August 18, 2014

Mapping Ferguson Tweets, or more maps that won't change your mind about racism in America

This post is the culmination of the Inaugural #IronWilson Map-a-Thon, held on Saturday, August 16th, and is the result of a collaboration between Matthew Wilson, Eric Huntley, Ryan Cooper and Taylor Shelton. 

A little over a week ago, the streets of Ferguson, Missouri, a suburb of St. Louis, were disrupted by the shooting of 18-year-old Michael Brown by Ferguson Police Officer Darren Wilson. While the details have been slow to emerge, the reaction to the killing of yet another unarmed young black man has been anything but -- whether in the form of street protests in Ferguson, or the online reaction to the news as seen on Twitter. The following graphic, produced by Twitter and published online by the Washington Post, demonstrates a typical representation of what we might call ‘#hashtag frenzy’, as people around the country take to Twitter to react to and comment upon the news. 

While certainly flashy and eye-catching, these so-called ‘animated ectoplasm maps’ tend to be short on meaningful insights. These visualizations show little more than population density in the US, and are remarkably similar from one trending topic on Twitter to the next. There is no attempt to normalize the data by population or overall levels of tweeting in a given place, thus obscuring both more detailed spatial patterns and broader social meanings that might be drawn out of such data. Still, maps such as this are useful in demonstrating the waxing and waning attention span toward issues of social importance, including the registering of yet another gun-related and police-initiated violent event, something that this blog post itself contributes to; therefore, in full admission of ‘yet another Twitter map of racial violence’...

We collected all geotagged tweets referencing a series of keywords -- 'Ferguson’, ‘handsup’, ‘mikebrown’, ‘dontshoot’ and ‘handsupdontshoot’ -- from Saturday, August 9th when the shooting occurred through the morning of Friday, August 15th, in an effort to provide a bit more resolution and, hopefully, insight into the ways and places people were tweeting about the protests. Starting with the first geotagged tweet referencing the shooting, we collected a total of 38,450 tweets. 'This tweet came from user Johnny__Tapia at 3:11pm Central Time on Saturday, saying “Ferguson police just shot a kid in the head in the middle of the street. 17 yrs old. Ain’t nobody saying what he did” [1].

In the several days following the shooting, news spread quickly over Twitter, with social media providing a key source of updates and information in lieu of any official reports or communication from the Ferguson Police Department. The map below, made by Eric Huntley, aggregates all the tweets in this dataset to hexagonal cells across the continental United States, and normalizes it relative to the overall amount of tweeting in that location at the same time. In other words it shows the relative focus of tweeting related to Michael Brown’s shooting (and the subsequent protests and police crackdown) compared to overall tweeting activity by location. In this map lighter shades indicate relatively more tweets about Ferguson than the national average.

The national and international media coverage of the story in Ferguson points toward the notion that this event transcends the local; there is something about it that speaks to people from any number of places and walks of life. For example, the aforementioned WaPo article ends with the relatively meaningless maxim, “People are watching from as far away as Fiji and Ghana. That's the world we live in now.” While discussions of increased police militarization and the persistent legacy of racism have certainly resonated strongly with a national audience, it is evident from our more-than-just-dots-on-a-map approach that the tweeting around this event is actually most prevalent in the general vicinity of where the shooting occurred: the St. Louis metropolitan area. The proportion of tweets on the topic is higher in and around St. Louis than anywhere else in the country, while other cities around the country have largely continued about their business, with lower levels of Ferguson-related tweeting relative to overall levels of Twitter activity [2]. While a few scattered and isolated areas throughout the country demonstrate a relatively high amount of tweeting about Ferguson -- mostly as a result low overall levels of tweeting -- the St. Louis region is really the only place that demonstrates a particularly concentrated and significant interest in the matter. In other words, "the world we live in now" is one in which spatial proximity and social connectedness remains incredibly important, even if people in Fiji and Ghana can follow along, too.

This lies in contrast to the aftermath of George Zimmerman receiving a ‘not guilty’ verdict last summer in his trial for the shooting death of Trayvon Martin, which is arguably the best parallel in terms of the public outcry and attention to the current Ferguson situation. Following Zimmerman’s verdict, large portions of the American South demonstrated a greater likelihood to use the #JusticeForTrayvon hashtag than other parts of the country, which we interpreted as indicative of Twitter users making connections between the events in Sanford, Florida and the broader legacies of racialized violence throughout the American South. Whether the different geographies of Twitter's reactions to these events are the result of different temporal evolutions (the immediate aftermath of the shooting vs. the trial verdict a year and a half later) or in divergent experiences, or perceptions, of racism between the South and Midwest [3], or something else entirely, is left to some level of speculation.

Despite the overall concentration of tweets in the St. Louis region, it also important to recognize that spatial unevenness exists at multiple scales, with respect to practically any phenomena. Indeed, the ability to examine such phenomena at a variety of scales is one of the major advantages to aggregating these points -- or individual tweets in this case -- to a uniform grid of hexagonal cells, as opposed to the more conventional, and largely arbitrary, Census-defined areal units. In the GIF below, created by Matt Wilson, you can see the spatial distribution of raw (i.e., non-normalized) tweets -- using the same dataset -- in the St. Louis metro area over time, beginning on Saturday when the shooting occurred, through the end of Thursday, August 14th [4].  

Given our lack of first-hand knowledge of St. Louis and its environs, we’re hesitant to draw too many conclusions from this data, though we certainly welcome any potential explanations from our readers. Because each of these snapshots is classified in the same way, we can see the diffusion of the news and growth in interest over time, becoming much more pronounced beginning on Monday. Tuesday is interesting insofar as it seems to demonstrate a much stronger clustering around Ferguson itself (the cluster of three dark blue hexagons north of downtown St. Louis), with the rest of the city actually seeing a decrease in tweeting about the event. This interest, especially in downtown St. Louis, ramps back up on Wednesday and Thursday, around the time of growing protests and the increasingly violent response from the Ferguson Police.

Ultimately, despite the centrality of social media to the protests and our ability to come together and reflect on the social problems at the root of Michael Brown's shooting, these maps, and the kind of data used to create them, can’t tell us much about the deep-seated issues that have led to the killing of yet another unarmed young black man in our country [5]. And they almost certainly won't change anyone's mind about racism in America. They can, instead, help us to better understand how these events have been reflected on social media, and how even purportedly global news stories are always connected to particular places in specific ways.

[1] It appears that this user has since deleted all of his tweets back to July 10.
[2] There is still a significant absolute amount of tweeting in these places, there just also happens to be a generally massive level of tweeting about other topics, as well.
[3] Of course, St. Louis, like pretty much everywhere in the United States, has it’s own important legacies of racism. For example, please see: Deep Tensions Rise to Surface After Ferguson ShootingThe Most Racist City In America: St. Louis?, and The Century-Old Urban Policy That Divides St. Louis.
[4] These maps also use a somewhat smaller sample of tweets that have only exact latitude and longitude coordinates, so as to avoid using those tweets tagged to place names, such as ‘St. Louis’, which might give the impression that there were large contingents of tweeters at the geographic center of the city.
[5] Though data about racial profiling, as Ryan Cooper analyzed for us here, can point towards some potential explanations.

August 17, 2014

Mapping the #LouisvillePurge

The only way to introduce this post is to say that yes, a bunch of really naive and/or, in the case of the local television news media, willfully idiotic, people thought that there was going to be a 'purge' -- a 12 hour period where all crime is made legal -- in Louisville, Kentucky on the night of Friday, August 15th, 2014. Starting with a single tweet from a local high school student, things quickly grew out of control, with #LouisvillePurge becoming a trending topic nationally by the time things were all said and done. While the best tweets referencing the purge made light of the phenomena, there were many, many more expressing confusion, fear, bewilderment and a desire to save the poor souls who might have been convinced to participate in such an event. But for all the attention given to the role of social media in spreading the hysteria [1], there's been no attempt to look at the where some of these tweets were coming from, and how the news spread over space and time.

While the tweet that kicked the whole ordeal off was created at 8:32pm on Sunday, August 10th, the first geotagged tweet with the #LouisvillePurge hashtag didn't show up for another couple of days, at 11:33pm on Wednesday, August 13th. Beginning with that tweet, we collected all geotagged tweets with the hashtag through noon on Saturday, August 16th, at which point things were dying down.

The map below shows the overall distribution of these 4,351 geotagged tweets, aggregated to hexagonal cells across the continental United States. While Louisville and the surrounding areas clearly have the highest concentrations, the discussion of the Louisville Purge was truly trans-local, with less than 25% of the total number of geotagged tweets coming from the Louisville Metro area. Of areas further away from Louisville in absolute distance, Houston, Dallas and Los Angeles represent some of the highest concentrations of tweeting about the (non-)event.

All #LouisvillePurge Tweets thru August 16th at 12pm EDT

But perhaps more interesting than just the overall spatial distribution is how this distribution evolved over time, from the first geotagged tweet all the way through the cycle of hype and hysteria that led the Louisville Purge to be featured on any number of national news websites. In the series of maps below, we have divided all of the tweets in our dataset into a series of (more-or-less arbitrary) time frames that give a good idea of when and where the news spread to other parts of the country [2].

The lead up to the purge demonstrates a relatively localized phenomenon within Louisville, though it's interesting that there is some extra-local tweeting from the very beginning, with a very small number of tweets coming from outside the state in West Virginia, Kansas, Texas and Florida. There were only a total of 182 geotagged tweets referencing #LouisvillePurge in this 44-hour aggregate time span, with tweets originating in Metro Louisville representing 55%, 66% and 60% of the total number of tweets with the hashtag during the three periods, respectively. In other words, talk of the purge spread quite slowly over the course of the week.

Time #1: 42 tweets
From August 13th at 11:30pm to August 15th at 6am

Time #2: 36 tweets
From August 15th at 6am to 4pm

Time #3: 104 tweets
From August 15th at 4pm to 8pm 

The number of tweets with the hashtag exploded right around 8pm on Friday night, the 'official' start time of the purge. This four hour time period represents the peak of tweeting activity around #LouisvillePurge, attributed largely to the fact that this is when the event started to diffuse outward beyond the city's boundaries to places both near and far. One can see both a significant increase in the amount of tweets across Kentucky, as well as to far-off cities like Los Angeles, Milwaukee, D.C., Philadelphia and New York City. From 8pm to 12am, the 757 tweets from Metro Louisville represent only 30% of the 2,533 tweets across the country, further highlighting the spatial diffusion of information about, and interest in, the purge. In fact, this measure of locally-concentrated tweeting drops even lower to less than 10% from the hours of midnight to 6am (when most Louisvillians would be asleep), though it again rebounds a bit higher to 23% during our final time span of 6am to noon on Saturday the 16th, after the purge has 'officially' ended.

Time #4: 2,533 tweets
August 15th at 8pm to August 16th at 12am

Time #5: 1,420 tweets
From August 16th at 12am to 6am

Time #6: 216 tweets
From August 16th at 6am to 12pm

Like our earlier research on #LexingtonPoliceScanner in the wake of the 2012 Kentucky Wildcats basketball championship, we can clearly see an ebb and flow in the way the event originates in a fairly localized area before gaining a larger following and eventually slowing down and becoming more localized again as many users reflect upon the aftermath. But unlike the attention paid to the #LexingtonPoliceScanner in large cities around the country, and especially the South, the interest in the #LouisvillePurge tended to be somewhat more diffuse, without any single location outside of the city or state paying a disproportionate amount of attention to the events.

In the end, we're happy to report that all of the Floatingsheep emerged from the purge unscathed and thoroughly amused, and we hope the same can be said for all of you and your loved ones. And do remember, don't trust everything you read on Twitter [3, 4]!

[1] Again, it's probably worth noting -- somewhat ironically, I suppose -- that despite the rumor originating and being passed around via social media, it was the traditional local television news networks whose willingness to believe and highlight the rumor drove further attention to the situation, which was almost obviously a farce from the very beginning.
[2] You can also access an animated GIF version of this time series map here.
[3] Especially if you are supposed to be a "real journalist"!
[4] For that matter, don't trust everything you see on the television news, either!

July 22, 2014

How Many Hobbits Could Chuck Norris Take In a Fight?

Inspired by the (relatively) recent Buzzfeed quiz, "How Many Five Year Old Children Can You Take In a Fight?" [1], we have been wondering about other potential battle royale matchups: Juggalos vs. Bronies, Juggalos vs. polar bears, Justin Bieber vs. Miley Cyrus and even goats vs. llamas

Perhaps our favorite attempt at recreating this kind of scenario is asking: how many hobbits could Chuck Norris take in a fight? The analysis was quite complex as we had to first set rules on the engagement (e.g., what kind of weapons? is mithril armor allowed or not? etc.) and decide which version of Chuck Norris (Walter, Texas Ranger Chuck Norris? Actual current Chuck Norris? Perhaps Delta Force Chuck Norris?) and what kind of hobbits (after all are we talking Brandybucks or Tooks? are these typical Shire hobbits or have they been abroad? etc.) we are talking about here.  

As you can suspect, there was a lot to sort out. But after much discussion and analysis we have come up with a clear answer but sadly, as the actual question has nothing to do with this blog, we've been forced to bury it in the footnotes [2]. What we can do, however, for the purposes of this blog is compare the distribution of references to hobbits, as opposed to references to Chuck Norris, in geotagged tweets. Starting from a 10% sample of all global geotagged tweets from July 2012 through March 2014, we collected all references to "hobbit*" and "Chuck Norris" to enable our comparison.

Hobbits vs. Chuck Norris, July 2012-March 2014

At the global level, there are actually quite comparable numbers of references to hobbits and Chuck Norris, thus making the location and scale of our hypothetical battle all the more important. There are 27,527 references to the man on Superman's pajamas, and 24,145 references to those short little guys with hairy feet.

What is evident, however, is that Chuck Norris isn't particularly popular anywhere but in the United States, as nearly half of the global references to him come from the USA, giving him a nearly 9000 tweet advantage over hobbits. Perhaps not everyone else in the world finds quite as much humor in the many Chuck Norris Facts as Americans do? Or perhaps other countries have their own Chuck Norris-like cult heroes to look up to [3]? The next closest country in terms of Chuck Norris appreciation is France, with just 250 more Chuck Norris tweets than hobbit tweets, followed up by South Africa, Nigeria and Puerto Rico in the top 5 countries favoring the man who predicted 1000 years of darkness were Barack Obama to be re-elected President of the United States.

Meanwhile, the top 5 countries favoring hobbits are Indonesia - where they hold a 2,141 tweet advantage - Turkey, Mexico, Spain and Malaysia, each of which have a greater than 500 tweet advantage for hobbits over Chuck Norris. A total of eleven countries have more than 100 more references to hobbits than Chuck Norris, a considerable feat given that only the top 3 Chuck Norris countries have a more than 100 tweet advantage.

In many ways, the pattern in this map is a replication of that from our recent map comparing references to Bieber and Miley; just as the only places with a real preference for Miley Cyrus were the USA and a smattering of African countries, so too are these the only places with a significant preference for Chuck Norris. Does this mean there is some sort of Chuck-Miley conspiracy afoot? Or that Bieber has taken command of an army of hobbits in his quest for world domination? We'll leave it to you to find out...

[1] See also: How many Justin Biebers could you take in a fight? How many 90 year olds could you take in a fight? How many hipsters could you take in a fight?
[2] The answer is zero.  Because hobbits are actually just fictional characters and Chuck Norris is a real living person. See? Sometimes there are clear and easy answers to tough questions.
[3] Ironically, of course, Kenya seems to display a slight preference for Chuck Norris over hobbits, despite Makmende's imposing presence.

July 08, 2014

A Quick Look at Global Language Patterns on Twitter

Today's post is derived from some testing we were doing within our data on language and since the results were interesting, we thought we'd share. This is a first step of a longer process of comparing language use at the global scale so much remains to be done.

Starting from a 10% sample of all global geotagged tweets from the calendar year 2013, we collected tweets that used a variety of non-Latin characters as a proxy for linguistic prevalence (see the map titles below for the list of characters searched). Using composite counts of what we found to be the five most commonly used characters in each of the given languages, we mapped normalized values at the country level in order to understand where these languages are most dominant. In other words, these maps represent the relative level of tweets containing non-Latin characters compared to all tweets; the US has plenty of tweets with Arabic, Chinese and Korean characters but these numbers are small compared to the overall number of tweets within the country.  

There are some issues with the data we collected -- for instance, we relied on non-definitive sources for our list of the most commonly used characters, and the constraints of the way we've structured our data makes (how we treat boolean queries and computing constraints) make our data somewhat incomplete. But still the initial results provide a reasonable snapshot of where Twitter is being used by people who don't speak languages which can be easily expressed in Latin characters. 

Arabic Characters:   ل   ن   م   ي   ا      

The spatial pattern of Arabic-language tweeting is interesting in that it seems to mimic a conventional distance decay effect. Saudi Arabia is the undoubted center of Arabic tweeting, with its immediate neighbors having relatively lower amounts, with their immediate neighbors having even lower concentrations, with practically no discernible differences once you reach Sub-Saharan Africa to the south, India to the east, or Europe to the north and west.

Chinese Characters:   的   一   是   不   了

While Japan has the highest absolute number of tweets containing Chinese characters, due to the fact that the Japanese language relies on written Chinese characters, the relative measure shows China to, quite unsurprisingly, be the center of Chinese-language tweeting. The territory of Greenland shows up as well, mainly because of the relatively low number of total tweets making the few tweets with Chinese characters relatively more frequent. We could, of course, account for this by requiring certain thresholds but for this initial look, we left it in. Given the increasing dominance of China within the global economy, it's somewhat interesting to see that there is very little Chinese-language tweeting happening in other parts of the world.

Korean Characters:   뭐   그   안   근데   거

The final language we explored was Korean and while it is not surprising that South Korea has by far the most Korean tweeting, it is interesting to note that North Korea, despite its almost complete disconnection to the global system, also appears on the map. Again, it seems that the scattering of relatively high scores for places such as Greenland and Somalia has more to do with the relatively low level of overall tweeting in these places than with some previously unknown concentration of Korean-speakers.

While there's not much definitive here, we believe this to be a useful, if incredibly brief, look at how online spaces such as Twitter remain connected to conventional, offline geographies, such as those of language and culture. And given the recent emergence of domain names in non-Latin characters, these maps might offer clues into the evolving geography of domain names, while also offering some potential for future research using such data.

July 01, 2014

The Drama of Llamas vs. the Gloating of the Goats

It should be no surprise to anyone that we're interested in sheep. But today we want to continue to mine the possibilities of our IronSheep 2014 dataset to bring you an alternative geography of animals as they are discussed and represented in social media [1]. Focusing on the global level and using a 10% sample of all geotagged tweets created between July 2012 and March 2014, we sought out to understand the global distribution of goats as opposed to llamas. 

Because, you know, it's important. Or perhaps because we're a bit bored.

While goats and llamas don't carry the same inherent antagonism as, say, bronies and juggalos [2], we thought it might be interesting to see how the two compare across the world since they are both major competitors to our favored sheep in the world of livestock [3]. At the most general level, llamas are absolutely dominant, with nearly triple the number of tweets as those mentioning goats, with 63,606 references to llamas and 24,322 references to goats. Of course, one does wonder, what all this llama/goat discourse is about? Are people extolling the virtue of their animal, or mentioning a chance sighting, or perhaps talking about what's on for dinner? Or perhaps someone has finally invented a hoof-accessible mobile device and the animals are taking to the net?

In any case, these raw numbers certainly don't tell the whole story, although arguably llamas are much cooler and more interesting than goats, so as to warrant significantly greater tweeting about them.

Global References to Goats and Llamas, July 2012-March 2014

Indeed, by mapping the concentrations of each term relative to the other, we can see that while llamas are dominant overall, their spatial distribution is much more concentrated, while goats, though in smaller numbers, are much more widely dispersed throughout the globe. 

Llamas dominate livestock-related tweeting in Latin America. While perhaps unsurprising given their offline manifestation throughout South America, Spain and Mexico actually have the highest number of both absolute and relative references to llamas, despite neither being a native habitat for the animal. Further, only two countries in the top 20 for relative references to llamas are not predominantly Spanish-speaking: Brazil has 1,189 more references to llamas based on our 10% sample, good for 8th most, while France has 82 more references to llamas, making it the 20th-most llama-est country in the world. Also interesting is the fact that the only three countries in Latin America and the Caribbean which do not favor llamas over goats are not Spanish-speaking: Guyana, Suriname and Haiti.

Meanwhile, the United States and United Kingdom are the only countries worldwide to display significant preference for goats over llamas, with over 10,000 and 3,000 more references respectively, while Nigeria, Canada and Australia all show some moderate preference for goats. The fact that the US also has the fifth-most absolute number of references to llamas just goes to show how much people in the US love their goats. I mean, who doesn't love goats, especially when they sound like humans? Plus, they can eat all of your leftover beer cans!

While much of Africa's preference for goats is also largely unsurprising given that it has some of the highest levels of global goat production next to China and India (which are likely lower on the goat rankings due to linguistic differences), we are somewhat baffled as to why most of Europe has a preference for llamas. But then again, after watching the goat screaming video for awhile it all seems to make sense.

[1] But definitely not an animal geography.
[2] A quick Google search for "goats and llamas" will likely return a number of results for how farmers can use llamas to protect their goat herds. Should these results not show up for you, blame Google and their never-ending drive to collect massive amounts of personal data about you in order to create a personalized experience of the internet for you that never exposes you to such oddities or anything else you might find unseemly.
[3] The less said about cows the better.

June 24, 2014

To Bieb or Not to Bieb? The Geographies of Bieber and Miley Fandom

In our continuing effort to use the massive amount of social data available to us in order to uncover unforeseen, unusual and sometimes uninteresting facts about the world around us, we turn today to a question that has long troubled our world (or at least the part of it consisting of fourteen year-old girls): Bieber or Miley? 

While the once (sort of?) innocent teen pop stars have long since grown up, getting any number of ridiculous and ill-advised tattoos, twerking across your television screen and maybe even romancing one another, Justin Bieber and Miley Cyrus remain inextricably tied in the imaginations of those of us who mostly don't really know what's going on with the kids these days [1]. But by firing up DOLLY and looking at the global distribution of tweets referencing one or the other of these music icons, we can see that the two couldn't be more different in their geographic reach.

Our comparison is based on a 10% random sample of all global geotagged tweets between July 2012 and March 2014, which yielded a total of 165,406 tweets referencing "Bieber" and 99,146 tweets mentioning "Miley".

The first thing that's evident from this map is that Justin Bieber is truly "All Around the World", garnering more references to his name than Miley Cyrus' in most of the world's countries. And while Bieber's dominance starts in his native Canada and extends south throughout the Americas from there, Miley Cyrus comes in like a "Wrecking Ball" to have a real "Party in the USA", where she has a nearly 10,000 tweet advantage over the Bieber. Unfortunately for Miley, however, the US is really the only place where she is more popular than Bieber. Indeed, she only has any advantage whatsoever in 45 countries around the world, with most of these clustered in Africa and the Caribbean. Then again, maybe she's just getting "The Best of Both Worlds"?

And while Bieber's advantage extends through Europe and much of Asia, his dominance is actually most deeply rooted in Latin America. The country with the biggest difference favoring Bieber tweets is Brazil, with over 22,000 more Bieber tweets than Miley tweets, even in our limited dataset. This is likely due to Bieber's well-documented risqué escapades in the country. In addition to his absolute dominance in Brazil, Bieber has an advantage of over 1,000 tweets in 18 other countries around the world, from Indonesia, Mexico, Turkey and Argentina at the top of the list, to Sweden, Denmark and Paraguay at the bottom.

Forty countries have no geotagged tweets referencing Bieber or Miley, though many of these are small island nations with very little tweeting activity to begin with. We suspect that there is probably a development grant that these places could apply for to help make them Beliebers.

The most interesting thing is that no country with any significant amount of tweeting about these pop stars displays parity between the two. This leads us to posit that there has been a significant Balkanization of the Biebersphere [2], with no reconciliation between the two opposing poles of over-sexualized, tabloid headline-gracing teen pop stars who are now more known for their distasteful appropriations of other cultural traditions than for actually making music anyone wants to hear. Then again, if you want to get dialectical about it, there's really nothing oppositional about them. Hell, they even twerk together! And by making this map, we've now probably set society back at least a good couple weeks in our arduous process of learning to ignore them. Our apologies. Sometimes, "We Can't Stop" ourselves.

OK, seriously, we're done now [3].

[1] Seriously, turn that music down! And get off of our (virtual) lawn!
[2] If you're wondering why we suddenly decided to invent the term 'Biebersphere' to refer to Twitter, look no further than the fact that Justin Bieber remains arguably the largest single topic of conversation on Twitter. It's frankly sort of amazing how many people tweet about him on a regular basis. And yes, this does utterly depress us about the state of humanity.
[3] Although, "Never Say Never".

June 10, 2014

Crowdsourcing Cake or Death?

Following up on our recent trend of finding inspiration for our maps in various oppositions that we've encountered in our day-to-day lives, we turn today to the seemingly obvious question posed by Eddie Izzard: cake or death? 

While this should be a no-brainer for us, we thought we'd crowdsource the answer to this question, turning to the collective wisdom of the geographically-referenced tweet machine. We draw on a dataset of all geotagged tweets mentioning "cake" or "death" between July 2012 and March 2014 [1]. Given that cake is so much more pleasurable than death, we expected Twitter references to show a similar preference. But the results might surprise you. 

Humans, apparently share a similar fondness for talking about cake and death. Extrapolating from our 10% random sample of global tweets, there are approximately 1,302,310 mentions of cake during this time, as opposed to 1,314,880 mentions of death.

Global Geotagged Twitter References to Cake or Death, July 2012-March 2014

The death loving nations of the United States, Nigeria, Canada, South Africa, and India clearly stand out on the map. Cake, on the other hand, is a much more frequent topic of conversation in the UK and a handful of Southeast Asian countries including Indonesia, Malaysia, the Philippines, and Thailand.

Among countries with a significant number of references to both cake and death, the Mediterranean countries of Lebanon and Greece, along with the Caribbean nations of Trinidad and Tobago and Barbados are the only ones that could be said to have found a nice balance between cake and death.

The real question here is, why do some countries prefer death over cake? It is understandable that Canadians are locked in a deep cake-less existential crisis (we would be too if we lived there), while South Africa has one of the world's highest murder rates. But why is the US so infatuated with death?

Geotagged Twitter References to Cake or Death in the USA, July 2012-March 2014

If we zoom into the world's most death-loving country, death is, well, pretty much everywhere around you. Death to everyone, indeed. In absolute terms, there are a total of 162,205 mentions of death in the US, as opposed to 845,923 mentions of cake, but the geographic distribution of these references is all the more stark and, dare we say it, troubling. If you happen to live in or, god forbid, be passing through the post-industrial towns of Michigan, Ohio or Pennsylvania, or the BosWash megalopolis, death is really everywhere around you. From the frozen tundra of the north to the sunny retirement hotspots of southern California, Arizona and Florida, you can't really escape it.

That is, unless you live in one of a handful of cities or towns smattered throughout the south and Great Plains. If, by choice or extreme luck, you happen to live in Atlanta or in one of several Texas cities -- from Dallas to Waco, down to Houston and all the way to Brownsville in the southern portion of the state -- you may be able to revel in the joy of boundless cake. Given the widespread dominance of death in other places, it is only natural to assume that cake will essentially become so abundant as to be given away for free at all restaurants and grocery stores. May we all be so lucky! [2]

[1] Yes, this is another missed opportunity from IronSheep 2014!
[2] This, of course, doesn't account for the fact that too much cake consumption will likely lead to obesity and then, yes, death.