Tweeting the AAGs

Now that we've all had a couple of weeks after the AAGs to relax and make fun of certain unnamed party-animals, we thought we would reflect on how the conference itself was reflected in the Twittersphere. With comments abound that there was more conference-related Twitter activity than ever before, we wanted to see if we couldn't uncover some more specific trends.

Thanks to an enterprising geographer, we have an archive of all 3,154 tweets with the official conference hashtag, #AAG2013. We know from this database that those tweets came from a total of 697 users, of which the top 10 users contributed about 23% of the total number of tweets.

But cross-referencing the Eventifier database with DOLLY's archive of geotagged tweets with the conference hashtag, we can try to understand how and where some geographers tweet and whether geographers fit the overall profile of Twitter users in terms of geotagging. Do geographers geotag their tweets at a higher rate than the average user because of their heightened awareness of spatial issues? Or do they intentionally avoid geotagging their tweets due to sensitivity to location privacy?

According to DOLLY, there were just 137 geotagged tweets with #AAG2013, coming from just 41 users. So, rather than adhering to the oft-cited rule of ~1.5% of all tweets being geotagged, geographers in Los Angeles for the AAGs actually geotagged more than 4% of their conference-related tweets. Of the 137, 127 actually have exact lat/lon coordinates, so we're able to do some mapping at the urban scale in order to see where geographers were tweeting about the conference.

And because only 8 tweets came before the AAG started on April 9, and only 5 came after it ended on April 13, and these are roughly congruent with the 16 tweets outside of Los Angeles County, we'll focus on the 113 of 127 tweets with exact coordinates which were located in downtown LA. In other words, because most of the AAG-related tweeting happened during the conference and in its general proximity, it isn't too interesting to focus on the other locations from which the hashtag was being used.

AAG-related Tweeting Activity in Downtown Los Angeles

As is evident from this map, the vast majority of the tweets referencing #AAG2013 came from the Westin Bonaventure Hotel, the primary site of the conference. The second highest concentration of tweeting activity came from the Millenium Biltmore Hotel and LARTA, the secondary conference site and location of our IronSheep event, respectively, which were just half-a-block or so apart, and immediately adjacent to Pershing Square. But given the lack of free conference Wi-Fi and general lack of cell phone service in the Biltmore, it's even less surprising that it had quite a bit less geotagged tweeting activity. Other small pockets of tweeting activity around the downtown seem to be located in the general vicinity of bars that were known to be frequented by geographers, such as the Library Bar, which hosted multiple conference related parties over the course of the week.

As is the case with many of our maps, there's nothing too surprising here. Of course it makes sense that people tweet about the conference from the location of the conference. But we'd still be careful about reading too much into these results. More specifically, we shouldn't get the impression that geographers go to the AAGs primarily to sit in stuffy hotel rooms giving paper presentations rather than gallivant around town with old friends, instead, it seems more plausible that geographers are simply having too great of a time at various drinking establishments to tweet about it, or too smart to use the official conference hashtag when doing so!

Mapping the Boston Marathon Bombing

The tragedy in Boston this week shook us all. Several of us have strong ties to the area and the randomness and sheer viciousness of the event is stunning.

We noted that many people felt similarly and many took immediately to social media (such as Twitter) to participate in a larger discussion. Some used it to assure loved ones that they were OK while cell phone service was spotty. Some used social media to spread misinformation for personal gain or to make a political point. So too did the Boston Police and Fire Departments rely on social media to get a better idea of what actually happened. But the focus on social media's role in responding to the bombings neglected the intensely geographic element of such user-generated content as individuals and society tries to make sense of it all.  Thus, in an effort to document the diffusion of spatial awareness of the tragedy we offer the following analysis.

Using DOLLY, we collected all geotagged tweets in North America referencing "Boston" from March 1, 2013 through April 15, 2013. We've divided the data from the last month and a half into three separate temporal snapshots: from March 1 to March 31, from April 1 to April 15 at 2:45pm and, finally, April 15 from 2:45pm to 11:59pm, roughly the time following the first explosion on Boylston Street near the finish line of the race. While the visual differences in the maps below may be somewhat subtle, the data behind them is anything but.

For the entire month of March 2013, there were a total of 48,622 geotagged tweets with reference to "Boston", of which 44,221 had exact lat/lon coordinates. Of the 48K+ tweets, nearly half (23,895) of them were within Boston's city limits [1]. A fairly similar pattern was evident in tweets in the first half of this month, with 24,991 tweets total (23,151 had lat/lon coordinates attached) and 12,206 in Boston. These general trends were evident in earlier data as well, especially with respect to the pattern of roughly half of the references to the city being located within it.

References to "Boston" in the Continental USA, March 1 to April 15 [2]

But in the time since yesterday's bombing, tweeting activity about Boston has both intensified and dispersed. After 2:45pm EST on the 15th, there were 52,339 tweets in our dataset -- that is, several thousand more tweets in roughly nine-and-a-quarter hours than there usually are in an entire month, indicating an expected spike in overall activity as a result of the news coverage. But of these, a lower percentage (83.6%, as compared to 90.9% for March and 92.6% for the first half of April) were geotagged with exact lat/lon coordinates. And, perhaps most interestingly, an incredibly small number of these tweets originated within Boston.

Whereas roughly half of the tweets about Boston originated there in the earlier time frames, only 3% of tweets were located within the city following the bombings. All of this remains in stark contrast to the numbers from last year's Boston Marathon, where there were only 775 total mentions of the city in geotagged tweets from North America, with 333 (again, close to half) within the city. So not only was there a considerably smaller amount of geotagged tweeting, but so too did it remain concentrated largely within the city.

References to "Boston" in the Greater Boston Area, March 1 to April 15

In addition to the overall intensification of discussion about Boston in the wake of the bombing, there are a couple of distinct spatial patterns at play here. First, yesterday's tragic events led to discussion of Boston on Twitter to become much more spatially diffuse around the country. This is likely the result of a combination of things: people within the city tweeting less due to concerns for their own safety, people within the city not feeling it necessary to include "Boston" in all of their topically-relevant tweets, and a heightened interest nationwide in what is just the latest in a long string of violence in recent months.

But second, discussion of the city within the city is also more spatially dispersed. While the time frames prior to the bombing demonstrate a massive concentration of tweets in Downtown and the Back Bay -- the areas in closest proximity to the bombings, as well as some of the more densely populated during daytime hours -- tweeting activity after the bombings shows less focus on these areas and a more random spatial distribution throughout the greater Boston area, though these areas maintain the highest concentrations.

This analysis shows how established spatial patterns of place-based social media activity can be disrupted by extraordinary circumstances, such as a terrorist attack, as well as the importance of looking at how such spatial patterns change over time [3]. While there remains more one could do with this data -- including a focus on tweeting activity within particular spaces of the city near the bombing or looking beyond particular keyword searches, or using social network analysis to understand the spatial and temporal diffusion of the tragic news -- these maps and statistics provides an initial look at how tragedies such as these and the outpouring of emotions about them result in shifting geographies of social media activity.

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[1] The greater Boston area -- including Cambridge, Somerville, Brookline, Newton, etc. -- were excluded from these counts for reasons of convenience.
[2] Note that both maps are in reverse chronological order, with the post-bombing time frame shown at the first in each series.
[3] There are also some important and potentially anomalous patterns relative to some of our earlier findings but this awaits further study.

The Urban Geography of Klout scores

We decided to dig deeper into the geography of Klout and examine the geography of some of the largest cities in the US. This revealed some very interesting patterns and large differences in the average influence of users in American cities.

Klout scores, for those unfamiliar with them, fall between 0 and 100 and supposedly measure influence (higher scores indicating that a person is more influential). As, we've noted before, this sort of quantification of a person's influence based on online activity is inherently problematic. It defines influence rather narrowly and then ranks each person with a highly decontextualised score that is unlikely to account for the many nuanced ways that influence is perceived and enacted. However, despite the problematic nature of the service, it is nonetheless important to attempt to better understand how it is measuring and representing people.

We therefore decided to calculate the average Klout score of 49 of the largest American cities. The map below displays each city as a circle that is shaded and sized according to its Klout score. In the interest of clarity, only the top-ten and bottom four cities are labelled.

First, a few words on how we collected the data: From April 8th to April 29th, 2012, approximately 195 million tweets were collected via Twitter's "spritzer" access level. Geo-coded tweets were selected using the API's internal methods. The resulting dataset was then cross-referenced against a list of fifty bounding boxes approximating the general conurbation of every city and its suburbs (so as to capture the full scope of the metropolitan area at large). For each resultant bounded set, 1,000 random users were selected from the city and referenced against Klout's score API. For each city, slightly less than 1,000 users are shown, as some of the tweeting users have not been detected and scored by Klout, and as a result have no score.

The city with the best average influence score (29.1) for its users is San Francisco (which perhaps unsurprisingly is also the headquarters of Klout). San Francisco's average score is also interestingly significantly higher than the city with the second-highest average (Austin at 27.8). We then see a tighter cluster of average city scores for Seattle in third place (27.1), and two more Bay Area cities in fourth and fifth: Oakland (27.1) and San Jose (26.8).

At the bottom end of the scale we have Houston (23.3), Jacksonville (22.9), Memphis (22.8), and Virginia Beach (22.7).

Why do we see such variance in the geography of Klout scores? Are people in San Francisco and Austin really that much more influential than people in Houston or Memphis? Klout scores certainly aren't (well, at least they don't appear to be) randomly assigned. They are derived by combining score of number of followers, number of people you follow, number of (and spread of) retweets etc.

But does the geography of Klout actually tell us anything useful about these cities? By themselves, these data tell us almost nothing. They are a very blunt and fuzzy tool applied to a limited sample and we should be hesitant about reading too much into the numbers. However, when brought together with other data and research about information production and consumption, influence, and voice they potentially allow us to us to draw more rounded pictures about the sub-national geographies of the internet.

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One interesting point is the discrepancy between these city-level scores as compared to the national scores conducted in an earlier study. While no conclusive reason has been found for this discrepancy, a few possibilities may create this effect. One theory may be that the users sampled for this report were collected on twitter in April 2012 - many of them may have since decreased the usage of their accounts, and as a result the scores may have decreased. Another theory is that there may be some correlation with users located outside of population centers having higher scores. Despite this, the data being shown was exhaustively assessed in order to determine the extent to which this discrepancy could have been in error, and has found to be accurate.

Preparing for the Zombie Apocalypse, Part IV: Zombies in the City

The following is an excerpt of our upcoming chapter in the edited collection Zombies in the Academy: Living Death in Higher Education.

In our book chapter, "Mapping Zombies", we attempt to discern how the spatial patterns exhibited by geo-coded content are reflective of some underlying social structure. One of the more obvious trends was the concentration of most zombie-related content in just a handful of places -- generally the world's largest Anglophone cities.

Using a simple keyword search for “zombies”, the following map visualizes the absolute concentrations of references within the Google Maps database. The map reveals two important spatial patterns worth consideration. First, much of the world lacks any content mentioning “zombies” whatsoever. Second, and related, the highest concentrations of zombies in the geoweb are located in the Anglophone world, especially in the largest cities.

References to "Zombies" Worldwide

The lack of content referencing zombies can likely be explained by two factors: language and socioeconomic inequality. First, because the searches for the keywords were conducted only in English and Latin characters, all references in other languages and scripts are absent. Nonetheless, many non-English speaking countries still had a number of references to zombies, meaning that language cannot be assigned complete causation. Because previous research indicates that socio-economic factors like income and internet access play a significant role in explaining the contribution of online content, it is likely that this accounts for much of the remaining difference. This ultimately means both that much of the world is left out of processes and practices of information sharing and generation, and that content is concentrated in a relatively small number of places rather than ubiquitously distributed across space.

Even within Europe and North America (i.e., the parts of the world containing the most zombie-related content), there is a significant concentration of content in just a handful of cities. New York, Los Angeles, San Francisco and London, for instance, contain the greatest number of online references to zombies, a fact that reflects their status as important nodes in the world’s information ecosystems. Information, much like zombies, is attracted to existing centers of activity as part of the historical process of urban agglomeration.

As of 2008, the world’s population was evenly divided between those living in rural areas and those living in urban areas. Given the sharp upswing in urban inhabitants through history, that ratio will increasingly favor those who live in cities. Given this oft-cited fact, it is unsurprising that, if we are to accept that zombies are an extension or a representation of society-at-large, references to zombies are clustered in urban areas. Such connections between zombies and urbanism are not unique to the geoweb, as May (2010) has argued that “recent zombie films offer a vision of the city that articulates the corporeality and bodily ambiguity of the zombie simultaneously with depictions of urban space” (285-286).

While the cognitive connection between zombies and the city is apparent, what the mere concentration of references cannot tell us is what exactly is being referenced. Each mention of “zombies” could be positive or negative, earnest or facetious, though there is no established way of discerning this context. References to zombies could refer to the location of annual ‘zombie walks’ or a place to buy a children’s zombie costume for Halloween. There seems, however, to be an interesting contradiction in the possibilities for zombies in the city.

On the one hand, zombies represent a dystopic future for the city. As one mathematician discovered, a zombie outbreak in a city of 500,000 people would take less than one week to eradicate all non-zombie life (Smith? 2009). Given startling, if still fictitious, statistics such as this, it’s hard not to imagine the city as the locus of the zombie apocalypse in the vein of Bladerunner or any number of books by Mike Davis. On the other hand, the city is something of a safe haven from zombies. The zombie attack in George Romero’s Night of the Living Dead begins in rural Pennsylvania, and the characters in The Walking Dead comic book series take shelter from zombies in the sprawling metropolis of Atlanta, Georgia. This alternative understanding is perhaps more in step with the urban fetishism of some recent scholarship which views cities as the solution to the world’s problems (Glaeser 2011).

Ultimately, drawing on our previous post outlining our approach to zombies in the geoweb, it is apparent that there is some important connection between zombies and the city, though we are unsure of what exactly it may be. Nonetheless, the fact that zombies are highly concentrated in only a handful of places is reflective of the importance of cities to society and of those particular cities as command and control centers for the global economy.

References
Gleaser, Edward L. 2011. Triumph of the City: How Our Greatest Invention Makes Us Richer, Smarter, Greener, Healthier and Happier. Penguin Press.

May, Jeff. 2010. Zombie geographies and the undead city. Social and Cultural Geography 11(3): 285-298.

Smith?, Robert. 2009. A report on the zombie outbreak of 2009: How mathematics can save us (no, really). Canadian Medical Association Journal 181(12): E297-E300.

Floating Sheep Publications

A special issue of the Journal of Urban Technology on information technologies and urban networks has just been published. It has a great series of articles from a range of researchers. Including the following two from the Floatingsheep collective.


Graham, M. and M. Zook. 2011. Visualizing the Global Cyberscape: Mapping User Generated Placemarks. Journal of Urban Technology 18(1): 115-132.
This article focuses on the representation of physical places on the Internet or what we term cyberscape. While there is a wide range of online place-related information available, this project uses the metric of the number of user-generated Google Maps placemarks containing specific keywords in locations worldwide. After setting out the methods behind this research, this article provides a cartographic analysis of these cyberscapes and examines how they inform us about the material world. Visibility and invisibility in material space are increasingly being defined by prominence, ranking, and presence on the Internet, and Google has positioned itself as a highly authoritative source of online spatial information. As such, any distinct spatial patterns within uploaded information have the potential to become real and reinforced as Google is relied upon as a mirror of the offline world.


Zook, M., Devriendt, L. and M. Dodge. (2011). Cyberspatial Proximity Metrics: Reconceptualizing Distance in the Global Urban System. Journal of Urban Technology 18(1): 93-114.
In this paper we analyze how distances between a sample of a hundred major world cities varies when measured in cyberspace. The project develops a novel spatial statistical model based upon the number of user-generated placemarks indexed by Google Maps. We demonstrate how this metric captures the “invisible” patterns of intercity information flows and helps comprehend the contours of the complex digital network that exists between large urban centers across the world. Using a specially designed software program to interrogate Google Maps, a series of keyword searches (“tourism,” “business,” “hotel”) as well as each of the city names were conducted in each of the sample places. Comparing this digital measure with the material movement of people and other relevant descriptive variables, such as national economic development and language differences, we were able to provide a cogent model that plausibly explains why certain city pairs (especially those that are physically distant) exhibit strong informational linkages. While the strength of these digital connections undoubtedly demonstrates the continued importance of physical proximity and established transport infrastructures in the twenty-first century, one can also observe significant evidence for [new?] digital “wormholes” which indicates that processes of globalization driven by online interaction also operates by its own rules.

Using Google Earth to think about urban development

As those of you who frequent the blog know, we're mostly interested in mapping and analyzing user-generated geographic information in the aggregate -- whether it be all the Google Maps references to a particular keyword or the number of geotagged Wikipedia articles within a certain country. From time to time, however, we like to talk about other interesting applications of web 2.0 spatial applications.

Although incredibly simple, one such interesting application for historical research is Google Earth's photo overlay feature. All it takes is an old map or aerial photograph and some free time, and you can begin to click and drag your way into comparing historical imagery with something a bit more up-to-date.

For a couple different reasons, I've been playing around with this feature quite a bit lately, mostly in analyzing urban development in Floatingsheep's North American home base of Lexington, KY. The following image is something I put together for some research my partner Emily has been doing on urban renewal in downtown Lexington.

The map shows a Sanborn Fire Insurance Map from 1909 overlaid on the area around Rupp Arena in downtown Lexington. In the late 1970s, a 16-acre neighborhood full of predominantly poor, black residents was demolished in order to make way for the parking lot that now sits across the street from the Lexington Civic Center and Rupp Arena, where the University of Kentucky plays its basketball games. And while a simple overlay can't tell the full story of urban renewal in Lexington, such a visualization is helpful in understanding just how much was lost in this particular case [1].

For my master's thesis research, I've used an old development plan for the University of Kentucky's Coldstream Research Campus to visualize just how much the plans for the campus have (not) been realized. Even though an exact date for the development plan isn't available (I've dated it somewhere between 1993-1996), it's possible to see just how little has actually been built at Coldstream in that time [2].

While these are two pretty basic examples that can't be totally divorced from the larger research projects they are a part of, they show the power of using web 2.0 spatial applications like Google Earth for other projects, especially those that have a historico-geographical element. Got any other good examples? Feel free to share them in the comments!

[1] It should be noted that the neighborhood likely experienced some degree of change in the intervening 70 years. The point, however, remains.

[2] Similar to the above note, the current Google Earth imagery for Lexington is incredibly out of date, circa March 2002, and several more buildings have been built at Coldstream since that time. Again, however, this does not refute the point at hand.

Mapping Chicago Sports Teams (or, where do they love Da Bears?)

Everyone knows we love making maps of obscure cultural phenomena. And everyone knows that Chicago loves its sports teams (and when you've got gems like Da Bears skit? and the Super Bowl Shuffle, too? Who couldn't love these teams?!). So why not try to bring these two otherwise unrelated worlds together?

Keeping with a theme set earlier in the week, today we present you with a series of maps showing how the Windy City of Chicago is represented in cyberspace, especially with regards to two of its beloved professional sports teams - the Chicago Cubs and Daaaaa Bears.

All User-Generated Content in Chicago IL

While the map above shows the aggregate of all user-generated Google Maps content in Chicago, the figures below map specific references to "Bears" and "Cubs" within the city.

User-Generated References to "Bears" in Chicago IL

User-Generated References to "Bears" at Soldier Field

At first glance, the map of references to "Bears" doesn't seem particularly informative. That is, unless you're already familiar with the geography of Chicago. But by zooming in to the location with the highest concentration of references, it becomes clear that the most references to "Bears" is, naturally, at the home of Da Bears - Soldier Field.

User-Generated References to "Cubs" in Chicago IL

User-Generated References to "Cubs" at Wrigley Field

Almost the exact same situation arises when we look at references to "Cubs" who, despite having a considerable number of user-generated references at Wrigley Field, have still not won the World Series in over a century. I guess it just goes to show that success in the virtual realm isn't necessarily related to success outside of it.

Mapping the Bluegrass cyberscape

Although it's been quite a while since we last posted our metro-level cyberscape visualizations, we figured that now was as good a time as any to bring them back. In some of our previous posts, we mapped the total number of user-generated Google Maps placemarks in our sample cities, along with some Crescent City culture-specific maps of New Orleans for Mardi Gras and other interesting examples from around the world.

Below you'll find maps depicting the location of all user-generated placemarks (using the keyword "1") and placemarks referencing "crime" in Lexington, Kentucky. Although Lexington doesn't hold much, if any, significance for most of our readership, it presents an excellent opportunity to ground truth these virtual references by comparing them to our collective experiences as current and past residents of "the Horse Capital of the World".

All User-Generated Content in Lexington KY

User-Generated References to "Crime" in Lexington KY

In the first map, the highest concentration of placemarks exists in downtown Lexington. More specifically, the points with the most placemarks (shown in red) are at the intersection of Limestone and Main Streets, a primary intersection in the city and the site of Phoenix Park (formerly the Phoenix Hotel) and the city's courthouses.

While the spatial pattern of all user-generated content is not surprising in the least, and largely mirrors what has been seen in other urban areas, the concentration of placemarks referencing "crime" is significantly more interesting. Rather than being a mirror of the more general pattern focused on the city center, placemarks referencing crime are focused on the Kirwan-Blanding residential complex on the University of Kentucky's South Campus.

Although this concentration isn't necessarily surprising, given the fact that the Kirwan-Blanding complex has been the site of some significant violent crimes, along with almost innumerable incidents of public intoxication and drug possession, this does represent an important deviation from common patterns of concentration within city centers, as was evidenced by the map of all placemarks in Lexington.

Skype Lecture at Madison, WI

Just finished a presentation (via Skype) to Kris Olds Introduction to the City class (GEOG-URPL 305) at University of Wisconsin, Madison. Always a bit challenging when you aren't in the same location but it worked well on my end, hopefully it was useful on the other end as well.

Amazing how easy a video link is with simple webcams and laptop computers. When I did a lecture remotely five years ago, we had to use a special room with video cameras and about 2-3 people providing support.

Also, Kris has set up a really interesting class blog related to urban geography topics.