Food blog content characteristics and frequency of use | The Food Blog Study

What works

I conducted a web-based survey of food bloggers last summer as a doctoral intern at Microsoft Research in the Social Media Collective. I am now analyzing the mountains of data that I gathered in the interviews (N=30), survey (N=303), and web crawler (N=30,000) and getting ready to send out papers for publication. I thought it would be nice to share some of the findings here in advance of the slow academic publishing process.

Since I made the graphic and since I am modest, I’ll just say that I like the colors and I like that I was able to find a way to keep all of the granular detail of tabular data while adding visual impact.

If you would rather hear about the substance of the study than about the struggles I had while creating the graphic, skip to the bottom third of the post and the “What surprised me” heading.

What needs work

Since I have the benefit of having seen the data I can say that two things certainly need work. First, the survey asked about many more behaviors than I have decided to depict in this graphic. I left out data mostly because I want to be able to publish it and publishers are not keen on accepting already-published material. Some of them are not too bothered if bits and pieces of the findings are blogged about here and there. Some of them are hugely bothered and will not accept submissions that have been written about on blogs at all. There are good reasons for subjecting the findings to peer-review – like having smart people verify that the findings are not fabricated from thin air or otherwise constituted by complete rubbish. All that being said, my biggest problem with this graphic is that it is just the tip of the iceberg in terms of what the survey had to say about the characteristics of food blog content.

The second big problem with this is that I had a very difficult time dealing with proportional data in the rows and the columns. In case you still haven’t figured out what this graphic is saying – and I don’t blame you if you find it hard to digest – the graphic is depicting the frequency with which about 300 food bloggers (303 to be exact) reported using the listed types of content. For example, 96% of food bloggers report using video 20% of the time or less. Video just is not all that common on food blogs and most food bloggers hardly ever use it. Images, on the other hand, are included in food blog posts most of the time by most food bloggers. Seventy-four percent of food bloggers use photos 80% of the time or more. Reviews of restaurants, cookbooks, and kitchen gear, on the other hand, end up on 11% of food bloggers posts very frequently (80% or more posts contain reviews) while fully half of food bloggers hardly ever post reviews (20% or fewer of their posts contain reviews).

Since most food bloggers like to mix things up at least a little – hardly anyone has such a firmly established template for their blog content that 100% of their posts contain recipes and photos while 0% of their posts contain videos or discussion of non-food content (which would include mentions of important life events like getting a book contract, having a child, getting married, or getting cancer). With content, then, I wanted to let food bloggers explain about how often they posted a variety of different kinds of content. But then I had this difficulty of having proportions in the rows and the columns of the graphic which makes it difficult to interpret. Believe me, the tabluar data without the blocks changing sizes and colors was even harder to interpret so turning this information into a visual did help the analysis along by making the patterns clearer.

What surprised me

I was expecting many more bloggers to report including recipes more often. Only 37% said that 80% or more of their posts contained recipes. From what I gathered in the interviews, having someone else make your recipe and then leave a comment about it is one of the routine gratifications associated with food blogging. Web traffic to the site from google.com and on mini-search engines within the site is generally related to recipes, as well. So whether food bloggers care about the deeper meaning associated with food blogging and being part of a community or the hard-nosed economics and web traffic side of writing a blog, from the interviews, I was expecting recipes to be a bigger part of reported content than what I found in the survey. Recipes are one of the main activities around which both creativity and community are wound. They also draw a lot of traffic. On blogs, traffic often equals money (though not all that much money, which is why I think the meaning associated with recipes is more interesting than the money associated with recipes).

I was not at all surprised that most bloggers ignore nutritional information but I think that people who have never done much with food blogs would be surprised to see that three-quarters of bloggers mention nutrition and nutritional information 20% of the time or less. Food blogging gets its meaning and importance through practices of creating and community-making, not because the blogs are used as archives or tracking devices for those trying to lose weight or achieve other health goals. There are blogging communities organized around those things, but generally speaking, folks in those communities do not identify with the term ‘food blogger’.

Reference

Norén, Laura. (2012) Infographic: The Content of Food Blogs. The Food Blog Study. [www.foodblogstudy.info/findings.html]

Geography of twitter in a tree map
Geography of twitter in a tree map. Graphic created using TreeMappa. Data gathered by Devin Gaffney; analysis by Monica Stephens and Mark Graham.

What works

1. Boxes-in-a-box diagrams aka treemaps achieve an efficient use of space without sacrificing granularity of information.

2. Intelligent grouping – all of the countries from each continent are grouped together in boxes that fit neatly into the perimeter of the overall boundary.

3. The color in the boxes does not obscure the labels. Also, the font size is well chosen.

4. The treemappa algorithm rigorously adheres to scale which is critical for visual analysis. Scale communicates across language barriers and that’s one of the reasons visual communication has advantages over text-only communication.

5. Treemappa is free to use.

What needs work

1a. The legend is efficiently small to benefit the efficiency goals of the design, but it doesn’t explain what numerical value underlies the High, Medium, and Low internet users-to-tweets ratio. The blog post accompanying the graphic does not describe this ratio either though I would imagine it is discussed in the as-yet-unpublished manuscript “Where in the world are you? Geolocation and language identification in Twitter” listed (but not linked) in the references. We’ll have to wait for formal publication.

1b. We also can’t tell what the scale is with respect to the activity comparisons between countries. Scale is extremely important for interpretation [see number 4 above]. It’s critical to include numbers in the legend so that viewers can calculate ratios. [For instance, I would like to know if they’re using a log or a linear scale but without a numerical legend I can’t tell…]

2. The biggest problem with this graphic is a problem I have been contemplating about many different information graphics: information graphics are consumed as hermetically sealed information objects that offer a kind of apolitical truthiness. Within the social science tradition – and within most scientific traditions – it’s incredibly important to make the messiness of research transparent. In this particular case, the blog author does an excellent job of representing the dubious validity of this research in the blog post that accompanies this image when he writes:

As a first step, we decided to collect all georeferenced tweets sent between March 5 and March 13, 2012. It is important to point out that georeferenced tweets comprise fewer than 1% of all tweets and it is possible that significant geographic biases exist in where and how people georeference their content.

So should we trust that the numbers above are representative of the actual geolocation of tweets? Well, we should only assume that this is a good representation if we believe that there is no systematic geographical correlation between users who include geolocation data with their tweets and those who do not. I am not a twitter expert, but it’s hard for me to swallow the idea that users of twitter have the same attitudes about privacy and competence with privacy settings the world over.

The tyranny of beauty

The bigger question for information graphics, though, is how can we ensure that the graphics themselves reveal their own messiness, incompleteness, and methodological underpinnings? If information graphics are to become legitimate components of (social) scientific practice, they need to find ways to include the kinds of doubts, disclaimers, and methodological difficulties that appear in the discussion section of academic papers.

I struggle with this immensely in the graphics I make. I’ve found that the designerly desire that graphics be beautiful in order that they communicate instantaneously through first impressions lead to a tyranny of aesthetics in which graphics that are deemed “good” are those that specifically avoid messiness and present a sanitized, sealed, image-as-object that deliberately obscures many of the problems that remain open questions. The graphic presents itself as an answer. In text, it is possible to differentiate between the elements of questions that are leaning towards answers. In photographs, interpretations can be meaningfully multiple. But in information graphics, the image is often so tightly bounded that it leaves no invitation to skepticism.

Boxes-in-a-box diagrams like the tree map above is a particularly clear illustration of the larger tension in which information graphics are asked to present clear and complex information at the same time that academic requirements ask that they make their messiness and unknowns obvious. The graphics were created in order to present information efficiently at first glance and then reveal granular detail upon further inspection. This is a worthy set of goals and the boxes-in-a-box tree map diagrams deliver on both of those goals. I would argue that those goals satisfy only one side of the problem – to communicate what is known in a clear, compelling fashion – leaving aside the notion that much remains unknown, that many other relationships have been left out, and that even the things we think we know rely on sound methodology which may or may not be possible. Social science research has always been blessed/plagued with the challenges of drawing meaning from incomplete, intersecting, and incommensurable information.

This is an issue I’ll continue to explore and I encourage both designers and social scientists to share thoughts about the benefits and drawbacks of ‘beautiful’ information.

References

Graham, Mark; Stephens, Monica; and Gaffney, Devin. (2012) “A Geography of Twitter” [blog post] Visualizing Data blog. Oxford, UK: University of Oxford, Oxford Internet Institute.

TreeMappa [free online graphic creation tool]

Saveur food blog award nominees and winners by gender, 2010-2012
Saveur food blog award nominees and winners by gender, 2010-2012

Gender in food blogging

Last summer I conducted a survey of food bloggers (N=283) which found that 85% of food bloggers are women (see here for more demographic statistics from the survey). I also conducted interviews with food bloggers and started to get the impression that food blogging is a community dominated by women in which the relatively few men end up being disproportionately successful. This kind of gender disparity – a group that is overwhelmingly women in which men are more likely to occupy positions of power or prestige – has been written about in the sociological literature with respect to elementary school teaching and nursing. In elementary schools, for example, the majority of the teachers were women but administrators (like the principal and vice principals) were disproportionately likely to be men. This gender disparity in the schools is no longer as pronounced as it once was. Women now occupy more of the administrative positions but men have not moved in to occupy more teaching positions. If food blogging follows the same trajectory, we can expect women to occupy more of the most prominent food blogging positions over time.

But what is a ‘prominent food blogging position’?

Since food bloggers are not working professionals within a clear hierarchy like teachers and nurses, I decided to look at food blog awards data as a proxy for success in the food blog world. The magazine Saveur hosts the longest running, most extensive set of food blogging awards of any organization. I used their awards nominees and winners to pull together the graphic above and find out how gender and success in food blogging interact.

Using the Saveur awards data, it is clear that there is a pattern of disproportionate male success within the food blog nominees and winners. In a perfectly gender-neutral world, we would expect that when 15% of the food blogs are written by men, 15% of the food blogging awards will be distributed to men. In fact, 26% of the nominees (chosen by Saveur) were men and 36% of the winners (voted on by the internet audience) were men. In other words, both the Saveur selections and the internet-audience voters were inclined to select men more often than strict chance would have predicted.

My interviews indicated that there could be a few explanations for this kind of pattern. However, I’m curious to hear what food bloggers – especially those who voted for or won Saveur‘s awards – have to say.

The comments are open.

Methodological note

N=194

I removed blogs whose writers’ genders were not revealed and blogs written by couples or other mixed-gender groups. I also removed blogs that did not meet my original definition of food blog which include the two categories for blogs about alcohol and the category for blogs about kitchen tools/gadgets.

References

Saveur Food Blog Awards 2012.
Saveur Food Blog Awards 2011.
Saveur Food Blog Awards 2010.

Norén, Laura. (2012) Saveur food blog award nominees and winners by gender, 2010-2012. [Blog post] Graphic Sociology blog.

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

SOPA Opera in Congress
SOPA Opera in Congress

Graphic Sociology opposes PIPA/SOPA

The proposed PIPA and SOPA legislation has been roundly criticized with solid, logical arguments here by danah boyd, here by Tarleton Gillespie who links to 16 other authors who have argued against SOPA/PIPA, and here in a letter Harvard Law Professor Laurence Tribe sent to members of Congress.

As someone who is a passionate scholar of collaboration (both in its cooperative and competitive forms), I worry about the legal and economic repercussions of SOPA/PIPA that have been brought up by the authors mentioned above as well as the negative impact the threat of discretionary censorship would have on the kinds of sharing and borrowing that have made the internet and digital files such a rich source of remixing, incremental improving, and all around innovation. There is no way I could put a dollar figure or other empirical metric on what might happen to remix culture (what the cool kids call it) or innovation (what the business schools call it) under a legal regime in which just about anyone can censor just about anyone else. I can say that the internet as we know it would cease to exist. I post things here on Graphic Sociology that I have designed and created without even mentioning Creative Commons or standard copyright or anything else. If people take my work and get something out of it, that’s fantastic. I don’t even care if they give me credit, though many creative people do, and for good reason. I’m afraid if PIPA and SOPA were to pass, fewer people would re-mix my work and that’s the best kind of use, as far as I am concerned. Reposting is fine, remixing is divine.

I also post the work of others and critique them as an academic, something that is legal under the fair use doctrine. I’m not sure how SOPA and PIPA would mesh with the particular provision of the fair use doctrine that I am exercising. Presumably, they can co-exist, but I certainly don’t have the resources to hire a lawyer and defend myself against anyone who might claim that I’m violating SOPA/PIPA. And as just one of a family of bloggers, any infringement claim against any blog post on the society pages could darken the entire site. So if someone got upset with me, that would mean lights out for Sociological Images, Thick Culture, and all the rest of the blogs here.

The rest of this post is written by guest blogger Alec Campbell of Reed College in Oregon.

 

Guest post by Alec Campbell, Reed College

 

What works

This graphic clearly shows that something caused a change between January 18 and January 19. That something was almost certainly the focused attention on SOPA and PIPA resulting from shutdowns, blackouts and other actions taken or led by a number of popular Internet sites (wikipdedia, reddit, the Social Media Collective, and even here at thesocietypages there was a blackout of sorts).

What needs work

The most important flaw in this graph is that it excludes members of congress who are undecided or whose opinions are unknown. Looking at the graph it appears that the distribution of opinion moves from 72% in favor before the Internet shut down to 39% in favor after. In reality the distribution is 15% in favor, 6% opposed and 79% unknown/undecided before the shutdown and 12% in favor, 19% opposed and 69% unknown /undecided after the shutdown. The two graphs aren’t comparable because they don’t include the same total number of observations. When comparing populations of different sizes one has to compare percentages which this graphic does not do.

In fairness, the article accompanying this graphic has links to much more detailed data on SOPA
and PIPA
that does include a full accounting of all members of congress. However, those data don’t allow for comparison over time, which is the central point of this graphic.

What I can’t figure out

It’s clear that there are fewer supporters on January 19 but it isn’t clear if the people who no longer support PIPA/SOPA now oppose it or if they are now undecided. Did the Internet action make converts or agnostics? Arstechnica is keeping a running tally of Senators who are now opposing PIPA, including many of the former co-sponsors of the bill.

The graphic could have used arrows to show movement from one of the three camps (supporters, opposers, undecideds) to help illustrate where the movement happened.

Why it Matters

None of this matters much if our interest is in the fate of SOPA/PIPA. It matters a great deal if we are interested in the power of Internet protest. This graphic is about the power of protest because the prominently displayed time dimension is only relevant to this issue. This graphic overstates the power of Internet protests by omitting the unknown/undecided category making it appear that people changed their minds overnight. Clearly, some did. The number of supporters dropped in absolute terms. However, the larger effect is in convincing people to publicly state their opinion or to finally make up their minds. It is entirely possible that the major effect of the Internet protest was to get congresspersons that were leaning towards opposition to publicly state their opposition and force some supporters to claim an undecided status. That is certainly something but it isn’t the same thing as changing supporters into opponents, which is what the graphic implies.

References

propublic.org following House support of SOPA

propublic.org following Senators support of PIPA

Lee, Timothy. (19 January 2012) PIPA support collapses, with 13 new Senators opposed. [blog post] arstechnica

The internet crosses the ocean
The internet crosses the ocean

What works

I like the colors in the graphic above, however, the version I found does not come with a key but if you click through you can see one. The internet does not always deliver material the way it was originally designed or in the way that we would prefer it.

So I went looking for the original, the one that would probably have had a key attached to it, and found this map of the same information instead.

The internet's undersea world | The Guardian
The internet's undersea world | The Guardian

I realize it is hard to see the tiny thumbnail of a graphic so you can either click through to the full version at the Guardian or look through the images I’ve distilled from the original below.

The internet undersea world | Thumbnail from the Guardian
The internet undersea world | Thumbnail from the Guardian

Besides the map above, which shows where all of the cables are laid out and is very similar to the colored version at the top of this post, the Guardian cartographers/infographic designers included useful contextual graphics. Often, there is much more to maps than just the map, and to fully understand why and how the geography matters, it is critical to understand characteristics of the relationship that are not available through the map alone. For instance, in the case of undersea internet cables, the paths and linkages indicate that connections between, say, New York and London are probably quicker than connections between Minneapolis and Leeds. But it is also useful to know how fat the cables are because this is a good proxy for their bandwidth. If the traffic between two points in this network approaches the carrying capacity of the cable, connections might slow down, there would be reasons to build more cables, and so forth.

Undersea internet cable width | The Guardian
Undersea internet cable width | The Guardian

The Guardian carried on with this sort of critical analysis by showing how submarine operations sell capacity to other carriers, who mostly buy it as back-up. On the busy trans-Atlantic route, 80% of the capacity is purchased but only 29% of it is being used. This kind of arrangement is in place for times when communication bandwidth needs spike far, far higher than normal and when cables are cut.

World cable capacity, inset | The Guardian
World cable capacity, inset | The Guardian

Discussion

I was turned on to ferreting out these maps by a book I’m reading by Michael Likosky called “Obama’s Bank: Financing a Durable New Deal.” In the book, Likosky points out that one strand of the global internet infrastructure was privately financed, though still heavily reliant on governmental cooperation.

He writes:

In 1995, the US West finalized an agreement fo the construction of the Fiber Optic Link Around the Globe (FLAG). This $1.5 billion project would run a fiber-optic cable from the United Kingdom to Japan. In the process, it would link up twenty-five political jurisdictions. It contributed to a series of interlacing global information infrastructure project. Although underwater telegraphic cables had been laid at the close of the previous century, this project represented the first ever privately initiated and financed transnational communications link of this size and scale. FLAG was only as strong as the public guarantees of the twenty-five licensing authorities involved in legitimizing the project. In other words, it was a transnational public-private partnership.”

I was left wondering who financed the other strands of this aquatic internet infrastructure, realizing that it was probably more reliant on the public sector than the private sector, which is why FLAG is so unique. One of the reasons this matters is that global communications connectivity makes the current trans-national spoke and hub pattern of US business development possible. Without high speed communications connectivity, it would not be feasible for multi-national corporations to situate call centers and other communications-heavy activities far from the hub of commercial activities they are supporting.

If the US Federal government was indeed responsible for some of the early undersea internet bandwidth, I wonder if they had an inkling of how that might impact the development of off-shoring. It has been argued, though maybe not recently, that off-shoring is a good thing because it puts environmentally and socially negative jobs outside of America. Then we can reap all the rewards of growth up the management chain by locating the better jobs here. Clearly, it is irresponsible to locate environmentally detrimental projects in places were regulations are lax for the sake of increasing profits here. The same argument holds with respect to social ills like poor safety standards for workers, child labor, inhumane hours, and other negative working conditions. Increasing the ability to communicate instantly with far flung places makes the spoke-and-hub pattern more possible.

What needs work

Neither of the maps show who paid for the cables or who generates what kind of revenue from their use. I really want to know. I was hoping the color-coded one might do that, but without the key it’s impossible to tell.

References

Likosky, Michael. (2010) Obama’s Bank: Financing a durable New Deal. New York: Cambridge University Press.

Johnson, Bobbie. (2008, 1 February) How one clumsy ship cut off the web for 75 million people. The Guardian, Technology Section. Map graphic by telegeography.com.

Blog reading and writing graph by gender, 2000-2010 | Pew Internet Research
Blog reading and writing by gender, 2000-2010 | Pew Internet Research

What works

This graphic was created using a wonderful, if not entirely complete, massive Excel spreadsheet summarizing interview results from the Pew Internet Project. There are many more questions than the three I looked at. I am primarily interested in how many adults write blogs and I was happy to see that the Pew Internet Research center has been asking adults about their blog reading and writing practices for about a decade. Just to give it context, I also plotted the percentage of adults using the internet at all.

I am also interested to see that women and men write blogs at about the same rate, these days, even though I know that they aren’t writing the same kinds of blogs. Food bloggers, for example, are overwhelmingly women as are baby bloggers (aka mommy bloggers, but using the term ‘mommy’ is too gender-restrictive). Political bloggers and tech bloggers tend to be male more often than not, though I know less about them.

What needs work

The interviews are different from year to year – some years I was averaging five or seven data points on the same question and some years I had only one (or, sadly, none). I wish there had been more years of data available on blog reading, for instance.

If I had one takeaway point it would be that we need to keep funding places like Pew to conduct detailed, ongoing research. I have found it invaluable to have access to their research and it makes the work I am currently conducting about food bloggers relatable to a wider body of practices.

References

Pew Center for Internet Research. Usage over time spreadsheet.
— If you cannot click on that link and automatically start a download, try downloading it from the Pew website

Magnatune Pricing | Evidence from Voluntary Musical Album Pricing
Magnatune Pricing | Evidence from Voluntary Musical Album Pricing

Voluntary Pricing

I put this simple bar graph together to illustrate the following text that I got from Yochai Benkler’s paper and he got from a paper about Magnatune pricing,

In the recent paper on Magnatune, the data revealed that over a five year period, 48% of users paid $8 per album where $5 was the minimum, and only 16% paid the minimum. Another 15% paid $10, 7.3% $12, etc., up to 2.6% who paid $18 per album. Payments were highly anchored around coordination focal points — for example, the drop down menu called “$8” the “typical” donation. While 48.05% of fans paid $8, only 2.93% paid $7.50 and 0.34% paid 8.50.

I wanted to see how these numbers looked as a graphic because it was a little hard to make sense of what was happening just reading about them. What concerned me was that Benkler seemed to have crafted his text to imply – but not state directly – that voluntary music pricing schemes lead people to pay more, not less, for their music. This would make a fantastic story, but for some reason I wasn’t entirely comfortable just going ahead with that implication tucked into my subconscious mind.

When I graphed it, I added a block on the lower end of the scale to help illustrate the fact that Magnatune will not sell albums below $5. So, if we were expecting a bell curve of payment choices, all of the people who might have paid less than $5 were bunched up at the $5 mark or priced out altogether. Maybe they grumbled and agreed to pay $5 when they would have chosen $2 or $3 or perhaps they just didn’t buy the album at all. It’s hard to say.

Of course, I wouldn’t really expect people to distribute their payments for an album along a bell curve. I would have expected more clustering around the lower numbers – why would people pay more if they could pay less? Especially because they may not have taken the time to listen to the whole album for one reason or another…so they are paying for something that is not completely known. We’ve all been there before – some songs on albums just aren’t as good as others.

On the other end of the spectrum are the people who not only have taken time to get so familiar with the music that they aren’t worried about the dreadfulness of the unknown. Benkler’s paper indicates that people who develop close relationships with the musicians through collaborative efforts or fansites might be willing to pay more as a sign of respect and admiration.

Getting back to the graphic as a mechanism for making sense of the information, the point is that there are actually FEWER people in the lower range than in the higher range. Nearly half of people paid the requested amount ($8) but where they deviated from the requested amount, more people paid decided to give more, rather than less.

How can we explain that irrational behavior? I’m guessing that it has something to do with the free riders, the people who aren’t paying anything at all. These are not people who are getting their music from Magnatune, these are the friends of those paying people who are sharing iTunes accounts and getting their new music for free. There are other ways to get music for free besides sharing iTunes accounts but I’m not trying to get into all that. My point is that, after having graphed this information, I feel reasonably assured that there are quite a few people who are listening without paying a thing. It doesn’t really matter to me how they are doing that.

What matters is that the shape of the graph and the distribution of payments that we can see leads me to believe that there ought to be a substantial proportion of people – at least 14% – who are free riders. That’s a very rough estimate, but it complicates the happy story that if musicians pursued voluntary pricing they might stand to make more. It’s hard to say if that’s true or not. I guess it’s nice to allow your biggest fans to ‘vote with their dollars’ and just shrug off the free-rider problem as being outside the pricing structure. If people don’t want to pay, they are going to find ways not to pay no matter how the pricing structure is set up. But if people DO want to pay more, they can only do so under a voluntary pricing scheme. If the prices are set, they cannot opt to ‘vote’ with their dollars and pay more.

*I stick ‘vote’ in scare quotes when I am linking it up to economic activity because I like to reserve the term voting for direct political participation rather than for political participation that is supposedly possible by participating in capitalist exchanges. I hardly think that consumer behavior is as critically important as electoral behavior. Not everyone agrees with me, but that’s not a topic for this post.

References

Benkler, Yochai. (2011) “Voluntary Payment Models” in Rethinking Music. Cambridge, MA: Berkman Center for the Internet and Society at Harvard University.

Facebook Privacy Settings 2005 Facebook Privacy Settings 2006

Facebook Privacy Settings 2007Facebook Privacy Settings Nov 2009

Facebook Privacy Settings Dec 2009 Facebook Privacy Settings 2010

What Works

If you are a New York Times reader or a facebook user you are probably aware that Facebook periodically makes changes to their privacy policy. These changes often anger advocates for privacy who then write articles about why they are upset and which settings Facebook users should change in order to protect their online privacy. There are also ongoing debates about whether or not it would be measurably detrimental to simply delete one’s Facebook account as well as whether or not there will continue to be social stigma related to pictures and wall posts of activities that are common enough (drinking, wearing bathing suits, sleeping in, telling little white lies).

Regardless of where you stand, it has been a little hard to understand just how Facebook’s privacy changes are, well, changes. The series of graphics above eliminate the need to read dry legalese (or even those New York Times articles) and allow us to see the changes. The graphic is interactive and I encourage you to click through and play around with it. Among it’s great features, it allows you to select the privacy settings so that you can see just which bits of your personal data you can still protect and which bits are out of your cyber control.

What Needs Work

There is nothing that needs work about this graphic – the author explains his methods and assumption, invites comments, provided this graphic from the motivation to make information free, and he provides full-disclosure about what he does for his day job (works for IBM Research at the Center for Social Software).

References

Holson, Laura. (8 May 2010) Tell-All Generation Learns to Keep Things Offline. In The New York Times, Fashion & Style Section.

McKeon, Matt. (May 2010) The Evolution of Privacy on Facebook. Personal website.

Nussbaum, Emily. (12 February 2007) Say Everything. New York Magazine, Features.

Perez, Sarah. (20 January 2010) The 3 Facebook Settings Every User Should Check Now. In The New York Times, Technology Section.

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feltron graphic:  cnn.com site traffic since launch day
cnn.com site traffic since launch day

What Works

Think about what this graphic could have been: basically just a line graph showing growth over time. Now look at it again. The little flags point out cnn.com’s busiest days and remind you what was happening on those days – Obama’s inauguration, the September 11th attacks, various other political happenings. Even if this graphic weren’t labeled ‘cnn.com’ I bet you would have been able to predict it was a news site just by looking at which days it had the most hits.

Other things to like: the little graph at the top showing global internet use to remind us that the growth of page views per day could largely be a function of the growing number of people who have access to the internet rather than an inherent growth in popularity of cnn.com. Of course, the little bitty bar graph isn’t big enough to see if there is a difference in the growth rate in access to the internet overall and the growth rate in page hits at cnn.com.

Mirroring the trend over the x axis is a brilliant move here. On top, we see the page views per day averaged over the week in red and the annual weekly average. This allows them to go granular with their highest hit days and also give a trend line that smooths over the outliers. Nice. And on the bottom, then, they can show basically the same trendline broken into content areas. So if you’re a skeptic and you think all this growth is probably in entertainment because folks are just nitwits feasting on celebrity-ism, well, you can see that the home page gets by far more traffic than the entertainment page. It’s possible that the nitwit theory holds, but folks aren’t turning to cnn for juicy gossip. We can also see that video takes off and politics has more page views in election years.

And on Christmas, the number of people ignoring cnn peaks.

From Feltron, the graphic’s designer, the best thing about the narrative depicted by this graphic is the trust we all put in the internet as a reliable source of news after 11 September. “Ultimately, I think the most fascinating story here is the change in our news habits after September 11, 2001. After this day, a new and higher baseline for visits to the site is established, and the inference is that this event really established CNN.com and the greater Internet as a reliable, timely and indispensable source for news.”

What needs work

This is a sophisticated, well developed graphic that basically needs no work.

But…

The text is too small to read. Of course, it’s virtually impossible to create a graphic with this much detail that is elegant and uncluttered with text that fits in 800 x 800 pixels, or thereabouts. For folks who happened to have the ever widening monitors, it would have been nice to link to a ginormous version. I bet feltron has a larger version since I’m not sure how he would have been able to convince himself that some of the smallest text was legible otherwise.

References

Feltron (2009, 11 November) cnn.com traffic graphic on Feltron’s blog at tumblr.com.