Category Archives: Crisis Mapping

MicroMappers: Towards Next Generation Humanitarian Technology

The MicroMappers platform has come a long way and still has a ways to go. Our vision for MicroMappers is simple: combine human computing (smart crowd-sourcing) with machine computing (artificial intelligence) to filter, fuse and map a variety of different data types such as text, photo, video and satellite/aerial imagery. To do this, we have created a collection of “Clickers” for MicroMappers. Clickers are simply web-based crowdsourcing apps used to make sense of “Big Data”. The “Text Cicker” is used to filter tweets & SMS’s; “Photo Clicker” to filter photos; “Video Clicker” to filter videos and yes the Satellite & Aerial Clickers to filter both satellite and aerial imagery. These are the Data Clickers. We also have a collection of Geo Clickers that digital volunteers use to geo-tag tweets, photos and videos filtered by the”Data Clickers. Note that these Geo Clickers auto-matically display the results of the crowdsourced geo-tagging on our MicroMaps like the one below.

MM Ruby Tweet Map

Thanks to our Artificial Intelligence (AI) engine AIDR, the MicroMappers “Text Clicker” already combines human and machine computing. This means that tweets and text messages can be automatically filtered (classified) after some initial crowdsourced filtering. The filtered tweets are then pushed to the Geo Clickers for geo-tagging purposes. We want to do the same (semi-automation) for photos posted to social media as well as videos; although this is still a very active area of research and development in the field of computer vision.

So we are prioritizing our next hybrid human-machine computing efforts on aerial imagery instead. Just like the “Text Clicker” above, we want to semi-automate feature detection in aerial imagery by adding an AI engine to the “Aerial Clicker”. We’ve just starting to explore this with computer vision experts in Switzerland and Canada. Another development we’re eyeing vis-a-vis UAVs is live video streaming. To be sure, UAVs will increasingly be transmitting live video feeds directly to the web. This means we may eventually need to develop a “Streaming Clicker”, which would in some respects resemble our existing “Video Clicker” except that the video would be broadcasting live rather than play back from YouTube, for example. The “Streaming Clicker” is for later, however, or at least until a prospective partner organization approaches us with an immediate and compelling social innovation use-case.

In the meantime, my team & I at QCRI will continue to improve our maps (data visualizations) along with the human computing component of the Clickers. The MicroMappers smartphone apps, for example, need more work. We also need to find partners to help us develop apps for tablets like the iPad. In addition, we’re hoping to create a “Translate Clicker” with Translators Without Borders (TWB). The purpose of this Clicker would be to rapidly crowdsource the translation of tweets, text messages, etc. This could open up rather interesting possibilities for machine translation, which is certainly an exciting prospect.

MM All Map

Ultimately, we want to have one and only one map to display the data filtered via the Data and Geo Clickers. This map, using (Humanitarian) OpenStreetMap as a base layer, would display filtered tweets, SMS’s, photos, videos and relevant features from satellite and UAV imagery. Each data type would simply be a different layer on this fused “Meta-Data Crisis Map”; and end-users would simply turn individual layers on and off as needed. Note also the mainstream news feeds (CNN and BBC) depicted in the above image. We’re working with our partners at UN/OCHA, GDELT & SBTF to create a “3W Clicker” to complement our MicroMap. As noted in my forthcoming book, GDELT is the ultimate source of data for the world’s digitized news media. The 3Ws refers to Who, What, Where; an important spreadsheet that OCHA puts together and maintains in the aftermath of major disasters to support coordination efforts.

In response to Typhoon Ruby in the Philippines, Andrej Verity (OCHA) and I collaborated with Kalev Leetaru from GDELT to explore how the MicroMappers “3W Clicker” might work. The result is the Google Spreadsheet below (click to enlarge) that is automatically updated every 15 minutes with the latest news reports that refer to one or more humanitarian organizations in the Philippines. GDELT includes the original URL of the news article as well as the list of humanitarian organizations referenced in the article. In addition, GDELT automatically identifies the locations referred to in the articles, key words (tags) and the date of the news article. The spreadsheet below is already live and working. So all we need now is the “3W Clicker” to crowdsource the “What”.

MM GDELT output

The first version of the mock-up we’ve created for the “3W Clicker” is displayed below. Digital volunteers are presented with an interface that includes an news article with the names of humanitarian organizations highlighted in red for easy reference. GDELT auto-populates the URL, the organization name (or names if there are more than one) and the location. Note that both the “Who” & “Where” information can be edited directly by the volunteer incase GDELT’s automated algorithm gets those wrong. The main role of digital volunteers, however, would simply be to identify the “What” by quickly skimming the article.

MM 3W Clicker v2

The output of the “3W Clicker” would simply be another MicroMap layer. As per Andrej’s suggestion, the resulting data could also be automatically pushed to another Google Spreadsheet in HXL format. We’re excited about the possibilities and plan to move forward on this sooner rather than later. In addition to GDELT, pulling in feeds from CrisisNET may be worth exploring. I’m also really keen on exploring ways to link up with the Global Disaster Alert & Coordination System (GDACS) as well as GeoFeedia.

In the meantime, we’re hoping to pilot our “Satellite Clicker” thanks to recent conversations with Planet Labs and SkyBox Imaging. Overlaying user-generated content such as tweets and images on top of both satellite and aerial imagery can go a long way to helping verify (“ground truth”) social media during disasters and other events. This is evidenced by recent empirical studies such as this one in Germany and this one in the US. On this note, as my QCRI colleague Heather Leson recently pointed out, the above vision for MicroMappers is still missing one important data feed; namely sensors—the Internet of Things. She is absolutely spot on, so we’ll be sure to look for potential pilot projects that would allow us to explore this new data source within MicroMappers.

The above vision is a tad ambitious (understatement). We really can’t do this alone. To this end, please do get in touch if you’re interested in joining the team and getting MicroMappers to the next level. Note that MicroMappers is free and open source and in no way limited to disaster response applications. Indeed, we recently used the Aerial Clicker for this wildlife protection project in Namibia. This explains why our friends over at National Geographic have also expressed an interest in potentially piloting the MicroMappers platform for some of their projects. And of course, one need not use all the Clickers for a project, simply the one(s) that make sense. Another advantage of MicroMappers is that the Clickers (and maps) can be deployed very rapidly (since the platform was initially developed for rapid disaster response purposes). In any event, if you’d like to pilot the platform, then do get in touch.


See also: Digital Humanitarians – The Book

Digital Jedis Complete Response to Typhoon Ruby

Thank you, Digital Jedis!

Every Click you made on MicroMappers was a gift. Typhoon Ruby (Hagupit) disrupted the lives of many and caused damage in regions already affected by previous disasters. As MicroMappers, you gave your time, clicks and skills to make a difference. Catherine, the Head of the UN’s Information Management Unit in the Philippines had this to say: “I would like to thank all the volunteers […] for their invaluable contribution over the past few days. We are lucky that Hagupit [Ruby] made less damages than expected and that the emergency quickly scaled down.”

MM Ruby Tweet Map

MicroMappers and our partners at the Standby Task Force (SBTF) were activated by the United Nations Office for the Coordination of Humanitarian Affairs (OCHA). The Mission?

To augment the situational awareness of humanitarian actors on the ground by making sense of social media generated following the Typhoon.

Over the course of 72 hours, these Digital Jedis united to MicroMap one Click at a time. By reviewing tweets and image, each MicroMapper built collective intelligence and insights that were used to build a comprehensive situational awareness reports and maps for the UN. Many hands, and in this case, Clicks, make light work.

As Catherine rightly notes, there was thankfully less damage than many feared. This explains why our MicroMaps (above and below) are thankfully not riddled with hundreds of markers. In addition, we prioritize quality over quantity at MicroMappers. Our UN partners had specifically asked for tweets related to:

(1) Requests for Help / Needs
(2) Infrastructure Damage
(3) Humanitarian Aid Provided

Together, these tweets—which are mapped above—represented less than 5% of the Ruby-related tweets that were collected during the first 72 hours of the Typhoon making landfall. This doesn’t mean that only 5% of the information on Twitter was relevant for emergency response, however. Indeed, we also tagged tweets that were not related to the above 3 categories but that were still informative. These constituted more than 20% of all tweets collected (which are not included in the map above). In the analysis provided to UN partners, we did include a review of those other relevant tweets.

MM Ruby Tweet Clicker

Some 700 Digital Jedis joined the response online, a new record for MicroMappers! An astounding 50,394 Clicks were made using the Text Clicker pictured above (each tweet was reviewed by at least 3 digital volunteers for quality assurance purposes). And a further 3,555 Clicks were carefully made by the SBTF to geo-locate (map) relevant tweets. In other words, close to 55,000 Clicks went into making the high quality map displayed above! That’s over 12 Clicks per minute non-stop for more than 4,300 consecutive minutes!

MM Ruby Image Map

The United Nations also asked Digital Jedis to identify pictures posted on Twitter that showed disaster damage. Over 30,000 Clicks went into this operation with a further 7,413 Clicks made by the SBTF to map images that showed severe and mild damage. In sum, over 40,000 Clicks went into the MicroMap above. Overall, the entire MicroMappers response was powered by close to 100,000 Clicks!

Screen Shot 2014-12-10 at 8.36.04 AMMM Infographic 2MM Infographic 3

Digital Jedis have yet again shown that together, we can help people get positively involved in their world, even when half-a-globe and many timezones away. Yes, we can and should donate $$ to support relief efforts and good causes around the world but we can also get directly involved by donating our time, or what we call M&M’s, Minutes and Mouse clicks. This year MicroMappers have mobilized to support wildlife protection in Namibia, food security efforts in the Philippines and of course this most recent response to Typhoon Ruby. On that note, thanks again to all volunteers who supported the MicroMappers response to the Typhoon in partnership with the United Nations. You truly are Digital Jedis! And the UK Guardian certainly agrees, check out their article on our digital response.

So what’s next? We will continue to solicit your feedback on how to improve the Clickers and will get started right away. (Add your MicroMappers feedback here). In the meantime, we will leave the Clickers online for newcomers who wish to practice. We are also in touch with the UN and UAV partners in the Philippines as they may soon fly their small, remote-control planes to take aerial photographs over disaster affected areas. If they do, they will send us the photographs for analysis via MicroMappers, so stay tuned.

In closing, MicroMappers was developed by QCRI in partnership SBTF/OCHA. So a million thanks to the QCRI team and SBTF for deploying MicroMappers in support of these digital humanitarian efforts. Special thanks go to Ji Lucas, Jus Mackinnon, ChaTo Castillo, Muhammad Imran, Heather Leson, Sarah Vieweg and last but certainly not least Peter Mosur.

(Ed. note: Blog post was cross-posted from Infrographic uses software)

Using Social Media to Anticipate Human Mobility and Resilience During Disasters

The analysis of cell phone data can already be used to predict mobility patterns after major natural disasters. Now, a new peer-reviewed scientific study suggests that travel patterns may also be predictable using tweets generated following large disasters. In “Quantifying Human Mobility Perturbation and Resilience in Hurricane Sandy,” co-authors Qi Wang and John Taylor analyze some 700,000 geo-tagged tweets posted by ~53,000 individuals as they moved around over the course of 12 days. Results of the analysis confirm that “Sandy did impact the mobility patterns of individuals in New York City,” but this “perturbation was surprisingly brief and the mobility patterns encouragingly resilient. This resilience occurred even in the large-scale absence of mobility infrastructure.”

Twitter Mobility

In sum, this new study suggests that “Human mobility appears to possess an inherent resilience—even in perturbed states—such that movement deviations, in aggregate, follow predictable patterns in hurricanes. Therefore, it may be possible to use human mobility data collected in steady states to predict perturbation states during extreme events and, as a result, develop strategies to improve evacuation effectiveness & speed critical disaster response to minimize loss of life and human suffering.”

Authors Wang and Taylor are now turning their attention to “10 other storms and typhoons that they’ve collected data on.” They hope to further demonstrate that quantifying mobility patterns before and after disasters will eventually help cities “predict mobility in the face of a future disaster, and thereby protect and serve residents better.” They also want to “understand where the ‘upper limit’ of resilience lies. ‘After Haiyan,’—the deadliest-ever Philippine Typhoon that struck last November—’there was a total breakdown in mobility patterns,’ says Taylor.”

Of course, Twitter data comes with well-known limitations such as demographic bias, for example. This explains why said data must be interpreted carefully and why the results simply augment rather than replace the analysis of traditional data sources used for damage after needs assessments after disasters.


See also:

  • Social Media & Emergency Management: Supply and Demand [link]
  • Using AIDR to Automatically Classify Disaster Tweets [link]
  • Visualization of Photos Posted to Instagram During Sandy [link]
  • Using Twitter to Map Blackouts During Hurricane Sandy [link]
  • Analyzing Foursquare Check-Ins During Hurricane Sandy [link]

Digital Jedis: There Has Been An Awakening…

Crowdsourcing and Humanitarian Action: Analysis of the Literature

Raphael Hörler from Zurich’s ETH University has just completed his thesis on the role of crowdsourcing in humanitarian action. His valuable research offers one of the most up-to-date and comprehensive reviews of the principal players and humanitarian technologies in action today. In short, I highly recommend this important resource. Raphael’s full thesis is available here (PDF).

Crowdsourcing Yolanda Response


Establishing Social Media Hashtag Standards for Disaster Response

The UN Office for the Coordination of Humanitarian Affairs (OCHA) has just published an important, must-read report on the use of social media for disaster response. As noted by OCHA, this document was inspired by conversations with my team and I at QCRI. We jointly recognize that innovation in humanitarian technology is not enough. What is needed—and often lacking—is innovation in policymaking. Only then can humanitarian technology have widespread impact. This new think piece by OCHA seeks to catalyze enlightened policymaking.


I was pleased to provide feedback on earlier drafts of this new study and look forward to discussing the report’s recommendations with policymakers across the humanitarian space. In the meantime, many thanks to Roxanne Moore and Andrej Verity for making this report a reality. As Andrej notes in his blog post on this new study, the Filipino Government has just announced that “twitter will become another source of information for the Philippines official emergency response mechanism,” which will lead to an even more pressing Big (Crisis) Data challenge. The use of standardized hashtags will thus be essential.


The overflow of information generated during disasters can be as paralyzing to disaster response as the absence of information. While information scarcity has long characterized our information landscapes, today’s information-scapes are increasingly marked by an overflow of information—Big Data. To this end, encouraging the proactive standardization of hashtags may be one way to reduce this Big Data challenge. Indeed, standardized hashtags—i.e., more structured information—would enable paid emergency responders (as well as affected communities) to “better leverage crowdsourced information for operational planning and response.” At present, the Government of the Philippines seems to be the few actors that actually endorse the use of specific hashtags during major disasters as evidenced by their official crisis hashtags strategy.

The OCHA report thus proposes three hashtag standards and also encourages social media users to geo-tag their content during disasters. The latter can be done by enabling auto-GPS tagging or by using What3Words. Users should of course be informed of data-privacy considerations when geo-tagging their reports. As for the three hashtag standards:

  1. Early standardization of hashtags designating a specific disaster
  2. Standard, non-changing hashtag for reporting non-emergency needs
  3. Standard, non-changing hashtags for reporting emergency needs

1. As the OCHA think piece rightly notes, “News stations have been remarkably successful in encouraging early standardization of hashtags, especially during political events.” OCHA thus proposes that humanitarian organizations take a “similar approach for emergency response reporting and develop partnerships with Twitter as well as weather and news teams to publicly encourage such standardization. Storm cycles that create hurricanes and cyclones are named prior to the storm. For these events, an official hashtag should be released at the same time as the storm announcement.” For other hazards, “emergency response agencies should monitor the popular hashtag identifying a disaster, while trying to encourage a standard name.”

2. OCHA advocates for the use of #iSee, #iReport or #PublicRep for members of the public to designate tweets that refer to non-emergency needs such as “power lines, road closures, destroyed bridges, large-scale housing damage, population displacement or geographic spread (e.g., fire or flood).” When these hashtags are accompanied with GPS information, “responders can more easily identify and verify the information, therefore supporting more timely response & facilitating recovery.” In addition, responders can more easily create live crisis maps on the fly thanks to this structured, geo-tagged information.

3. As for standard hashtags for emergency reports, OCHA notes emergency calls are starting to give way to emergency SMS’s. Indeed, “Cell phone users will soon be able to send an SMS to a toll-free phone number. For emergency reporting, this new technology could dramatically alter the way the public interacts with nation-based emergency response call centers. It does not take a large imaginary leap to see the potential move from SMS emergency calls to social media emergency calls. Hashtags could be one way to begin reporting emergencies through social media.”

Most if not all countries have national emergency phone numbers already. So OCHA suggests using these existing, well-known numbers as the basis for social media hashtags. More specifically, an emergency hashtag would be composed of the country’s emergency number (such as 911 in the US, 999 in the UK, 133 in Austria, etc) followed by the country’s two-letter code (US, UK, AT respectively). In other words: #911US, #999UK, #133AT. Some countries, like Austria, have different emergency phone numbers for different types of emergencies. So these could also be used accordingly. OCHA recognizes that many “federal agencies fear that such a system would result in people reporting through social media outside of designated monitoring times. This is a valid concern. However, as with the implementation of any new technology in the public service, it will take time and extensive promotion to ensure effective use.”

Digital Humanitarians: The Book

Of course, “no monitoring system will be perfect in terms of low-cost, real-time analysis and high accuracy.” OCHA knows very well that there are a number of important limitations to the system they propose above. To be sure, “significant steps need to be taken to ensure that information flows from the public to response agencies and back to the public through improved efforts.” This is an important theme in my forthcoming book “Digital Humanitarians.”


See also:

  • Social Media & Emergency Management: Supply and Demand [link]
  • Using AIDR to Automatically Classify Disaster Tweets [link]

Using Flash Crowds to Automatically Detect Earthquakes & Impact Before Anyone Else

It is said that our planet has a new nervous system; a digital nervous system comprised of digital veins and intertwined sensors that capture the pulse of our planet in near real-time. Next generation humanitarian technologies seek to leverage this new nervous system to detect and diagnose the impact of disasters within minutes rather than hours. To this end, LastQuake may be one of the most impressive humanitarian technologies that I have recently come across. Spearheaded by the European-Mediterranean Seismological Center (EMSC), the technology combines “Flashsourcing” with social media monitoring to auto-detect earthquakes before they’re picked up by seismometers or anyone else.

Screen Shot 2014-10-23 at 5.08.30 PM

Scientists typically draw on ground-motion prediction algorithms and data on building infrastructure to rapidly assess an earthquake’s potential impact. Alas, ground-motion predictions vary significantly and infrastructure data are rarely available at sufficient resolutions to accurately assess the impact of earthquakes. Moreover, a minimum of three seismometers are needed to calibrate a quake and said seismic data take several minutes to generate. This explains why the EMSC uses human sensors to rapidly collect relevant data on earthquakes as these reduce the uncertainties that come with traditional rapid impact assess-ment methodologies. Indeed, the Center’s important work clearly demonstrates how the Internet coupled with social media are “creating new potential for rapid and massive public involvement by both active and passive means” vis-a-vis earthquake detection and impact assessments. Indeed, the EMSC can automatically detect new quakes within 80-90 seconds of their occurrence while simultaneously publishing tweets with preliminary information on said quakes, like this one:

Screen Shot 2014-10-23 at 5.44.27 PM

In reality, the first human sensors (increases in web traffic) can be detected within 15 seconds (!) of a quake. The EMSC’s system continues to auto-matically tweet relevant information (including documents, photos, videos, etc.), for the first 90 minutes after it first detects an earthquake and is also able to automatically create a customized and relevant hashtag for individual quakes.

Screen Shot 2014-10-23 at 5.51.05 PM

How do they do this? Well, the team draw on two real-time crowdsourcing methods that “indirectly collect information from eyewitnesses on earthquakes’ effects.” The first is TED, which stands for Twitter Earthquake Detection–a system developed by the US Geological Survey (USGS). TED filters tweets by key word, location and time to “rapidly detect sharing events through increases in the number of tweets” related to an earthquake. The second method, called “flashsourcing” was developed by the European-Mediterranean to analyze traffic patterns on its own website, “a popular rapid earthquake information website.” The site gets an average of 1.5 to 2 million visits a month. Flashsourcing allows the Center to detect surges in web traffic that often occur after earthquakes—a detection method named Internet Earthquake Detection (IED). These traffic surges (“flash crowds”) are caused by “eyewitnesses converging on its website to find out the cause of their shaking experience” and can be detected by analyzing the IP locations of website visitors.

It is worth emphasizing that both TED and IED work independently from traditional seismic monitoring systems. Instead, they are “based on real-time statistical analysis of Internet-based information generated by the reaction of the public to the shaking.” As EMSC rightly notes in a forthcoming peer-reviewed scientific study, “Detections of felt earthquakes are typically within 2 minutes for both methods, i.e., considerably faster than seismographic detections in poorly instrumented regions of the world.” TED and IED are highly complementary methods since they are based on two entirely “different types of Internet use that might occur after an earthquake.” TED depends on the popularity of Twitter while IED’s effectiveness depends on how well known the EMSC website is in the area affected by an earthquake. LastQuake automatically publishes real-time information on earthquakes by automatically merging real-time data feeds from both TED and IED as well as non-crowdsourcing feeds.


Lets looks into the methodology that powers IED. Flashsourcing can be used to detect felt earthquakes and provide “rapid information (within 5 minutes) on the local effects of earthquakes. More precisely, it can automatically map the area where shaking was felt by plotting the geographical locations of statistically significant increases in traffic […].” In addition, flashsourcing can also “discriminate localities affected by alarming shaking levels […], and in some cases it can detect and map areas affected by severe damage or network disruption through the concomitant loss of Internet sessions originating from the impacted region.” As such, this “negative space” (where there are no signals) is itself an important signal for damage assessment, as I’ve argued before.

remypicIn the future, EMSC’s flashsourcing system may also be able discriminate power cuts between indoor and outdoor Internet connections at the city level since the system’s analysis of web traffic session will soon be based on web sockets rather than webserver log files. This automatic detection of power failures “is the first step towards a new system capable of detecting Internet interruptions or localized infrastructure damage.” Of course, flashsourcing alone does not “provide a full description of earthquake impact, but within a few minutes, independently of any seismic data, and, at little cost, it can exclude a number of possible damage scenarios, identify localities where no significant damage has occurred and others where damage cannot be excluded.”

Screen Shot 2014-10-23 at 5.59.20 PM

EMSC is complementing their flashsourching methodology with a novel mobile app that quickly enables smartphone users to report about felt earthquakes. Instead of requiring any data entry and written surveys, users simply click on cartoonish-type pictures that best describe the level of intensity they felt when the earthquake (or aftershocks) struck. In addition, EMSC analyzes and manually validates geo-located photos and videos of earthquake effects uploaded to their website (not from social media). The Center’s new app will also make it easier for users to post more pictures more quickly.


What about typical criticisms (by now broken records) that social media is biased and unreliable (and thus useless)? What about the usual theatrics about the digital divide invalidating any kind of crowdsourcing effort given that these will be heavily biased and hardly representative of the overall population? Despite these already well known short-comings and despite the fact that our inchoate digital networks are still evolving into a new nervous system for our planet, the existing nervous system—however imperfect and immature—still adds value. TED and LastQuake demonstrate this empirically beyond any shadow of a doubt. What’s more, the EMSC have found that crowdsourced, user-generated information is highly reliable: “there are very few examples of intentional misuses, errors […].”

My team and I at QCRI are honored to be collaborating with EMSC on integra-ting our AIDR platform to support their good work. AIDR enables uses to automatically detect tweets of interest by using machine learning (artificial intelligence) which is far more effective searching for keywords. I recently spoke with Rémy Bossu, one masterminds behind the EMSC’s LastQuake project about his team’s plans for AIDR:

“For us AIDR could be a way to detect indirect effects of earthquakes, and notably triggered landslides and fires. Landslides can be the main cause of earthquake losses, like during the 2001 Salvador earthquake. But they are very difficult to anticipate, depending among other parameters on the recent rainfalls. One can prepare a susceptibility map but whether there are or nor landslides, where they have struck and their extend is something we cannot detect using geophysical methods. For us AIDR is a tool which could potentially make a difference on this issue of rapid detection of indirect earthquake effects for better situation awareness.”

In other words, as soon as the EMSC system detects an earthquake, the plan is for that detection to automatically launch an AIDR deployment to automatically identify tweets related to landslides. This integration is already completed and being piloted. In sum, EMSC is connecting an impressive ecosystem of smart, digital technologies powered by a variety of methodologies. This explains why their system is one of the most impressive & proven examples of next generation humanitarian technologies that I’ve come across in recent months.


Acknowledgements: Many thanks to Rémy Bossu for providing me with all the material and graphics I needed to write up this blog post.

See also:

  • Social Media: Pulse of the Planet? [link]
  • Taking Pulse of Boston Bombings [link]
  • The World at Night Through the Eyes of the Crowd [link]
  • The Geography of Twitter: Mapping the Global Heartbeat [link]