Tag Archives: power

Using Twitter to Map Blackouts During Hurricane Sandy

I recently caught up with Gilal Lotan during a hackathon in New York and was reminded of his good work during Sandy, the largest Atlantic hurricane on record. Amongst other analytics, Gilal created a dynamic map of tweets referring to power outages. “This begins on the evening October 28th as people mostly joke about the prospect of potentially losing power. As the storm evolves, the tone turns much more serious. The darker a region on the map, the more aggregate Tweets about power loss that were seen for that region.” The animated map is captured in the video below.

Hashtags played a key role in the reporting. The #NJpower hashtag, for example, was used to ‘help  keep track of the power situation throughout the state (1). As depicted in the tweet below, “users and news outlets used this hashtag to inform residents where power outages were reported and gave areas updates as to when they could expect their power to come back” (1). 

NJpower tweet

As Gilal notes, “The potential for mapping out this kind of information in realtime is huge. Think of generating these types of maps for different scenarios– power loss, flooding, strong winds, trees falling.” Indeed, colleagues at FEMA and ESRI had asked us to automatically extract references to gas leaks on Twitter in the immediate aftermath of the Category 5 Tornado in Oklahoma. One could also use a platform like GeoFeedia, which maps multiple types of social media reports based on keywords (i.e., not machine learning). But the vast majority of Twitter users do not geo-tag their tweets. In fact, only 2.7% of tweets are geotagged, according to this study. This explains why enlightened policies are also important for humanitarian technologies to work—like asking the public to temporally geo-tag their social media updates when these are relevant to disaster response.

While basing these observations on people’s Tweets might not always bring back valid results (someone may jokingly tweet about losing power),” Gilal argues that “the aggregate, especially when compared to the norm, can be a pretty powerful signal.” The key word here is norm. If an established baseline of geo-tagged tweets for the northeast were available, one would have a base-map of “normal” geo-referenced twitter activity. This would enable us to understand deviations from the norm. Such a base-map would thus place new tweets in temporal and geo-spatial context.

In sum, creating live maps of geo-tagged tweets is only a first step. Base-maps should be rapidly developed and overlaid with other datasets such as population and income distribution. Of course, these datasets are not always available acessing historical Twitter data can also be a challenge. The latter explains why Big Data Philanthropy for Disaster Response is so key.

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Map or Be Mapped: Otherwise You Don’t Exist

“There are hardly any street signs here. There are no official zip codes. No addresses. Just word of mouth” (1). Such is the fate of Brazil’s Mare shanty-town and that of most shantytowns around the world where the spoken word is king (and not necessarily benevolent). “The sprawling complex of slums, along with the rest of Rio de Janerio’s favelas, has hung in a sort of ‘legal invisibility’ since 1937, when a city ordinance ruled that however unsightly, favelas should be kept off maps because they were merely ‘temporary'” (2).

shantytown

The socio-economic consequences were far-reaching. For decades, this infor-mality meant that “entire neighborhoods did not receive mail. It had also blocked people from giving required information on job applications, getting a bank account or telling the police or fire department where to go in an emergency call. Favela residents had to pick up their mail from their neighborhood associations, and entire slums housing a small town’s worth of residents had to use the zip code of the closest officially recognized street” (3).

All this is starting to change thanks to a grassroots initiative that is surveying Mare’s 16 favelas, home to some 130,000 people. This community-driven project has appropriated the same survey methodology used by the Brazilian government’s Institute of Geography and Statistics. The collected data includes “not only street names but the history of the original smaller favelas that make up the community” (4). This data is then “formatted into pocket guides and distributed gratis to residents. These guides also offer background on certain streets’ namesakes, but leave some blank so that residents can fill them in as Mare [...] continues shifting out from the shadows of liminal space to a city with distinct identities” (5). And so, “residents of Rio’s famed favelas are undergoing their first real and ‘fundamental step toward citizenship'” (6).

These bottom-up, counter-mapping efforts are inherently political—call it guerrilla mapping. Traditionally, maps have represented “not just the per-spective of the cartographer herself, but of much larger institutions—of corporations, organizations, and governments” (7). The scale was fixed at one and only one scale, that of the State. Today, informal communities can take matters into their own hands and put themselves on the map; at the scale of their choosing. But companies like Google still have the power to make these communities vanish. In Brazil, Google said it “would tweak the site’s [Google Maps'] design, namely its text size and district labeling to show favela names only after users zoomed in on those areas.”

GmapNK

Meanwhile, Google is making North Korea’s capital city more visible. But I had an uncomfortable feeling after reading National Geographic’s take on Google’s citizen mapping expedition to North Korea. The Director for National Geographic Maps, Juan José Valdéscautions that, “In many parts of the world such citizen mapping has proven challenging, if not downright dangerous. In many places, little can be achieved without the approval of local and or national authorities—especially in North Korea.” Yes, but in many parts of the world citizen mapping is safe and possible. More importantly, citizen mapping can be a powerful tool for digital activism. My entire doctoral dissertation focuses on exactly this issue.

Yes, Valdés is absolutely correct when he writes that “In many countries, place-names, let alone the alignment of boundaries, remain a powerful symbol of independence and national pride, and not merely indicators of location. This is where citizen cartographers need to understand the often subtle nuances and potential pitfalls of mapping.” As the New Yorker notes, “Maps are so closely associated with power that dictatorships regard information on geography as a state secret.” But map-savvy digital activists already know this better than most, and they deliberately seek to exploit this to their advantage in their struggles for democracy.

National Geographic’s mandate is of course very different. “From National Geographic’s perspective, all a map should accomplish is the actual portrayal of national sovereignty, as it currently exists. It should also reflect the names as closely as possible to those recognized by the political entities of the geographic areas being mapped. To do otherwise would give map readers an unrealistic picture of what is occurring on the ground.”

natgeomaps

This makes perfect sense for National Geographic. But as James Scott reminds us in his latest book, “A great deal of the symbolic work of official power is precisely to obscure the confusion, disorder, spontaneity, error, and improvisation of political power as it is in fact exercised, beneath a billiard-ball-smooth surface of order, deliberation, rationality, and control. I think of this as the ‘miniaturization of order.'” Scott adds that, “The order, rationality, abstractness and synoptic legibility of certain kinds of schemes of naming, landscape, architecture, and work processes lend themselves to hierarchical power [...] ‘landscapes of control and appropriation.'”

Citizen mapping, especially in repressive environments, often seeks to change that balance of power by redirecting the compass of political power with the  use of subversive digital maps. Take last year’s example of Syrian pro-democracy activists changing place & street names depicted on on the Google Map of Syria. They did this intentionally as an act of resistance and defiance. Again, I fully understand and respect that National Geographic’s mandate is completely different to that of pro-democracy activists fighting for freedom. I just wish that Valdés had a least added one sentence to acknowledge the importance of maps for the purposes of resistance and pro-democracy movements. After all, he is himself a refugee from Cuba’s political repression.

There is of course a flip side to all this. While empowering, visibility and legibility can also undermine a community’s autonomy. As Pierre-Joseph Proudhon famously put it, “To be governed is to be watched, inspected, spied upon, directed, law-driven, numbered, regulated, enrolled, indoctrinated, preached at, controlled, checked, estimated, valued, censured, commanded, by creatures who have neither the right nor the wisdom nor the virtue to do so.” To be digitally mapped is to be governed, but perhaps at multiple scales including the preferred scale of self-governance and self-determination.

And so, we find ourselves repeating the words of Shakespeare’s famous character Hamlet: “To be, or not to be,” to map, or not to map.

 

See also:

  • Spying with Maps [Link]
  • How to Lie With Maps [Link]
  • Folksomaps for Community Mapping [Link]
  • From Social Mapping to Crisis Mapping [Link]
  • Crisis Mapping Somalia with the Diaspora [Link]
  • Perils of Crisis Mapping: Lessons from Gun Map [Link]
  • Crisis Mapping the End of Sudan’s Dictatorship? [Link]
  • Threat and Risk Mapping Analysis in the Sudan [Link]
  • Rise of Amateur Professionals & Future of Crisis Mapping [Link]
  • Google Inc + World Bank = Empowering Citizen Cartographers? [Link]

Note: Readers interested in the topics discussed above may also be interested in a forthcoming book to be published by Oxford University Press entitled “Information and Communication Technologies in Areas of Limited State-hood.” I have contributed a chapter to this book entitled “Crisis Mapping in Areas of Limited Statehood,” which analyzes how the rise of citizen-genera-ted crisis mapping replaces governance in areas of limited statehood. The chapter distills the conditions for the success of these crisis mapping efforts in these non-permissive and resource-restricted environments. 

The Mathematics of War: On Earthquakes and Conflicts

A conversation with my colleague Sinan Aral at PopTech 2011 reminded me of some earlier research I had carried out on the mathematics of war. So this is a good time to share some of the findings from this research. The story begins some 60 years ago, when British physicist Lewis Fry Richardson found that international wars follow what is called a power law distribution. A power law distribution relates the frequency and “magnitude” of events. For example, the Richter scale, relates the size of earthquakes to their frequency. Richardson found that the frequency of international wars and the number of causalities each produced followed a power law.

More recently, my colleague Erik-Lars Cederman sought to explain Richardson’s findings in his 2003 peer-reviewed publication “Modeling the Size of Wars: From Billiard Balls to Sandpiles.” However, Lars used an invalid statistical technique to test for power law distributions. In 2005, I began collaborating with Pro-fessors Neil Johnson and Michael Spagat on related research after I came across their fascinating co-authored study that tested casualty distributions in new wars (internal conflicts) for power laws. Though he was not a co-author on the 2005 study, my colleague Sean Gourely presented this research at TED in 2009.

In any case, I invited Michael to present his research at The Fletcher School in the Fall of 2005 to generate interest here. Shortly after, I suggested to Michael that we test whether conflict events, in addition to casualties, followed a power law distribution. I had access to an otherwise proprietary dataset on conflict events that spanned a longer time period than the casualty datasets that he and Neils were working off. I also suggested we try to test whether casualties from natural disasters follow a power law distribution.

We chose to pursue the latter first and I submitted an abstract to the 2006 American Political Science Association (APSA) conference to present our findings. Soon after, I was accepted to the Santa Fe Institute’s Complex Systems Summer Institute for PhD students and took the opportunity to pursue my original research in testing conflict events for power law distributions with my colleague Dr. Ryan Woodard.

The APSA paper, presented in August 2006, was entitled “Natural Disasters, Casualties and Power Laws:  A Comparative Analysis with Armed Conflict” (PDF). Here is the paper’s abstract and findings:

Power-law relationships, relating events with magnitudes to their frequency, are common in natural disasters and violent conflict. Compared to many statistical distributions, power laws drop off more gradually, i.e. they have “fat tails”. Existing studies on natural disaster power laws are mostly confined to physical measurements, e.g., the Richter scale, and seldom cover casualty distributions. Drawing on the Center for Research on the Epidemiology of Disasters (CRED) International Disaster Database, 1980 to 2005, we find strong evidence for power laws in casualty distributions for all disasters combined, both globally and by continent except for North America and non-EU Europe. This finding is timely and gives useful guidance for disaster preparedness and response since natural catastrophes are increasing in frequency and affecting larger numbers of people.  We also find that the slopes of the disaster casualty power laws are much smaller than those for modern wars and terrorism, raising an open question of how to explain the differences. We show that many standard risk quantification methods fail in the case of natural disasters.

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Dr. Woodard and I presented our research on power laws and conflict events at SFI in June 2006. We produced a paper in August of that year entitled “Concerning Critical Correlations in Conflict, Cooperation and Casualties” (PDF). As the title implies, we also tested whether cooperative events followed a power law. As far as I know, we were the first to test conflict events not to mention cooperative events for power laws. In addition, we looked at conflict/cooperation (C/C) events in Western countries.

The abstract and some findings are included below:

Knowing that the number of casualties of war are distributed as a power law and given a rich data set of conflict and cooperation (C/C) events, we ask: Are there correlations among C/C events? Is there a correlation between C/C events and war casualties? Can C/C data be used as proxy for (potentially) less reliable casualty data? Can C/C data be used in conflict early warning systems? To begin to answer these questions we analyze the distribution of C/C event data for the period 1990–2004 in Afghanistan, Colombia, Iran, Iraq, North Korea, Switzerland, UK and USA. We find that the distributions of individual C/C event types scale as power laws, but only over approximately a single decade, leaving open the possibility of a more appropriate fit (for which we have not yet tested). However, the average exponent of the power law (2.5) is the same as that found in recent studies of casualties of war. We find low levels of correlations between C/C events in Iraq and Afghanistan but not in the other countries studied. We find that the distribution of the sum of all conflict or cooperation events scales exponentially. Finally, we find low levels of correlations between a two year time series of casualties in Afghanistan and the corresponding conflict events.

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I’m looking to discuss all this further with Sinan and learning more about his fascinating area of research.