What do Twerking and Syria have in common? Not much, except for the Twerking Tramp Stamp of America

User-generated data, especially generated via social media, provides a useful look into the day-to-day experiences and conversations that occur around the world. This kind of data provides insights, however partial, into our hopes, our triumphs and our fears. Sometimes it reveals things that we would rather not think about, like hate speech or racially charged discourse. But in all cases, it enlightens us to what matters to people, or at least what matters to the people participating in online discussions.

The past month has seen a sharp increase in two topics of discussion, the first representing an African American cultural meme from the bounce music tradition of New Orleans but more recently (and cynically) appropriated by white pop artists, and the other tied to an ongoing conflict that rapidly garnered calls for international intervention. We speak, of course, of twerking [1] and the ongoing civil war in Syria. While the two topics share little in common apart from recent media attention, the divergences between the space-time patterns of these geo-coded tweets show how online and offline actions and characteristics are intricately and imperfectly connected.

Using DOLLY, we extracted all geocoded tweets from July 1, 2012 to September 11, 2013 from North America that referenced either "twerk*" or "syria*". It quickly became apparent that twerking is a much more popular topic on Twitter, with 775,000 geocoded tweets during this time period, while there were only 75,000 references to Syria [3]. These numbers have changed significantly over the past month as the U.S. has called for military strikes in response to reports of chemical weapon attacks in Syria, but nevertheless there have still been three times as many references to twerking as Syria in August and September, with 133,000 tweets against just 43,000.

Indexed Volumes of Twerk and Syria Tweets, July 2012 to August 2013

The evolution in volume of each kind of tweet overtime is also strikingly different.  Compared to the number of mentions in July 2012, twerking has steadily become a more popular topic of Twitter conversations over the course of the past thirteen months. In contrast, discussion about Syria largely declined over the course of the year, and only in August did it became a hot topic. Since July 2013, the relative amount of conversation about Syria increased almost tenfold, from an index value of 61 to an index value of 526. Though they took much different trajectories, both topics have around five times as much discussion as was the case a year ago.

Looking at the geography of these tweets, just for the month of August 2013, illustrates how tweeting behavior varies across space during a time when there was a lot of national attention to both topics. Using a simple ratio of the # of Syria Tweets / # of Twerking Tweets, which we term the Twerkyria Index, the maps below show this distribution at the state and county levels.

The Twerkyria Index by State, August 2013

One of the most compelling results is the clear difference in ratios for Washington D.C., which has three times as many Syria tweets as twerking tweets, bucking the national average which is three to one in the opposite direction. The next closest areas are Vermont and Alaska, with relatively small African American populations, which have roughly the same number of tweets for each topic. The rest of the country is divided into red states that have more than the national average of twerking and pink states that are slightly less twerking obsessed (at least relative to attention to events in Syria). The concentration of states in the southeast -- from Texas to South Carolina -- forms a Twerking Tramp Stamp across America [4], with a few other concentrations tastefully tattooed across the Great Plains and Midwest.

The pattern suggests a number of possible connections between the Twerkyria index of Twitter activity and offline demographics. Despite Miley Cyrus's "act of cultural appropriation being passed off as a rebellious reclamation of her sexuality after a childhood in the Disneyfied spotlight", twerking's roots are within
African American culture, especially as it relates to southern hip-hop. In this context, sending a tweet containing twerk is likely much more about cultural expression of local and identity politics than the more recent appropriation of the work by the dominant culture to work through "a raft of personal, socioeconomic and third-wave-feminist issues". Likewise, tweets containing Syria represent a wide range of political views and stances towards possible U.S. intervention.

In short, it's complicated. Far from a simple unitary meaning, the use of both twerking and Syria on Twitter are complicated expressions of cultural and political expression in the U.S., relating these locations both to particular regional cultures within the country and particular geopolitical configurations that span the globe.

In an effort to test some of these relationships, we ran a quick (and relatively crude) OLS regression at the state level with the Twerkyria index as the dependent variable and a range of demographic variables including:

• Population under 18 years, percent, 2012  
• African American Population, percent, 2012 
• Median value of owner-occupied housing , 2007-2011
• Population per square mile, 2010 

The model excludes Washington DC, given that it is a city rather than a state [5] and includes dummy variables for Hawaii and Alaska given their unique spatial position vis-a-vis the lower 48 states.

Modelling the Twerkyria Index

While there are any number of ways to critique/improve upon this basic model, it works well for simple illustration [6]. The model explains about 65% of the variation in the Twerkyria Index. States with younger populations and a higher percentage of African Americans are associated with more twerking tweets. Interest in foreign affairs is more difficult to measure (at least with standard Census data), but a combination of housing price and population density provides a measure of a state's urbanity and presumed interest in international affairs. Locations with more expensive real estate and higher population densities, i.e., more urbanized states, have relatively fewer tweets about twerking and more with Syria. This model shows that the Twerkyria Index correlates fairly well with some reasonable theoretical expectations about the nature of the offline demographics of the points of origin of these tweets.

The Twerkyria Index by County, August 2013

The state level, however, masks many of the subtle distinctions that emerge within these relatively large spatial units.  Examining the Twerkyria index at the county level (see below) shows that the higher number of Syria tweets in Washington DC is also evident in a number of counties, roughly equal in size, to the district. While these counties are scattered across the country, a particularly large concentration is found in the San Francisco Bay with Alameda County, containing Oakland and Berkeley, representing the source of fully 8% of all Syria-related tweets. Given this large concentration, it is not surprising, that the Twerkyria Index diverges greatly from the rest of the country. In contrast, southern California largely conforms with the larger national trend of tweeting considerably more about twerking.

In summary, we have no easy answer to the age old, "To twerk, or not to twerk" [7], but looking at the socio-spatial dimension of online activities provides useful insight on the complicated interconnections between our online and offline activities.

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[1] For those few unaware of what twerking is, we refer you to the Wikipedia definition, which defines it as "a type of dancing in which the dancer, usually a woman, shakes her hips in an up-and-down bouncing motion, causing the dancer's buttocks to shake, "wobble" and "jiggle".  If you still have trouble understanding it we suggest this thoughtful overview provided by the New York Times. After all, where else would one go to truly understand an artifact of twenty-century African American urban culture than the grand grey lady of journalism?  Or you could view the three videos at YouTube with the most hits 1) Booty Me Down Song By Kstylis; 2) How to Twerk and 3) Jimmy Kimmel Reveals "Worst Twerk Fail EVER - Girl Catches Fire" Prank".

We're still working on obtaining video of someone from the FloatingSheep collective twerking but an array of technical and legal difficulties have prevented this thus far. [2]

[2] Also the fact that no one has volunteered has been a bit of problem. But we have high hopes that we'll eventually wear Mark's resistance down.

[3] For sake of international comparison, the UK has 26,607 tweets on Syria and 28,342 tweets containing Twerk.  Apparently, twerking still has room for expansion in Britian.

[4] Not to be confused with the Beer Belly of America, which is an entirely different socio-spatial phenomenon that we anthropomorphized into a regional definition.

[5] Although models that include DC actually have a higher r-squared. It just seems better to exclude it from a state level model.

[6] Seriously, this is just a blog post comparing twerking and Syria. For this, you expect peer review?

[7] Except in the case of Mark (see [2]) in which case the answer is yes.

Hiring a full-time researcher to work with Mark at the Oxford Internet Institute

The Oxford Internet Institute is hiring a full-time researcher to work with Mark on an ESRC-DFID funded project, The Promises of Fibre-Optic Broadband: A Pipeline for Economic Development in East Africa. Employing case-studies, interviews, surveys and textual analysis in Kenya and Rwanda, this project examines the expectations and stated potentials of broadband Internet and compares those expectations to on-the-ground effects that broadband connectivity is having in three economic sectors: tea production, tourism, and business process outsourcing.

This is an exciting role in which the Researcher will conduct in-depth qualitative research on the topic of connectivity, value chains, information flow, and exclusion in Rwanda. The researcher will also contribute to the dissemination of this work through academic papers and project reports.

Candidates should have experience of social science research in Development Studies, Geography, Sociology, Social Anthropology, Communications, or related disciplines and a strong record of training and practical experience in qualitative research methodology.

Based primarily at the Oxford Internet Institute (with periods of fieldwork in Rwanda), this position is available from immediately for 10 months in the first instance, with the possibility of renewal thereafter, funding permitting. We will soon be starting a multi-year project focusing on knowledge economies in Sub-Saharan Africa. We would therefore also welcome applications from candidates who are keen to be part of a larger research programme in order to extend the position.

The deadline is September 27 and interviews for those short-listed are planned to take place on October 15th and 17th. More info and an application package is available here, but feel free to get in touch if you have any question about the job.

Schmos, Schmucks and Schlongs, Oy vey!

Oy vey. It has been a very busy, long summer and due to some glitches we've fallen behind in producing posts for the blog like some kind of nebbish. We could kvetch some more but no one likes a nudnik and beside we know all of our readers are real mensches and won't complain and become pains in our tukhus.

Besides, Rosh Hashanah is upon us and we have just enough time to power up the patented FloatingSheep mapping chutzpah and create a special holiday post... Mazel Tov!

And in case you haven't figured it out, today's theme is Yiddish, that wonderfully expressive language of the Jews of central and eastern Europe and more recently (by which we mean the past century) of New York. Drawing from the DOLLY database, aka the golem of the geoweb, we compiled maps of tweets in the USA for the most common yiddish words used in English. Ok, well, Wikipedia complied the list and we made the maps.

Since it is a holiday, we'll keep things short and simple. A key finding is that Yiddish words are alive and well on Twitter within the US, albeit primarily used as single words rather than in whole phrases or sentences. For example, there is a whole lot of "Oy" and "Oy vey" in the Twitterverse. Likewise, the surprisingly long list of Yiddish terms for penis (putz, schlong, schmuck) are running amuk like some kind of meshuggener, which upon reflection makes sense. Nosh is also very popular relative to other Yiddish terms, such as the delightful zaftig which is not as heavily used.

Below, you'll find a series of maps showing how these various terms are distributed across the U.S. Shalom.

Yiddish words are predominantly used in large cities in the US. The map of Yiddish speakers on Wikipedia suffers from the modifiable area unit problem, so not aggregating to the level of the state is more illustrative here.

chutzpah: nerve, guts, daring, audacity, effrontery (Yiddish חוצפּה khutspe, from Hebrew)

kvetch: to complain habitually, gripe; as a noun, a person who always complains (from Yiddish קװעטשן kvetshn 'press, squeeze', cf. German quetschen 'squeeze')

People in the north east kvetch more on Twitter than in other areas of the country.

mensch: an upright man; a decent human being (from Yiddish מענטש mentsh 'person', cf. German Mensch) 

nosh: snack (noun or verb) (Yiddish נאַשן nashn, cf. German naschen)

oy or oy vey: interjection of grief, pain, or horror (Yiddish אוי וויי oy vey 'oh, pain!' or "oh, woe"; cf. German oh weh) 

schlep: to drag or haul (an object); to walk, esp. to make a tedious journey (from Yiddish שלעפּן shlepn; cf. German schleppen)

schlong: (vulgar) penis (from Yiddish שלאַנג shlang 'snake'; cf. German Schlange)

There was more intense discussion of schlongs in smaller cities and suburbs throughout the United States.

schmo: a stupid person. (an alteration of schmuck; see below)

schmuck: (vulgar) a contemptible or foolish person; a jerk; literally means 'penis' (from Yiddish שמאָק shmok 'penis', maybe from Polish smok 'dragon')

schmutz: dirt (from Yiddish שמוץ shmuts or German Schmutz 'dirt')

schnoz or schnozz also schnozzle: a nose, especially a large nose (perhaps from Yiddish שנויץ shnoyts 'snout', cf. German Schnauze)

shtup: vulgar slang, to have intercourse (from Yiddish שטופּ "shtoop" 'push,' 'poke,' or 'intercourse'; cf. German stupsen 'poke')

Shtup is used evenly across the country, perhaps as a misprint for "shut up" in conversations, but then again shtuping is a popular activity across time and space.

spiel or shpiel: a sales pitch or speech intended to persuade (from Yiddish שפּיל shpil 'play' or German Spiel 'play')

Spiel is used more in small cities, such as around Marion, Illinois and Sandusky, Ohio.

tush (also tushy): buttocks, bottom, rear end (from tukhus) 

yutz: a fool 

zaftig: pleasingly plump, buxom, full-figured, as a woman (from Yiddish זאַפֿטיק zaftik 'juicy'; cf. German saftig 'juicy') 

There is no particular pattern of where 'zaftig' is used more, apparently the pleasingly plump are distributed throughout the continental United States.

Visualizing the Relational Spaces of Hurricane Sandy

Nearly a year ago, Hurricane Sandy made landfall on the eastern seaboard of the US, wreaking havoc on the lives of millions of people in its path. At the time, we threw together some quick maps of where Sandy was being talked about on Twitter, and how the geographies of Sandy-related tweets were both intensely connected to the material impacts of the storm, but also somewhat incongruent.

Since then, we've been putting the finishing touches on a paper that extends our initial interest in the data shadows of Hurricane Sandy to a more comprehensive look at how we can use Sandy-related tweeting to understand the multidimensionality of the geographies of social media activity. All too often, a one-to-one connection is made between the location of a geotagged tweet or other piece of social media content and the content of that tweet [1]. We have instead been attempting to understand how we can think through, and then visualize, how geotagged tweets reflect and produce much more complex socio-spatial relations, which include both intense connections to the places where such content is produced, as well as much more physically distant locations which are brought closer in relational space through such informational flows. The rest of this post is adapted from our paper-in-progress, and outlines how we can map and measure the relational spaces of Hurricane Sandy.

Using T-100 Domestic Market data from the Research and Innovative Technology Administration (RITA) on flights and the number of passengers between city pairs in 2012, we determined the 50 cities that have the most passenger traffic with New York City, ranging from Chicago (3.5 million passengers back and forth) to Kansas City (175,000 passengers). Since operations and activities at some airports close to New York were directly affected by Sandy’s landfall, we exclude any airport within 500 kilometres of Manhattan in this analysis. For the remaining airports we used a buffer of 5km to collect all Hurricane Sandy related tweets and calculated the lower bound of the odds-ratio (or location quotient).  This metric measures the level of Hurricane Sandy tweets relative to overall Twitter activity . If relational networks did not play a significant role in Sandy-related tweeting, one would expect to see a direct distance decay effect: as the distance from New York City increases the odds-ratio should decrease.

Twitter Activity vs. Physical Distance

Our map shows, however, that physical distance has no significant relationship with the relative level of tweeting activity about Hurricane Sandy as is evidenced by both the scatterplot and the map (Spearman’s rho is -0.05). The map uses an azimuthal equidistant projection with New York City as the center, where the size of each airport is proportional to its odds ratio. Airports that are equally distant in physical terms from New York have widely diverging measures of Sandy-related Twitter activity. In addition, the average odds ratio in each 1000km zone does not decrease the further away one travels from New York.

In contrast, a slightly altered version of our map shows that the number of passengers between each city and New York City exhibits a much stronger positive correlation with the odds-ratio metric of Twitter activity (Spearman’s rho is 0.34). This figure preserves the directional bearing of each city with respect to New York City, but instead uses an inverse of the number of passengers to recalculate the relational distance between the cities. Airports are thus no longer displayed according to their physical distance from New York City, but rather based on the intensity of air traffic between the two cities. Since the bearing has remained the same, airports with a higher intensity will move closer to New York along that line, and vice versa. In addition to the correlation coefficient, we can also visually determine that cities with a lower odds-ratio, such as Pittsburgh and Memphis, have a tendency to move towards the outer circles while cities with a higher odds-ratio, such as San Francisco and Los Angeles, move relatively closer.

Twitter Activity vs. Air Traffic Interactivity

In other words, it is the relational connection to New York, measured by number of air travelers, not physical distance, which better explains the level of concern with Hurricane Sandy as expressed via Twitter. This concern, however, can vary within metropolitan territories depending upon the scale of analysis; some parts of an urban area may have much stronger relational ties to distant cities, while other parts are largely disconnected from such global flows.

To test the extent to which the data shadows of Sandy-related tweeting are a localized phenomenon within certain parts of metropolitan areas (rather than a more generalized territorial phenomenon), we increased the initial buffer around each airport from 5km to 25km. Thus, rather than just capturing neighborhoods that are spatially proximate to the airport, this measure captures a much wider swath of each metropolitan area. With this larger buffer, there is a near-reversal of the correlations illustrated in our first map, as Pearson’s rho for total number of passengers is now 0.06 (rather than 0.34), while the distance effect starts to emerge (rho is -0.15). In other words, even though the sociospatiality of a phenomenon like Sandy is expressed partly through a network of connections between territories, these connections are very much bounded by the locally-specific practices of place. This once again highlights the complex ways in which the digital data shadows of a material event are manifest through the intertwinement of different dimensions of social space.

As evidenced by these examples, Sandy’s data shadows are not evenly distributed through the continental United States. They are instead quite intense in some locations, while hardly reaching others at all, demonstrating the multiple spatial dimensions of social processes such as the response to Hurricane Sandy.
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[1] We're as guilty of this as anyone.

Tweeting for Trayvon

While the not guilty verdict is in for George Zimmerman, the discussion about and ramifications of Trayvon Martin's killing seventeen months ago are only beginning, from protest marches throughout the country to tweeting with hashtags like #MillionHoodies. Plenty of people smarter than us have weighed in on what this means for the persistent racism and inequity of the justice system in the United States, so we'll leave that side of the analysis to them. But as we specialize in thinking about and analyzing the geographies of social media, we want to offer our own two cents on what we can collectively take away from the case based on an analysis of geotagged tweets reacting to George Zimmerman's acquittal for Trayvon Martin's slaying.

First, some quick notes on our methodology and general trends in the data. Using DOLLY, we collected all the geotagged tweets from July 1 through July 15, referencing either "JusticeForTrayvon" or "Not Guilty", capturing the usage of these phrases with or without an accompanying hashtag. There were a total of 27,863 tweets referencing "Not Guilty" in this time frame, and just 6,614 referencing "JusticeForTrayvon". We calculated location quotients using hexagonal binning in order to normalize the data based on a relative measure of tweeting activity, as well as to account for differential size of counties or other similarly arbitrary areal units [1]. More simply, this allows us to compare the relative level of Twitter activity in any particular location, rather than relying on raw counts which are biased by population density.

Timeline of Tweets Referencing "Trayvon" from July 13th-14th

In addition to our primary interest in the spatial dimension of tweeting, we're also able to visualize a timeline of tweeting activity, which shows a clear spike immediately following the verdict on Saturday evening around 10 pm. While we're sure that many people's timelines were filled with reactions to the verdict throughout the day on Sunday, it seems as though much of the tweeting became more dissipated throughout the day as protests heated up and others went back to their usual routines.

Taking a look at the spatial patterns of these keywords, there are some clear differences. While there are many fewer JusticeForTrayvon tweets overall, they tend to be generally scattered, but with some relative concentrations largely in the south, in cities like Shreveport and Alexandria, Louisiana and Durham, North Carolina. Again, these measured are normalized for overall level of Twitter activity and thus show that these places were more engaged in this topic via Twitter than other parts of the country.

References to Not Guilty, however, in addition to being far more prevalent, demonstrate significantly more clustering in areas of the country outside the south, especially in Texas (depending on whether or not you consider it to be Southern) and some of the Midwestern or Mid-Atlantic states. We should note that there is a greater concentration references to Not Guilty in the vicinity of Sanford, Florida, the location of Trayvon Martin's killing and the subsequent trial, than was visible in references to JusticeForTrayvon. 

It is also important to note, however, that large cities on the west coast, like Los Angeles, San Francisco and Seattle, have relatively little tweeting about the case for either term, as do major cities along the eastern seaboard, like New York, Boston, D.C. and Philadelphia, despite being the sites of the major protests following the verdict.

Comparing references to the two terms -- while keeping in mind that they are not entirely oppositional, i.e., "Not Guilty" is a much more neutral and contextually dependent phrase than JusticeforTrayvon, which explicitly 'takes sides' in this debate -- reveals a much clearer geographic pattern. This comparison brings the different geographies of these phrases into a stark contrast, with many more references to JusticeforTrayvon concentrated throughout the southern states of Arkansas, Louisiana, Mississippi, Alabama, Georgia and Kentucky (highlighted in purple), with a greater number of more generic references to the verdict (highlighted in green) scattered throughout much of the rest of the country. In short, the hashtag that is more closely associated with protesting the outcome of the court case, is more highly concentrated in Southern states.

One thing that is clear is that although the experience of racism isn't unique to the American South, it is uniquely associated with and experienced in that place when viewed through geotagged social media content [2]. This isn't to say that the tweeting about the case throughout the south is, in and of itself racist, as many, if not most, tweets express outrage at Zimmerman's acquittal, as evidenced by the large number of tweets referencing the JusticeForTrayvon hashtag. But given the back-and-forth around the particularity of racism in the south or the universality of racism across the United States, the higher concentration of this Twitter discussion within the region suggests a process distinct from the rest of the country.

The fact that Trayvon Martin's killing took place in Florida, which shares a similar history with regard to race as the rest of the south, has clearly elicited a broader reaction from those in a (relatively) similar geographic context. The complexities of racism (both historical and contemporary) as expressed in part through problematically-enforced laws like stand-your-ground come to the fore in the south at a time like this, as can be seen in the much higher-than-usual tweeting about the case in Alabama, Georgia, Mississippi, Louisiana and Arkansas. If anything, the outpouring of tweets throughout the south in support of the Martin family and in favor of a more sensible and equitable justice system serves to destabilize the common narrative that the south is unitary, coherent region populated by those clinging to nineteenth century racial mores. The south is, like any other place, marked by conflict and contradiction, something evident nowhere more than in the way it continues to deal with (or ignore) persistent racial inequality like that seen in Trayvon Martin's killing and George Zimmerman's acquittal.
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[1] We've previously demonstrated the utility of this method for mapping concentrations of tweets about a given phenomena.
[2] See, for example, our work on mapping racist tweets in response to President Obama's re-election last November.

Welcome to 'Merica (or is it 'Murica?)

"Chicken & waffle flavored lays? #Murica."

On this day (well, technically the day before) in which we celebrate our independence from those limey redcoats and their tea-guzzling ways [1], it's time we take on one of the truly great debates tearing at the fabric of our country... 'Merica? or 'Murica?

When dropping the first letter of America (either sarcastically or to preserve our limited supply of vowels), is it more correct to (a) continue as if it were still there and use the term 'Merica? or (b) produce an altogether different word, 'Murica, to express our facetiousness and/or lack of spelling ability?

For instance, the emotionally incensed Twitter user below makes a compelling argument for 'Merica:

"P.s. please stop spelling it #murica or #mericuh or any other variation. It's #MERICA. #northerngirlprobs"

In contrast, this erudite tweeter prefers the more guttural 'Murica spelling:

"I don't know Harry, I heard the French are assholes" true statement. Elated to be back in 'Murica" 

But sadly, there is no consensus around this important issue, which if left unchecked (or at least unmapped) could threaten to undermine the very foundation of the nation. Even more tragic is that someone [2] was so unthoughtful as to bring up this topic on the day in which all 'Mericans/'Muricans should join together in our hatred of everyone who doesn't acknowledge that we're so totally superior to them. As such, we dutifully bring you an investigation of this debate that you may not have even been aware of. You're welcome.

In this endeavor, we collected all geotagged tweets referencing "murica" or "merica" in the United States from July 1, 2012 to June 30, 2013, producing 12,407 references to "murica" and 80,344 references to "merica". If you believe that absolute numbers solve the debate, read no further, as we should obviously err on the side of 'Merica. But if you believe that, you must also believe that "On dit que Dieu est toujours pour les gros bataillons" [3], which we must point out is in FRENCH, and hence your opinion on this day can easily be ignored. Again, you're welcome.

Seeing as there is such a significant preference for 'Merica, we created a normalized measure at the county level to allow for geographic comparison in spite of the massive difference in usage of the terms.  Thus, the maps below illustrate counties' share of tweets for each of the two terms.

For example, Cook County, Illinois had the absolute most tweets for either term, with 201 for "murica" and 782 for "merica". But because its 201 tweets represented 1.6% of all tweets referencing 'Murica, and its 782 were only 0.97% of the tweets refrencing 'Merica, it was determined to have a relatively greater usage of 'Murica, and is shaded as such on the map. So in this first map, the areas that are the darkest shade of red are those places where that place produces a significantly greater share of the overall number of tweets for 'Murica than it does for tweets referencing 'Merica. Confused? You're welcome.

The Misspellings of America

While it might be remarked that this unusual methodology unfairly tilts the linguistic playing field in favor of the much less used 'Murica, we would respond with: who cares? This is our map and we can do what we want with it. Also, we're academics (aka commies) and are totally OK with doing things like changing the rules to benefit the less well-off. Also, note the holiday appropriate color ramp of blues to white to reds. Clever, yes? You're welcome.

As you can see, use of 'Murica tends to be associated with the east and west coasts, with there being fairly little usage of the term, even by relative measures, in the interior of the United States. So it appears that those living in "flyover country" tend to prefer the more simple 'Merica, the coastal elite like to step up their sarcasm an extra notch by exchanging an 'e' for a 'u'.

While some of the country's biggest cities -- Los Angeles, New York City, Chicago, Boston, Phoenix, Minneapolis, Seattle and D.C. -- have a relatively greater amount of 'Murica-ness (or should that be 'Murica-lity), the divide between the two spellings doesn't break down along clear urban/rural lines. Oklahoma City and Indianapolis are two of the biggest users of 'Merica, while parts of the Charlotte and Atlanta metropolitan regions are also on the list of counties who believe that it's spelled 'Merica, not 'Murica.

Indeed, if you further normalize by creating a location quotient -- in effect controlling for absolute size -- a similar picture emerges, albeit one which tends to emphasize the large urban areas much less, regardless of whether they see themselves (or others) as 'Mericans or 'Muricans.

The Misspellings of America (by Location Quotient)

Unlike in the previous map, the most red end of the spectrum here actually shows the places where there is the most parity between the usage of the two spellings, even if there are still a greater number of absolute references to 'Merica than to 'Murica. So less populous counties, or those with many fewer Twitter users, such as Piscataquis County, Maine, with fewer than five or ten overall references to either term, will generally tend to be more red.

But perhaps the most interesting (and actually rather methodologically valid) ways of examining the data is to simply look at a ranked list of the top ten counties for each term. One sees here that the top ten counties for 'Merica are almost exclusively in the South, while the top ten counties for 'Murica are outside the South and within large metropolitan areas. So, our working hypothesis (which we suggest you discuss over beer and burgers on this fine day), is that 'Murica is likely a derivative of 'Merica, used ironically by slow-pour-coffee-drinking, skinny-jean-wearing hipsters in big cities. Our extensive examination of hipsters (n=1) confirms this hypothesis and places the epicenter of this plague somewhere in the Greater Boston area. But you can probably spell it however you'd like.

Happy 4th of July everyone!

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[1] No offense intended. Verily, some of the FloatingSheep collective members are British and have yet to make the move to the promised land of 'Merica/'Murica.
[2] That would be us.
[3] "It is said that God is always on the side of the big battalions." -Voltaire

The Geography of #StandWithWendy Tweets

The filibuster by Texas State Senator Wendy Davis on June 25th to block a new piece of legislation that would have resulted in many more restrictions on abortion in Texas brought a lot of attention to the Lone Star state this week. Day-long filibusters, parliamentary machinations, vocal protesters, and changing the time stamps on votes all make for great political theater, even more so as it involves a highly contentious issue and inter-party fights. From our perspective, one of the most compelling elements of this story was the strong response within social media (including Twitter) that this event engendered. In the course of a few hours, tens (or even hundreds) of thousands of tweets were sent using the hashtag #standwithwendy in order to show their support for the senator's efforts.

We collected all geocoded tweets from June 25th and 26th that contained the text "standwithwendy", resulting in a dataset of 3,702 tweets. Although we are primarily interested in the spatial dimension of tweeting activity, the way this event played out over time is particularly interesting. Using our dataset, one can see how this event - or at least its reflection in Twitterspace - started building around 8pm on the 25th and peaking around midnight as the deadline for the special session neared, though it maintained momentum well into the early hours of the 26th when the legislative session was officially declared over and the bill defeated.

Temporal Distribution of Relative Frequency of 

Tweets Containing #StandWithWendy at the County Level

Blue = relatively more #StandWithWendy Tweets; Red = relatively fewer 

Source: DOLLY, n = 3702 #StandWithWendy tweets on June 25th and 26th, 2013; Normalized by the total number of tweets sent during the same time period; The peak is at ~700 tweets right around midnight

Returning to our primary interest in the spatial distribution of tweets, it should come as no surprise that Texas had by far the most tweets, around a thousand in all, or 28.7% of all tweets with the aforementioned hashtag. While Texas is home to six of the twenty largest cities in the US, and thus is likely to have a significant number of tweets based on its population alone, the state is over-represented in the corpus of #StandWithWendy tweets by ~3.5x, relative to its share of the total US population (Texas constitutes around 8% of the country's population), so there is an obvious localizing effect that comes with being the epicenter of this debate. But the phenomenon was far from limited to Texas, with many tweets coming from around the country, though the rest of these tweets much more closely resemble the distribution of population.

Percentage of Tweets by State (blue text) & Location of Each Tweet (pink dot)

Source: DOLLY, n = 3702 #StandWithWendy tweets on June 25th and 26th, 2013; Darker shading indicates greater intensity

The spatial differences are particularly telling when one looks not just at the raw number of tweets, but rather a value normalized by the total number of tweets sent during this time. Doing so allows us to avoid simply highlighting those places with a large number of people by comparing a given place's production of #StandWithWendy tweets relative to its 'usual' tweet output.

The map below shows this normalized distribution. Darker shaded states have relatively more tweets containing #StandWithWendy than the national average, and lighter states have relatively fewer tweets.  The darker the shading the greater the intensity. That Texas remains shaded dark grey in this map is further indication of the above point that its high volume of tweets in this case goes beyond simply its mass of population, while it becomes evident that the large amount of tweeting in California and New York is more dependent on its population than on any unusual interest in the issue by users in those states. South Carolina and Kentucky were the biggest standouts in terms of having relatively few tweets on the subject.

Geographic Distribution of Relative Frequency of 

Tweets Containing #StandWithWendy at the State Level

Source: DOLLY, n = 3702 #StandWithWendy tweets on June 25th and 26th, 2013; Darker shading indicates greater intensity; Normalized by the total number of tweets sent during the same time period

Overall, there seems to be a general pattern of more tweets in the Northeast, Upper Great Plains and West Coast, while states in the Southeast, Mid-Atlantic, Midwest and Southwest have relatively fewer.  But as this is a quick analysis, we'd caution against reading too much into this.

We can also look into the relative amount of tweets at the county level. The map below shows a small section of the country from Texas to South Carolina. One can see that Austin, the location of the state capitol and Senator Davis' filibuster, is very over represented in the number of tweets, as are many other places in Texas. One of the most interesting patterns is within larger metropolitan areas in which the level of tweeting activity around #StandWithWendy varies widely between neighboring counties, as in Atlanta. 

Geographic Distribution of Relative Frequency of 

Tweets Containing #StandWithWendy at the County Level

Blue = relatively more #StandWithWendy Tweets; Red = relatively fewer; White = no tweets; Darker shading indicates greater intensity

Source: DOLLY, n = 3702 #StandWithWendy tweets on June 25th and 26th, 2013; Normalized by the total number of tweets sent during the same time period