Graphic Sociology

Time and Newsweek Circulation from the year 2007

Time and Newsweek Reader Demographics Table (US Pop. data from 2008 American Community Survey)

Time and Newsweek Reader Demographics - Graph

What works

These graphics accompany the graphic in my previous post about the counts of humanitarian images in Time and Newsweek. They are meant to give context to the methods section which describes these two magazines in terms of a few demographic variables and circulation information. I do not have access to the original source so I could not go back and get more demographic information besides household income and readers’ ages. It is possible that those were the only two pieces of information available in that source about reader demographics.

What needs work

The big question is: do you like the graph of the demographic data or should I just leave it in a table? I won’t tell you which way I’m leaning so as not to prejudice your opinions.

Go ahead, feel free to leave a one word comment (the one word being graph, table, or neither). If you’re feeling especially motivated, it would be nice if you explained your reasoning. But it’s August, so I’ll cut you some slack if all you can muster is a single word.

References

American Community Survey – 2008.

Mediamark Research & Intelligence (MRI). 2008 (Fall). Magazine Audience Estimates. New York: MRI.

Admissions rates at top schools drop | Yale Daily News

What Works

The above graph was produced by Yale Daily News. It is clean and does a good job of displaying their admission status compared to their competitors. The reason I thought it was worth mentioning is that a few small aesthetic decisions make the graph pleasing. I like the open circles. I like the fact that the ending values are included as numbers. I would have liked it if they had included starting numerical values, too.

Comparison

For those going through the college admissions process, it can be all-consuming. The New York Times runs a blog called The Choice that focuses solely on this process from the testing to wait lists to moving, transferring and everything in between. Unsurprisingly, then, they ran a table showing similar information about a larger number of schools which they gathered through a mix of old-fashioned reporting – contacting schools and asking them – and Web 2.0 reporting in which schools who had not made the initial deadline could email their data in to be added to the table. Have a look below.

The Choice blog at New York Times 2010 admissions data | J. Steinberg

Ask yourself about the difference between a table and a graph when it comes to conveying information. Edward Tufte is a fan of tables because they can display a great deal more information than a graph. That is true in this case – look at how many more categories of information there are in the table. What do you think? When is it better to present a table full of all the details and when is it better to display a graph like the one above?

References

Lu, Carmen. (5 April 2010) Admissions game getting riskier. Graph. Yale Daily News.*

Sternberg, Jacques. (2 April 2010) Applications to Selective Colleges Rise as Admission Rates Fall. The New York Times “The Choice” blog.

*Note that I wonder if the graphic designer got the data from The Choice blog piece – the publication dates could just be coincidental.

The graph below was originally posted at Flowing Data with an invitation for readers to take the same information and display it with clarity and meaning. The image below is difficult to understand – it brings to mind one of my favorite tricks which is to see if the infographic would deliver more or less the same message if it were in gray scale. This one would suffer in gray scale even more than it already is, a bad sign.

The original chart showing the increase in obesity (confusing)

Jonas Sekamane took up the challenge posed by Flowing Data and came up with what you see below as a first stab. He said, “My main “beef” with the graph above, is that comparison is difficult, if not impossible. This is of course due to the data gaps, but it could easily be fix with a guideline of some sort. Adding an age-group average, makes it much easier for the viewer to see if the level of obesity is in fact high or low.”

The second draft - now there is a single trend line, but still confusing

But he didn’t rest on his relatively simple fix. He decided that starting over altogether would be the only way to wrestle this information into a clear, meaningful infographic. First, he massaged the data into a more visually relevant format by calculating, “an index in Excel where 100 = the age-group average.”

I agree with his assessment of the original – that it was too far gone to be saved. I’d also like to take this opportunity to address social scientists more accustomed to the writing process than to graphic design process. Just as a paper will require several drafts before it reaches it’s potential, most graphics get better with revision. And like this reworking proves, sometimes it is necessary to scrap it all and start over, even after you think you have something could work. The key is that you cannot fall in love with your graphic designs (or your papers). In order to maximize their potential, some of them will need demolition and redesign, not just a new coat of paint.

No more trend line - Easy to see that obesity is increasing, especially for young people

Reference

Sekamane, Jonas. (29 April 2010) “Obesity Trends – Makeover”

Flowing Data (29 April 2010) Challenge – Graphing Obesity Trends

Recidivism rates of US prisoners - reduced color palette

Figure 6.3 from Henslin's Intro to Soc - Recidivism of US Prisoners

On color

When architects draft plans and sections, they pay close attention to line weight. Part of the craft of draftsmanship is knowing which line weights are just right and making sure to apply the right line weight in the right instance. One of the criticisms older architects who were used to drafting boards and pencils levied against younger architects who draft using AutoCAD programs is that they just don’t do line weights properly. CAD displays layers in different colors and the younger architects were happy to rely on the appearance of these different colors as they worked on their monitors without making smart choices about line weights. When the documents were printed, all the lines could be the same weight, or if there were different line weights, they appeared to be arbitrarily chosen. Why were the older architects so upset? Because line weight carries meaning in architectural drawings. Get it right, and a simple section can speak volumes to the trained eye. Get it wrong and it’s like hearing a sentence without inflection (or perhaps worse, with inflections in the wrong places).

I feel the same way about color that the older architects feel about line weight. Color should mean something in a graphic. When the paint bucket comes out, there better be a reason for it beyond ‘decoration’. Graphic design is not about decorating otherwise drab diagrams. It is about enhancing the amount of information that can be communicated that privileges the image over the word because words always already require translation and the potential for misunderstanding.

The two bar graphs above depict the same information. One uses color with no apparent meaning attached to it – the bars are different colors just because it looks nice. The backdrop is yellow perhaps “to make the graphic jump off the page”. In my opinion, the full bleed back drop is like a heavy cloak, burying the information the chart contains in a Halloween costume. This Halloween celebration continues with the use of randomly selected colors for each bar on the chart. And the use of italics and bold where it isn’t needed is much like costume jewelry.

The gray-scale graphic uses color to highlight the originating question for the graphic. Each of the bars is shaded in accordance with the recidivism level for that crime – those imprisoned for auto theft have a 79% chance of being rearrested so that bar is 79% saturated with black. The bottom bar represents a 41% rearrest rate so it is 41% saturated with black. In this way, the saturation level reinforces the length of the bar and the numerical value printed in the bar.

References

Color graphic from: Henslin, James. (2009) Essentials of Sociology: A down-to-earth approach 8th ed., Pearson Publishing: New Jersey. Figure 6.3.

Gray-scale graphic: By Norén.

Michael Schwabs poster design for the Art Center College of Design in Pasadena, CA

How to go from inspiration to design?

There are plenty of great graphic designers plastering walls with posters, filling magazines with intelligent ads, and even getting their work into museums. A lot of the time, it’s hard to see how all the inspiration and excitement of graphic design for advertising can make it’s way into the information graphics social scientists use to communicate their findings.

I took a fake example to show you how I translated my appreciation for Schwab’s design into some thoughts about enlivening a basic line graph. Let me emphasize this one more time: this example is fake. I didn’t use real data. Yes, global consumption of meat is increasing per capita, but no, it’s not as dramatic at it appears here. I went ahead and left off scales on the X and Y axes to ensure this graphic doesn’t end up traveling around the interwebs as truth.

Step 1

Break down Schwab’s graphic. He’s basically got a right triangle sitting on a single color background that bleeds into a thick border. The border contains the only text. The only realist element – the pencil – intersects the triangle to make what is like a giant X in the center of the poster.

How is this at all like social science graphics? Well, if you flip the triangle, it’s a lot like any positive relationship as depicted by a line graph.

Basic positive relationship depicted by a line graph

What next?

Now that you can see how a line graph is a little like Michael Schwab’s elegant pencil poster we can start to apply his decisions directly to our graphic. First, we can add a clearer background. If it’s just white the thick borders do not read as thick borders. They just look like the same old place everyone puts their axial labels. I distinguish this by adding a background color which will pull the borders into a relationship with the background behind the graph. I also go ahead and fill in the area under the graph to help nudge it into reading as an area, rather than some jiggly line.

The tough part here is the graphic. Not all stories we want to tell are going to be linked to a slender X-making image. I chose to depict the rise in meat consumption. Sure, I could have picked a cattle prod or other cattle killing tool dripping with blood. It would have been slender and I could have made an X. But I was trying not to appear unbiased so I just went with an iconic image of a beef cow. I planted the cow in the middle. We do lose a few data points in the middle – there are ways to deal with that if it’s important (overlay a yellow line across our cow’s gut where the data points are missing).

Here’s what we’ve got. The point is that the graphic below is the basically the same data as our line graph above except far more arresting (I took the liberty of adding two more lines of text – not necessary, but I was trying to closely follow Schwab’s concept). If you are trying to keep the attention of the audience in a presentation, be they sleepy students or sleepy colleagues, it might be worth your while to take a little extra time on your most important graphics. And if you do have one or two major points you want the people to take away from the graphic, you can write them across the top or up the side. Writing up the side is not as good – use it only for secondary points or graphic credits in the case that you hire someone to craft your graphics.

Simple line graph copying Michael Schwab's concept

References

Schwab, Michael. (2009) “Instrument of Creativity” [poster design] Art Center College of Design in Pasadena, CA.

Hirasuna, Delphine. (2009) “Art Center’s Instrument of Creativity” in At Issue Journal: The Online Journal of Business and Design. San Francisco, CA.

Top 10 States by HIV Rate 1987 and 2007 (CDC data)

Top 10 States by HIV rate - modified

What Works

This data could easily have been thrown into a table – the bars make it a graphic. It is more visually interesting and instantly legible than a table, but are the bars enough?

What Needs Work

Most of the states on the top ten list in 1987 are not still on the list in 2007. That’s the most interesting part for me, and I would like the graphic to address that somehow — either by focusing on the four states that stayed on the list or by making sure it’s easy to see just how much movement there is on and off. What did the states at the top of the list in 1987 have in common? What about the states at the top in 2007? It appears that having a high percentage of the state living in urban areas makes some kind of difference but the graphic doesn’t give any clues at all about what is going on to get on or off the top ten list. Quite honestly, it doesn’t make sense to talk about the top ten states by HIV rate. It just doesn’t. That’s what the graph tells me.

I did try my hand at nudging the graphic in the right direction with the pink barred example. I don’t know if those converging lines pointing to somewhere outside the top ten help viewers to key into the large amount of movement on the list, but that is what I was thinking.

In the end, it would be better to go back to the data and come up with a more thoughtful analysis than to alter this graphic. The moral of the story is that the graphic can only be as helpful as the underlying data and the logic of the analysis.

Relevant Resources

CDC HIV Report – 2007

Centers for Disease Control. (2008) HIV/AIDS in the US – Factsheet

Kaiser Family Foundation. Topic: HIV/AIDS Fast Facts – Slides

The Story From Across the Pond

There are so many stories that get played out on the legal stage and the stakes are highest when death is involved. I found two graphics each of which attempted to provided an overview of the death penalty in America. We start with the view from London (though the writer of the article was in New York while he was writing).

The Death Penalty in the US - An Overview with an emphasis on Texas

The graphic they’ve come up with over at The Independent does a great job of summarizing the story of the death penalty in the US. The best part of this graphic is the right-most graph showing that the states with the death penalty started with lower murder rates and *still* have lower murder rates than those states that have the death penalty. Murder rates in both types of states change over time, but those changes seem to be largely independent of the death penalty. Great way to show that the death penalty does not make a good deterrent.

One last notable point from this article is that the graphic seems to do a better job at representing “just the facts” than the text. From the other side of the pond, the continued use of the death penalty in the US looks, well, barbaric beyond anachronism.

From Usborne writing in The Independent: “China tops the world’s executions league table (officially it used the death penalty 470 times last year, though Amnesty International believes the true figure is far higher), followed by Iran and Saudi Arabia. Among developed industrialised nations, only the US, Japan and South Korea persist in retaining capital punishment. None of the United States’ European allies entertain it nor do its neighbours, Mexico and Canada.”

In case you aren’t accustomed to decoding dry British writing, it is most certainly not a good thing to fall into the same category as China or Iran when it comes to human rights.

The Story from the Backyard

Not to be outdone, the New York Times has also run a number of graphics about the death penalty which is a recurrent topic of popular and academic debate.

Death Penalty Overview - The New York Times

Here’s where the difference between the US depiction and the UK depiction starts to stand out. The UK added up all the executions since 1976 which tends to imply a great magnitude of death. There’s a big red 409 over Texas in their graphic and ‘just’ 20 in the NYTimes graphic, because the Times took a statistician’s more favored approach of looking at the number of death sentences per 1,000 murder convictions. This makes it easier to compare state by state data because it acts as a control for population size and murder rate. In this version, Oklahoma, Nevada, and Idaho appear to be more invested in the death penalty than Texas. Don’t mess with Texas becomes don’t mess with Nevada. (I guess what happens in Vegas really does stay in Vegas…but not in a good way).

The NYTimes graphic also looks at the sentencing rates when the race of the victims and perpetrators are the same and when they’re different. The way they’ve simply represented the facts speaks clearly to the continued machinations of racism in America. When whites are the victims, the perpetrators are more likely to be sentenced to death, especially if those perpetrators are black. Look at that part of the chart for a while then think about why the writer from The Independent has such strong negative feelings about America’s death penalty.

The Story from the US – 2003

Juries Reluctant to Give the Death Sentence

This post is not about how the general population in America feels about the death penalty – check out some of the death penalty blogs listed below for more on public opinion. I was beguiled by this next graphic because it so simply illustrated ambivalence which is not all that easy. Each block is a case, every case has to have only one outcome with respect to death sentencing, and the designer manipulated this binary to produce a picture of declining conviction. Bravo.

The article’s text offered about five competing reasons for the decline in the rate of death sentences applied, including poor representation. They ended with this one:

“Alan Vinegrad, a former United States attorney in Brooklyn, said the recent statistics represented something larger.

”It reflects that the tide is turning in this country with regard to attitudes about the death penalty,” Mr. Vinegrad said. ”There has been so much publicity about wrongfully convicted defendants on death row that people sitting on juries are reluctant to impose the ultimate sanction.” ”

Relevant Resources

About.com’s list of the Top Ten Death Penalty Blogs. Most are not big on graphics or visuals of any kind.

Amnesty International’s Human Rights Now blog which hosts their posts on the death penalty.

The Death Penalty Information Center

Liptak, Adam. (18 November 2007) Does the Death Penalty Deter Murders? in The New York Times. National Section.
–Including this, ““You have two parallel universes — economists and others,” said Franklin E. Zimring, a law professor at the University of California, Berkeley, and the author of “The Contradictions of American Capital Punishment.” Responding to the new studies, he said, “is like learning to waltz with a cloud.””

Liptak, Adam. (15 June 2003) Juries Reject Death Penalty in Nearly All Federal Trials. National Section.

Usborne, David. (7 August 2008) Why is the United States still imposing the death penalty? in The Independent.

Mapping the location of crimes committed in Brooklyn, 1998

Mapping the home addresses of the imprisoned population in Brooklyn, 2003

What Works

The beauty of these graphics is that, given their captions, they are instantly legible. On the left, the map shows where crimes are committed in 1998. It’s a diffuse pattern with a few warm spots. On the right, the map shows where the imprisoned population calls home (2003 data). It’s an image with vivid hot spots amidst a sea that’s mostly dark. In thirty seconds or less, viewers can see that while crimes are committed all over Brooklyn, the population in prison tends to come from a handful of very localized neighborhoods. It would have been easy, and easy on the eyes, to use two different colors for the different maps, but because this idea works as a comparison, it’s important to keep the color scale the same across both images.

These maps are used as tools of analysis and pattern recognition, helping to make data legible both for the public and for the researchers who use these tools not only as tools for publication but also as tools of analysis. They go further, augmenting these maps with finer grained maps as you’ll see if you keep reading.

What Needs Work

A stronger outline of Manhattan would help non-New Yorkers recognize the location immediately.

More Than Critique

This post reminds us that there are many victims of crime. The authors’/graphic designers write, “If crime maps succeeded dramatically in mobilizing public opinion, redefining the city as a mosaic of safe and unsafe spaces, and forcing the reallocation and targeting of police resources on specific neighborhoods, the gains were short-lived. The resulting crime prevention techniques, and the community-policing movement in general, soon reached the inevitable limits of any purely tactical approach. The city spaces that were targeted came safer, but too often crime incidents were simply displaced to other locations.”

Nobody is denying that being mugged or raped or murdered is fun for the person who was mugged or raped or robbed or murdered. But the report by the Spatial Design Lab at Columbia University sponsored by The Architectural League that uses maps as a tool of analysis and discovery to suggest that because perpetrators live in areas with lots of other perpetrators, those entire communities are also the victims, not of the crimes per se, but of the impact of high concentrations of recurrent incarceration. Convicted people go away to prison leaving these neighborhoods with a gender imbalance (only 12% of the prison population is female). The money spent to imprison this largely male population is not being invested in developing these communities. This study finds a block where $4.4m has been spent to imprison its one-time residents. One block, $4.4m.

Million Dollar Block, Brownsville neighborhood in Brooklyn 2003

The authors pose the question their maps have helped make obvious: “What if we sought to undo this shift, to refocus public spending on community infrastructures that are the real foundation of everyday safety, rather than criminal justice institutes of prison migration?”

Relevant Resources

Spatial Information Design Lab at Columbia University (2006) Architecture and Justice sponsored by The Architectural League.

Spatial Information Design Lab Main Page

The Architectural League

US Greenhouse Gas Inventory Report - Executive Summary, Figure ES-11

Why This?

Continuing what I have decided will be an agriculture theme for the week, I went looking for data related to energy efficiency of diets. This concept first became news in the 1970′s during the energy crisis, championed in the book “Diet for a Small Planet” by Frances Moore Lappé which has recently been released as a 20th anniversary edition. I was interested in getting to the bottom of the planetary (rather than the personal) part of her argument which is that to produce unit weight of protein in the form of beef/veal, the animal is going to need an input equivalent to 21 units of protein and we’d be globally better off if we just ate the plant sources ourselves in terms of energy consumption and intelligent stewardship of the planet. I didn’t quite find what I was looking for to back up that data (yet) but I did find the contemporary twist on that argument which relates dietary choice to greenhouse gas emissions.

What Works

The first graphic doesn’t work all that well and probably makes no sense to you so we’ll come back to that. The second graphic, from the EPA, is not particularly pretty, but it has strength in simplicity and it makes intelligent use of the x-axis to represent greenhouse gas sinks. (Note: The visual representation does a great job of communicating that are emissions dwarf our sinks better than reading a number on a page would do.) Whereas the first graphic fails miserably to represent the difference in the energy efficiency of diets, the second graphic at least conveys the conclusion of the report that went along with the first graphic which is that the difference between eating the standard American diet and a vegan diet is, “far from trivial, …[it] amounts to over 6% of the total U.S. greenhouse gas emissions.”

The details of the report accompanying the first graphic are worth perusing and I only wish they would have spent more time trying to represent them graphically. The authors, Eshel and Martin, compute the comparative impacts of transit choice vs. dietary choice and find that, “while for personal transportation the average American uses 1.7 × 10^7–6.8 × 10⁷ BTU yr⁻¹, for food the average American uses roughly 4 × 10⁷ BTU yr⁻¹.” That would make an excellent graphic in about ten different ways and catapult them past the problem that many readers are going to get tripped up looking at the orders of magnitude and units and miss the point.

What Needs Work

The first graphic is supposed to show the composition of the hypothetical diets considered. The mean American diet as reported by FAOSTAT has a little break-out component that provides more detail about the constituents of the animal products category but it took me a long hard look to figure that out. The break out part should have been constructed so it wasn’t exactly the same scale as the rest of the graphic (which it isn’t, by the way) otherwise it just reads like another column with viewers liable to assume that they can follow the scale on the y-axis. But the y-axis doesn’t relate to the break-out part at all – only the percentages listed alongside it are salient.

My bigger problem with the first graphic are the next five bars. Just to help you navigate α represents the proportion of the standard 3744 kcal diet that comes from animal sources. See α, think animal. A key would have been nice. Now that you know that, looking at the graph, it appears that each of the diets gets the same amount of kcals from plant sources because the green segments are all the same size. However, this is not actually what the authors are trying to convey. You have to read through the text quite carefully to pick out what proportion of each diet comes from animal sources overall. Once having done that, this graphic can help you further breakdown how those animal sources are apportioned. For example, the ovo-lacto group gets none of their animal protein from animal flesh – only from dairy (.85 of animal protein total) and eggs (.15 of animal protein total). But it took a good ten minutes of going between text and graphic to figure out what they have charted here. In all honesty, I’m still a little confused about whether the last three diets just switch out fish for meat for poultry and keep the same total number of kcalories in the animal flesh category relative to dairy+eggs. And I certainly can’t tell if any of those hypothetical diets have a greater or lesser proportion of kcals coming from plants by looking at this graphic.

In summary, the two graphics here were not trying to make the same point. The first one was trying to explain how the authors modeled their hypothetical diets in order to convince you that, in the end, and in conjunction with some other writing and graphic representation, if Americans moved to vegan diets the national greenhouse gas emission rate would drop by 6%, on par with what would happen if everyone started driving a Prius. The second graphic does this much better using aggregate data (and thus a totally different approach than Eshel and Martin).

Relevant Resources

Eshel, Gidon and Martin, Pamela. (May 2005) Diet, Energy and Global Warming. Submitted to Earth Interactions.

United States Environmental Protection Agency. (April 2008) Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006

Moore Lappé, Frances. (1971, 1991) Diet for a Small Planet Ballantine Books.