big picture story that the more ‘advanced’ online music sales techniques are the less profitable per unit of effort they are for the artists. The little pie charts try to show us how the money is allotted. But the revenue pie is never a full pie and it’s difficult to tell where the money that doesn’t go to the artists or labels is going. Some clearly goes into things like the cost of the physical CD (where there is a physical CD) and some goes to the other players involved, right? But how much? And who are these other players? And why choose a pie graph technique if the pie is never completed and the incomplete part is not fully specified? In the end, what those pie charts do is compare revenue streams to two recipients – labels and artists – while offering a general sense of the amount of money going elsewhere (though we don’t know where that elsewhere is). Maybe a flowchart of dollars moving from consumers into different pots would have done a better job of demonstrating that portion of the story.

I would also point out, from a sociological perspective now, that minimum wage is both a logical reference point and a difficult reference point. Minimum wage puts a single person just over the poverty line but the poverty line is incredibly low. Poverty lines are tied to the cost of food rather than to some composite cost of daily living that includes not only food but rent, transportation/energy, health care, and all of those things that people have to spend money on which have increased more rapidly than the cost of food. It’s my long-winded way of saying that even if artists could make minimum wage they would not actually be able to live comfortably, especially not in cities like LA and NYC where there are large, vibrant music scenes. They would have an easier time in Nashville.

References

Faza. (10 January 2010) “The paradise that should have been” at The Cynical Musician.

Faza. (15 April 2010) The paradise that should have been – revisited at The Cynical Musician.

McCandless, David. (13 April 2010) How much do music artists learn online at Information is Beautiful.

Yau, Nathan. (4 June 2010) “How little musicians earn online” at Flowing Data.