Category Archives: Ushahidi

Traditional vs. Crowdsourced Election Monitoring: Which Has More Impact?

Posted on August 7, 2012 | Leave a comment

Max Grömping makes a significant contribution to the theory and discourse of crowdsourced election monitoring in his excellent study: “Many Eyes of Any Kind? Comparing Traditional and Crowdsourced Monitoring and their Contribu-tion to Democracy” (PDF). This 25-page study is definitely a must-read for anyone interested in this topic. That said, Max paints a false argument when he writes: “It is believed that this new methodology almost magically improves the quality of elections [...].” Perhaps tellingly, he does not reveal who exactly believes in this false magic. Nor does he cite who subscribes to the view that  ”[...] crowdsourced citizen reporting is expected to have significant added value for election observation—and by extension for democracy.”

My doctoral dissertation focused on the topic of crowdsourced election observa-tion in countries under repressive rule. At no point in my research or during interviews with activists did I come across this kind of superficial mindset or opinion. In fact, my comparative analysis of crowdsourced election observation showed that the impact of these initiatives was at best minimal vis-a-vis electoral accountability—particularly in the Sudan. That said, my conclusions do align with Max’s principle findings: “the added value of crowdsourcing lies mainly in the strengthening of civil society via a widened public sphere and the accumulation of social capital with less clear effects on vertical and horizontal accountability.”

This is huge! Traditional monitoring campaigns don’t strengthen civil society or the public sphere. Traditional monitoring teams are typically composed of inter-national observers and thus do not build social capital domestically. At times, traditional election monitoring programs may even lead to more violence, as this recent study revealed. But the point is not to polarize the debate. This is not an either/or argument but rather a both/and issue. Traditional and crowdsourced election observation efforts can absolutely complement each other precisely because they each have a different comparative advantage. Max concurs: “If the crowdsourced project is integrated with traditional monitoring from the very beginning and thus serves as an additional component within the established methodology of an Election Monitoring Organization, the effect on incentive structures of political parties and governments should be amplified. It would then include the best of both worlds: timeliness, visualization and wisdom of the crowd as well as a vetted methodology and legitimacy.”

Recall Jürgen Habermas and his treatise that “those who take on the tools of open expression become a public, and the presence of a synchronized public increasingly constrains un-democratic rulers while expanding the right of that public.” Why is this important? Because crowdsourced election observation projects can potentially bolster this public sphere and create local ownership. Furthermore, these efforts can help synchronize shared awareness, an important catalyzing factor of social movements, according to Habermas. Furthermore, my colleague Phil Howard has convincingly demonstrated that a large active online civil society is a key causal factor vis-a-vis political transitions towards more democratic rule. This is key because the use of crowdsourcing and crowd-mapping technologies often requires some technical training, which can expand the online civil society that Phil describes and render that society more active (as occurred in Egypt during the 2010 Parliamentary Elections—see  dissertation).

The problem? There is very little empirical research on crowdsourced election observation projects let alone assessments of their impact. Then again, these efforts at crowdsourcing are only a few years old and many do’ers in this space are still learning how to be more effective through trial and error. Incidentally, it is worth noting that there has also been very little empirical analysis on the impact of traditional monitoring efforts: “Further quantitative testing of the outlined mechanisms is definitely necessary to establish a convincing argument that election monitoring has positive effects on democracy.”

In the second half of his important study, Max does an excellent job articulating the advantages and disadvantages of crowdsourced election observation. For example, he observes that many crowdsourced initiatives appear to be spon-taneous rather than planned. Therein lies part of the problem. As demonstrated in my dissertation, spontaneous crowdsourced election observation projects are highly unlikely to strengthen civil society let alone build any kind of social capital. Furthermore, in order to solicit a maximum number of citizen-generated election reports, a considerable amount of upfront effort on election awareness raising and education needs to take place in addition to partnership outreach not to mention a highly effective media strategy.

All of this requires deliberate, calculated planning and preparation (key to an effective civil society), which explains why Egyptian activists were relatively more successful in their crowdsourced election observation efforts compared to their counterparts in the Sudan (see dissertation). This is why I’m particularly skeptical of Max’s language on the “spontaneous mechanism of protection against electoral fraud or other abuses.” That said, he does emphasize that “all this is of course contingent on citizens being informed about the project and also the project’s relevance in the eyes of the media.”

I don’t think that being informed is enough, however. An effective campaign not only seeks to inform but to catalyze behavior change, no small task. Still Max is right to point out that a crowdsourced election observation project can “encou-rage citizens to actively engage with this information, to either dispute it, confirm it, or at least register its existence.” To this end, recall that political change is a two-step process, with the second—social step—being where political opinions are formed (Katz and Lazarsfeld 1955). “This is the step in which the Internet in general, and social media in particular, can make a difference” (Shirky 2010). In sum, Max argues that “the public sphere widens because this engagement, which takes place in the context of the local all over the country, is now taken to a wider audience by the means of mapping and real-time reporting.” And so, “even if crowdsourced reports are not acted upon, the very engagement of citizens in the endeavor to directly make their voices heard and hold their leaders accountable widens the public sphere considerably.”

Crowdsourcing efforts are fraught with important and very real challenges, as is already well known. Reliability of crowdsourced information, risk of hate speech spread via uncontrolled reports, limited evidence of impact, concerns over security and privacy of citizen reporters, etc. That said, it is important to note that this “field” is evolving and many in this space are actively looking for solutions to these challenges. During the 2010 Parliamentary Elections in Egypt, the U-Shahid project was able to verify over 90% of the crowdsourced reports. The “field” of information forensics is becoming more sophisticated and variants to crowdsourcing such as bounded crowdsourcing and crowdseeding are not only being proposed but actually implemented.

The concern over unconfirmed reports going viral has little to do with crowd-sourcing. Moreover, the vast majority of crowdsourced election observation initiatives I have studied moderate all content before publication. Concerns over security and privacy are issues not limited to crowdsourced election observation and speak to a broader challenge. There are already several key initiatives underway in the humanitarian and crisis mapping community to address these important challenges. And lest we forget, there are few empirical studies that demonstrate the impact of traditional monitoring efforts in the first place.

In conclusion, traditional monitors are sometimes barred from observing an election. In the past, there have been few to no alternatives to this predicament. Today, crowdsourced efforts are sure to swell up. Furthermore, in the event that traditional monitors conclude that an election was stolen, there’s little they can do to catalyze a local social movement to place pressure on the thieves. This is where crowdsourced election observation efforts could have an important contribution. To quote Max: “instead of being fearful of the ‘uncontrollable crowd’ and criticizing the drawbacks of crowdsourcing, [...] governments would be well-advised to embrace new social media. Citizens [...] will use new techno-logies and new channels for information-sharing anyway, whether endorsed by their governments or not. So, governments might as well engage with ICTs and crowdsourcing proactively.”

Big thanks to Max for this very valuable contribution to the discourse and to my colleague Tiago Peixoto for flagging this important study.

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Posted in Crowdsourcing, Digital Activism, Social Media, Ushahidi

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Enhanced Messaging for the Emergency Response Sector (EMERSE)

Posted on July 24, 2012 | 6 Comments

My colleague Andrea Tapia and her team at PennState University have developed an interesting iPhone application designed to support humanitarian response. This application is part of their EMERSE project: Enhanced Messaging for the Emergency Response Sector. The other components of EMERSE include a Twitter crawler, automatic classification and machine learning.

The rationale for this important, applied research? “Social media used around crises involves self-organizing behavior that can produce accurate results, often in advance of official communications. This allows affected population to send tweets or text messages, and hence, make them heard. The ability to classify tweets and text messages automatically, together with the ability to deliver the relevant information to the appropriate personnel are essential for enabling the personnel to timely and efficiently work to address the most urgent needs, and to understand the emergency situation better” (Caragea et al., 2011).

The iPhone application developed by PennState is designed to help humanitarian professionals collect information during a crisis. “In case of no service or Internet access, the application rolls over to local storage until access is available. However, the GPS still works via satellite and is able to geo-locate data being recorded.” The Twitter crawler component captures tweets referring to specific keywords “within a seven-day period as well as tweets that have been posted by specific users. Each API call returns at most 1000 tweets and auxiliary metadata [...].” The machine translation component uses Google Language API.

The more challenging aspect of EMERSE, however, is the automatic classification component. So the team made use of the Ushahidi Haiti data, which includes some 3,500 reports about half of which came from text messages. Each of these reports were tagged according to a specific (but not mutually exclusive category), e.g., Medical Emergency, Collapsed Structure, Shelter Needed, etc. The team at PennState experimented with various techniques from (NLP) and Machine Learning (ML) to automatically classify the Ushahidi Haiti data according to these pre-existing categories. The results demonstrate that “Feature Extraction” significantly outperforms other methods while Support Vector Machine (SVM) classifiers vary significantly depending on the category being coded. I wonder whether their approach is more or less effective than this one developed by the University of Colorado at Boulder.

In any event, PennState’s applied research was presented at the ISCRAM 2011 conference and the findings are written up in this paper (PDF): “Classifying Text Messages for the Haiti Earthquake.” The co-authors: Cornelia Caragea, Nathan McNeese, Anuj Jaiswal, Greg Traylor, Hyun-Woo Kim, Prasenjit Mitra, Dinghao Wu, Andrea H. Tapia, Lee Giles, Bernard J. Jansen, John Yen.

In conclusion, the team at PennState argue that the EMERSE system offers four important benefits not provided by Ushahidi.

“First, EMERSE will automatically classify tweets and text messages into topic, whereas Ushahidi collects reports with broad category information provided by the reporter. Second, EMERSE will also automatically geo-locate tweets and text messages, whereas Ushahidi relies on the reporter to provide the geo-location information. Third, in EMERSE, tweets and text messages are aggregated by topic and region to better understand how the needs of Haiti differ by regions and how they change over time. The automatic aggregation also helps to verify reports. A large number of similar reports by different people are more likely to be true. Finally, EMERSE will provide tweet broadcast and GeoRSS subscription by topics or region, whereas Ushahidi only allows reports to be downloaded.”

In terms of future research, the team may explore other types of abstraction based on semantically related words, and may also “design an emergency response ontology [...].” So I recently got in touch with Andrea to get an update on this since their ISCRAM paper was published 14 months ago. I’ll be sure to share any update if this information can be made public.

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Posted in Crowdsourcing, Humanitarian Tech, Social Computing, Social Media, Ushahidi

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DeadUshahidi: Neither Dead Right Nor Dead Wrong

Posted on July 5, 2012 | 2 Comments

There’s a new Crowdmap in town called DeadUshahidi. The site argues that “Mapping doesn’t equal change. Using crowdsourcing tech like Ushahidi maps without laying the strategic and programmatic ground work is likely not going to work. And while we think great work has been done with crowdsourced reporting, there is an increasing number of maps that are set up with little thought as to why, who should care, and how the map leads to any changes.”

In some ways this project is stating the obvious, but the obvious sometimes needs repeating. As Ushahidi’s former Executive Director Ory Okolloh warned over two years ago: “Don’t get too jazzed up! Ushahidi is only 10% of solution.” My own doctoral research, which included a comparative analysis of Ushahidi’s use in Egypt and the Sudan, demonstrated that training, preparedness, outreach and strategic partnerships were instrumental. So I do appreciate DeadUshahidi’s constructive (and entertaining!) efforts to call attention to this issue and explain what makes a good crowd-sourced map.

At the same time, I think some of the assumptions behind this initiative need questioning. According to the project, maps with at least one of the following characteristics is added to the cemetery:

  • No one has submitted a report to your map in the last 12 months.
  • For time-bound events, like elections and disasters, the number of reports are so infinitesimally small (in relation to the number of the community the map is targeting) that the map never reached a point anywhere near relevance. (Our measure for elections is, for instance, # of submissions / # of registered voters > .0001).
  • The map was never actually started (no category descriptions, fewer than 10 reports). We call that a stillbirth.

Mapping doesn’t equal change, but why assume that every single digital map is launched to create change? Is every blog post written to create change? Is every Wikipedia article edit made to effect change? Every tweet? What was the impact of the last hard copy map you saw? Intention matters and impact cannot be measured without knowing the initial motivations behind a digital map, the intended theory of change and some kind of baseline to measure said change. Also, many digital maps are event-based and thus used for a limited period of time only. They may no longer receive new reports a year after the launch, but this doesn’t make it a “dead” map, simply a completed project. A few may even deserve to go to map heaven—how about a UshahidiHeaven crowdmap?

I’m also not entirely convinced by the argument that the number of reports per map has to cross a certain threshold for the crowdsourced map to be successful. A digital map of a neighborhood in Sydney with fewer than one hundred reports could very well have achieved the intended goal of the project. So again, without knowing or being able to reliably discern the motivations behind a digital map, it is rather farfetched to believe that one can assess whether a project was success-ful or not. Maybe most of the maps in the DeadUshahidi cemetery were never meant to live beyond a few days, weeks or months in the first place.

That said, I do think that one of the main challenges with Ushahidi/Crowdmap use is that the average number of reports per map is very, very low. Indeed, the vast majority of Crowdmaps are stillborn as a forthcoming study from Internews shows. Perhaps this long-tail effect shouldn’t be a surprise though. The costs of experimenting are zero and the easier the technology gets, the more flowers will bloom—or rather the more seeds become available. Whether these free and open source seeds actually get planted and grow into flowers (let alone lush eco-systems) is another issue and one dependent on a myriad of factors such as the experience of the “gardener”, the quality of the seeds, the timing and season, the conditions of the soil and climate, and the availability of other tools used for planting and cultivation.

Or perhaps a better analogy is photography. Thanks to Digital Cameras, we take zillions more pictures than we did just 5 years ago because each click is virtually free. We’re no longer limited to 24 or 36 pictures per roll of film, which first required one to buy said roll and later to pay for it again to be developed. As a result of digital cameras, one could argue that there are now a lot more bad quality (dead) pictures being uploaded everywhere. So what? Big deal. There is also more excellent amateur photography out there as well. What about other technologies and media? There are countless of “dead” Twitter accounts, WordPress blogs, Ning platforms, customized Google Maps, etc. Again, so what?

Neogeography is about democratizing map-making and user-generated maps. Naturally, there’s going to be learning and experimentation involved. So my blog post is not written in defense of Ushahidi/Crowdmap but rather in defense of all amateur digital mappers out there who are curious and just want to map whatever the heck they well please. In sum, and to return to the gardening analogy if I may, the more important question here is why the majority of (Usha)seeds aren’t planted or don’t grow, and what can be done about this in a pro-active manner. Is there something wrong with the seed? Do would-be gardeners simply need more gardening manuals? Or do they need more agile micro-tasking and data-mining tools? The upcoming Internews report goes a long way to explaining the why & what and TechChange’s course on Ushahidi may be one way to save some future maps from ending up in the DeadUshahidi cemetery prematurely.

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Posted in Crowdsourcing, Digital Activism, Social Media, Ushahidi

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Evolution in Live Mapping: The 2012 Egyptian Presidential Elections

Posted on July 2, 2012 | 3 Comments

My doctoral dissertation compared the use of live mapping technology in Egypt and the Sudan during 2010. That year was the first time that Ushahidi was deployed in those two countries. So it is particularly interesting to see the technology used again in both countries in 2012. Sudanese activists are currently using the platform to map #SudanRevolts while Egyptian colleagues have just used the tool to monitor the recent elections in their country.

Analyzing the evolution of live mapping technology use in non-permissive environments ought to make for a very interesting piece of research (any takers?). In the case of Egypt, one could compare the use of the same technology and methods before and after the fall of Mubarak. In 2010, the project was called U-Shahid. This year, the initiative was branded as the “Egypt Elections Project.”

According to my colleagues in Cairo who managed the interactive map, “more than 15 trainers and 75 coordinators were trained to work in the ‘operation room’ supporting 2200 trained observers scattered all over Egypt. More than 17,000 reports, up to 25000 short messages were sent by the observers and shown on Ushahid’s interactive map. Although most reports received shown a minimum amount of serious violations, and most of them were indicating the success of the electoral process, our biggest joy was being able to monitor freely and to report the whole process with full transparency.”

Contrast this situation with how Egyptian activists struggled to keep their Ushahidi project alive under Mubarak in 2010. Last week, the team behind the current live map was actually interviewed by state television (picture above), which was formerly controlled by the old regime. Interestingly, the actual map is no longer the centerpiece of the project when compared to the U-Shahid deploy-ment. The team has included and integrated a lot more rich multimedia content in addition to data, statistics and trends analysis. Moreover, there appears to be a shift towards bounded crowdsourcing rather than open crowd-sourcing as far as election mapping projects go.

These two live mapping projects in Egypt and the Sudan are also getting relatively more traction than those in 2010. Some 17,000 reports were mapped in this year’s election project compared to 2,700 two years ago. Apparently, “millions of users logged into the [Egypt Project Elections] site to check the outcome of the electoral process,” compared to some 40,000 two years ago. Sudanese activists in Khartoum also appear to be far better organized and more agile at leverage social media channels to garner support for their movement than in 2010. Perhaps some of the hard lessons from those resistance efforts were learned.

This learning factor is key and relates to an earlier blog post I wrote on “Technology and Learning, Or Why the Wright Brothers Did Not Create the 747.” Question is: do repressive regimes learn faster or do social movements operate with more agile feedback loops? Indeed, perhaps the technology variable doesn’t matter the most. As I explained to Newsweek a while back, “It is the organiza-tional structure that will matter the most. Rigid structures are unable to adapt as quickly to a rapidly changing environment as a decentralized system. Ultimately, it is a battle of organizational theory.” In the case of Egypt and Sudan today, there’s no doubt that activists in both countries are better organized while the technologies themselves haven’t actually changed much since 2010. But better organization is a necessary, not sufficient, condition to catalyze positive social change and indirect forms of democracy.

Pierre Rosanvallon (2008) indentifies three channels whereby civil society can hold the state accountable during (and in between) elections, and independent of their results.

“The first refers to the various means whereby citizens (or, more accurately, organizations of citizens) are able to monitor and publicize the behavior of elected and appointed rulers; the second to their capacity to mobilize resistance to specific policies, either before or after they have been selected; the third to the trend toward ‘juridification’ of politics when individuals or social groups use the courts and, especially, jury trials to bring delinquent politicians to judgment.”

Live maps and crowdsourcing can be used to monitor and publicize the behavior of politicians. The capacity to mobilize resistance and bring officials to judgment may require a different set of strategies and technologies, however. Those who don’t realize this often leave behind a cemetery of dead maps.

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Posted in Crisis Mapping, Crowdsourcing, Digital Activism, Social Media, Ushahidi

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Crisis Mapping the End of Sudan’s Dictatorship?

Posted on June 24, 2012 | 8 Comments

Anyone following the twitter hashtag #SudanRevolts in recent days must be stunned by the shocking lack of coverage in the mainstream media. The protests have been escalating since June 17 when female students at the University of Khartoum began demonstrating against the regime’s austerity measures, which are increasing the prices of basic commodities and removing fuel subsidies. The dissent has quickly spread to other universities and communities.

There’s no doubt that Sudan’s dictator is in trouble. He faces international economic sanctions and a mounting US$2.5 billion budget deficit following the secession of South Sudan last year. What’s more, he is also “fighting expensive, devastating, and unpopular wars in Darfur (in the west), Blue Nile, Southern Kordofan, and the Nuba Mountains (on the border with South Sudan)” (UN Dispatch). So what next?

Enter Sudan Change Now, a Sudanese political movement with a clear mandate: peaceful but total democratic change. They seek to “defeat the present power of darkness using all necessary tools of peace resistance to achieve political stability and social peace.” The movement is thus “working on creating a common front that incorporates all victims of the current regime to ensure a unified and effective course of action to overthrow it.” Here are some important videos they have captured of the protests.

According to GlobalVoices, “The Sudanese online community believe that media coverage was an integral part of the revolutions in Egypt and Tunisia, and are therefore demanding the same for Sudan.” The political movement Sudan Change Now is thus turning to crisis mapping to cast more light on the civil resistance efforts in the Sudan:

https://sudanchangenow2012.crowdmap.com

The crisis map includes over 50 individual reports (all added in the past 24 hours) ranging from female protestors confronting armed guards to Sudanese security forces using tear gas to break up demonstrations. There are also reports of detained activists and journalists. These reports come from twitter while more recent incidents are sourced from the little mainstream media coverage that currently exists. The live map is being updated several times a day.

As my colleague Carol Gallo reminds us, “The University of Khartoum was also the birthplace of the movement that led to the overthrow of the military government in 1964.” Symbols and anniversaries are important features of civil resistance. For example, Sudan’s current ruling party came to power on June 30th, 1989. So protestors including those with Sudan Change Now are gearing up for some major demonstrations this Wednesday.

This is not the first crisis map of protests in Khartoum. In January 2011, activists launched this crisis map. I hope that protestors engaged in current civil resistance efforts take note of the lessons learned from last year’s #Jan30 demonstrations. For my doctoral dissertation, I compared the use of crisis maps by Egyptian and Sudanese activists in 2010. If I had to boil down the findings into three key words, these would be: unity, preparedness, creativity.

Unity is absolutely instrumental in civil resistance. As for preparedness, nothing should be left to chance. Prepare and plan the sequence of civil resistance efforts (along with likely reactions) and remember that protests come at the end. The ground-work must first be laid with other civil resistance tactics and thence escalated. Finally, creativity is essential, so here are some tactics that may provide some ideas. They include both traditional tactics and technology-enabled ones like digital crisis maps.

NB: I understand that the security risks of using the Ushahidi mapping platform have been indirectly communicated to the activists.

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Disaster Response, Self-Organization and Resilience: Shocking Insights from the Haiti Humanitarian Assistance Evaluation

Posted on May 23, 2012 | 6 Comments

Tulane University and the State University of Haiti just released a rather damming evaluation of the humanitarian response to the 2010 earthquake that struck Haiti on January 12th. The comprehensive assessment, which takes a participatory approach and applies a novel resilience framework, finds that despite several billion dollars in “aid”, humanitarian assistance did not make a detectable contribution to the resilience of the Haitian population and in some cases increased certain communities’ vulnerability and even caused harm. Welcome to supply-side humanitarian assistance directed by external actors.

“All we need is information. Why can’t we get information?” A quote taken from one of many focus groups conducted by the evaluators. “There was little to no information exchange between the international community tasked with humanitarian response and the Haitian NGOs, civil society or affected persons / communities themselves.” Information is critical for effective humanitarian assistance, which should include two objectives: “preventing excess mortality and human suffering in the immediate, and in the longer term, improving the community’s ability to respond to potential future shocks.” This longer term objective thus focuses on resilience, which the evaluation team defines as follows:

“Resilience is the capacity of the affected community to self-organize, learn from and vigorously recover from adverse situations stronger than it was before.”

This link between resilience and capacity for self-organization is truly profound and incredibly important. To be sure, the evaluation reveals that “the humani-tarian response frequently undermined the capacity of Haitian individuals and organizations.” This completely violates the Hippocratic Oath of Do No Harm. The evaluators thus “promote the attainment of self-sufficiency, rather than the ongoing dependency on standard humanitarian assistance.” Indeed, “focus groups indicated that solutions to help people help themselves were desired.”

I find it particularly telling that many aid organizations interviewed for this assessment were reluctant to assist the evaluators in fully capturing and analyzing resource flows, which are critical for impact evaluation. “The lack of transparency in program dispersal of resources was a major constraint in our research of effective program evaluation.” To this end, the evaluation team argue that “by strengthening Haitian institutions’ ability to monitor and evaluate, Haitians will more easily be able to track and monitor international efforts.”

I completely disagree with this remedy. The institutions are part of the problem, and besides, institution-building takes years if not decades. To assume there is even political will and the resources for such efforts is at best misguided. If resilience is about strengthening the capacity of affected communities to self-organize, then I would focus on just that, applying existing technologies and processes that both catalyze and facilitate demand-side, people-centered self-organization. My previous blog post on “Technology and Building Resilient Societies to Mitigate the Impact of Disasters” elaborates on this point.

In sum, “resilience is the critical link between disaster and development; monitoring it will ensure that relief efforts are supporting, and not eroding, household and community capabilities.” This explains why crowdsourcing and data mining efforts like those of Ushahidi, HealthMap and UN Global Pulse are important for disaster response, self-organization and resilience.

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Crisis Mapping Syria: Automated Data Mining and Crowdsourced Human Intelligence

Posted on March 25, 2012 | 22 Comments

The Syria Tracker Crisis Map is without doubt one of the most impressive crisis mapping projects yet. Launched just a few weeks after the protests began one year ago, the crisis map is spearheaded by a just handful of US-based Syrian activists have meticulously and systematically documented 1,529 reports of human rights violations including a total of 11,147 killings. As recently reported in this NewScientist article, “Mapping the Human Cost of Syria’s Uprising,” the crisis map “could be the most accurate estimate yet of the death toll in Syria’s uprising [...].” Their approach? “A combination of automated data mining and crowdsourced human intelligence,” which “could provide a powerful means to assess the human cost of wars and disasters.”

On the data-mining side, Syria Tracker has repurposed the HealthMap platform, which mines thousands of online sources for the purposes of disease detection and then maps the results, “giving public-health officials an easy way to monitor local disease conditions.” The customized version of this platform for Syria Tracker (ST), known as HealthMap Crisis, mines English information sources for evidence of human rights violations, such as killings, torture and detainment. As the ST Team notes, their data mining platform “draws from a broad range of sources to reduce reporting biases.” Between June 2011 and January 2012, for example, the platform collected over 43,o00 news articles and blog posts from almost 2,000 English-based sources from around the world (including some pro-regime sources).

Syria Tracker combines the results of this sophisticated data mining approach with crowdsourced human intelligence, i.e., field-based eye-witness reports shared via webform, email, Twitter, Facebook, YouTube and voicemail. This naturally presents several important security issues, which explains why the main ST website includes an instructions page detailing security precautions that need to be taken while sub-mitting reports from within Syria. They also link to this practical guide on how to protect your identity and security online and when using mobile phones. The guide is available in both English and Arabic.

Eye-witness reports are subsequently translated, geo-referenced, coded and verified by a group of volunteers who triangulate the information with other sources such as those provided by the HealthMap Crisis platform. They also filter the reports and remove dupli-cates. Reports that have a low con-fidence level vis-a-vis veracity are also removed. Volunteers use a dig-up or vote-up/vote-down feature to “score” the veracity of eye-witness reports. Using this approach, the ST Team and their volunteers have been able to verify almost 90% of the documented killings mapped on their platform thanks to video and/or photographic evidence. They have also been able to associate specific names to about 88% of those reported killed by Syrian forces since the uprising began.

Depending on the levels of violence in Syria, the turn-around time for a report to be mapped on Syria Tracker is between 1-3 days. The team also produces weekly situation reports based on the data they’ve collected along with detailed graphical analysis. KML files that can be uploaded and viewed using Google Earth are also made available on a regular basis. These provide “a more precisely geo-located tally of deaths per location.”

In sum, Syria Tracker is very much breaking new ground vis-a-vis crisis mapping. They’re combining automated data mining technology with crowdsourced eye-witness reports from Syria. In addition, they’ve been doing this for a year, which makes the project the longest running crisis maps I’ve seen in a hostile environ-ment. Moreover, they’ve been able to sustain these import efforts with just a small team of volunteers. As for the veracity of the collected information, I know of no other public effort that has taken such a meticulous and rigorous approach to documenting the killings in Syria in near real-time. On February 24th, Al-Jazeera posted the following estimates:

Syrian Revolution Coordination Union: 9,073 deaths
Local Coordination Committees: 8,551 deaths
Syrian Observatory for Human Rights: 5,581 deaths

At the time, Syria Tracker had a total of 7,901 documented killings associated with specific names, dates and locations. While some duplicate reports may remain, the team argues that “missing records are a much bigger source of error.” Indeed, They believe that “the higher estimates are more likely, even if one chooses to disregard those reports that came in on some of the most violent days where names were not always recorded.”

The Syria Crisis Map itself has been viewed by visitors from 136 countries around the world and 2,018 cities—with the top 3 cities being Damascus, Washington DC and, interestingly, Riyadh, Saudia Arabia. The witnessing has thus been truly global and collective. When the Syrian regime falls, “the data may help sub-sequent governments hold him and other senior leaders to account,” writes the New Scientist. This was one of the principle motivations behind the launch of the Ushahidi platform in Kenya over four years ago. Syria Tracker is powered by Ushahidi’s cloud-based platform, Crowdmap. Finally, we know for a fact that the International Criminal Court (ICC) and Amnesty International (AI) closely followed the Libya Crisis Map last year.

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Posted in Big Data, Crisis Mapping, Crowdsourcing, Digital Activism, Social Computing, Social Media, Ushahidi

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#UgandaSpeaks: Al-Jazeera uses Ushahidi to Amplify Local Voices in Response to #Kony2012

Posted on March 14, 2012 | 2 Comments

[Cross-posted from the Ushahidi blog]

Invisible Children’s #Kony2012 campaign has set off a massive firestorm of criticism with the debate likely to continue raging for many more weeks and months. In the meantime, our colleagues at Al-Jazeera have repurposed our previous #SomaliaSpeaks project to amplify Ugandan voices responding to the Kony campaign: #UgandaSpeaks.

Other than GlobalVoices, this Al-Jazeera initiative is one of the very few seeking to amplify local reactions to the Kony campaign. Over 70 local voices have been shared and mapped on Al-Jazeera’s Ushahidi platform in the first few hours since the launch. The majority of reactions submitted thus far are critical of the campaign but a few are positive.

One person from Kampala asks, “How come the world now knows more about #Kony2012 than about the Nodding Syndrome in Northern Uganda?” Another person in Gulu complains that “there is nothing new they are showing us. Its like a campaign against our country. [...] Did they put on consideration how much its costing our country’s image? It shows as if Uganda is finished.” In nearby Lira, one person shares their story about growing up in Northern Uganda and attending “St. Mary’s College Aboke, a school from which Joseph Kony’s rebels abducted 139 girls in ordinary level [...]. For the 4 years that I spent in that school (1999-2002), together with other students, I remember praying the Rosary at the School Grotto on daily basis and in the process, reading out the names of the 30 girls who had remained in captivity after Sr. Rachelle an Italian Nun together with a Ugandan teacher John Bosco rescued only 109 of them.”

The Ushahidi platform was first launched in neighboring Kenya to give ordinary Kenyans a voice during the post election-violence in 2007/2008. Indeed, “ushahidi” means witness or testimony in Swahili. So I am pleased to see this free and open source platform from Africa being used to amplify voices next door in Uganda, voices that are not represented in the #Kony2012 campaign.

Some Ugandan activists are asking why they should respond to “some American video release about something that happened 20 years ago by someone who is not in my country?” Indeed, why should anyone? If the #Kony2012 campaign and underlying message doesn’t bother Ugandans and doesn’t paint the country in a bad light, then there’s no need to respond. If the campaign doesn’t divert attention from current issues that are more pressing to Ugandans and does not adversely effect tourism, then again, why should anyone respond? This is, after all a personal choice, no one is forced to have their voices heard.

At SXSW yesterday, Ugandan activist Teddy Ruge weighed in on the #Kony2012 campaign with the following:

“We [Ugandans] have such a hard time being given the microphone to talk about our issues that sometimes we have to follow on the coat-tails of Western projects like this one and say that we also have a voice in this matter.”

I believe one way to have those local voices heard is to have them echoed using innovative software “Made in Africa” like Ushahidi and then amplified by a non-Western but international news company like Al-Jazeera. Looking at my Twitter stream this morning, it appears that I’m not the only one. The microphone is yours. Over to you.

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Posted in Crisis Mapping, Crowdsourcing, iRevolution, Social Media, Ushahidi

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Trails of Trustworthiness in Real-Time Streams

Posted on March 3, 2012 | 1 Comment

Real-time information channels like Twitter, Facebook and Google have created cascades of information that are becoming increasingly challenging to navigate. “Smart-filters” alone are not the solution since they won’t necessarily help us determine the quality and trustworthiness of the information we receive. I’ve been studying this challenge ever since the idea behind SwiftRiver first emerged several years ago now.

I was thus thrilled to come across a short paper on “Trails of Trustworthiness in Real-Time Streams” which describes a start-up project that aims to provide users with a “system that can maintain trails of trustworthiness propagated through real-time information channels,” which will “enable its educated users to evaluate its provenance, its credibility and the independence of the multiple sources that may provide this information.” The authors, Panagiotis Metaxas and Eni Mustafaraj, kindly cite my paper on “Information Forensics” and also reference SwiftRiver in their conclusion.

The paper argues that studying the tactics that propagandists employ in real life can provide insights and even predict the tricks employed by Web spammers.

“To prove the strength of this relationship between propagandistic and spamming techniques, [...] we show that one can, in fact, use anti-propagandistic techniques to discover Web spamming networks. In particular, we demonstrate that when starting from an initial untrustworthy site, backwards propagation of distrust (looking at the graph defined by links pointing to to an untrustworthy site) is a successful approach to finding clusters of spamming, untrustworthy sites. This approach was inspired by the social behavior associated with distrust: in society, recognition of an untrustworthy entity (person, institution, idea, etc) is reason to question the trust- worthiness of those who recommend it. Other entities that are found to strongly support untrustworthy entities become less trustworthy themselves. As in society, distrust is also propagated backwards on the Web graph.”

The authors document that today’s Web spammers are using increasingly sophisticated tricks.

“In cases where there are high stakes, Web spammers’ influence may have important consequences for a whole country. For example, in the 2006 Congressional elections, activists using Google bombs orchestrated an effort to game search engines so that they present information in the search results that was unfavorable to 50 targeted candidates. While this was an operation conducted in the open, spammers prefer to work in secrecy so that their actions are not revealed. So,  revealed and documented the first Twitter bomb, which tried to influence the Massachusetts special elections, show- ing how an Iowa-based political group, hiding its affiliation and profile, was able to serve misinformation a day before the election to more than 60,000 Twitter users that were follow- ing the elections. Very recently we saw an increase in political cybersquatting, a phenomenon we reported in [28]. And even more recently, […] we discovered the existence of Pre-fabricated Twitter factories, an effort to provide collaborators pre-compiled tweets that will attack members of the Media while avoiding detection of automatic spam algorithms from Twitter.

The theoretical foundations for a trustworthiness system:

“Our concept of trustworthiness comes from the epistemology of knowledge. When we believe that some piece of information is trustworthy (e.g., true, or mostly true), we do so for intrinsic and/or extrinsic reasons. Intrinsic reasons are those that we acknowledge because they agree with our own prior experience or belief. Extrinsic reasons are those that we accept because we trust the conveyor of the information. If we have limited information about the conveyor of information, we look for a combination of independent sources that may support the information we receive (e.g., we employ “triangulation” of the information paths). In the design of our system we aim to automatize as much as possible the process of determining the reasons that support the information we receive.”

“We define as trustworthy, information that is deemed reliable enough (i.e., with some probability) to justify action by the receiver in the future. In other words, trustworthiness is observable through actions.”

“The overall trustworthiness of the information we receive is determined by a linear combination of (a) the reputation RZ of the original sender Z, (b) the credibility we associate with the contents of the message itself C(m), and (c) characteristics of the path that the message used to reach us.”

“To compute the trustworthiness of each message from scratch is clearly a huge task. But the research that has been done so far justifies optimism in creating a semi-automatic, personalized tool that will help its users make sense of the information they receive. Clearly, no such system exists right now, but components of our system do exist in some of the popular [real-time information channels]. For a testing and evaluation of our system we plan to use primarily Twitter, but also real-time Google results and Facebook.”

In order to provide trails of trustworthiness in real-time streams, the authors plan to address the following challenges:

•  ”Establishment of new metrics that will help evaluate the trustworthiness of information people receive, especially from real-time sources, which may demand immediate attention and action. […] we show that coverage of a wider range of opinions, along with independence of results’ provenance, can enhance the quality of organic search results. We plan to extend this work in the area of real-time information so that it does not rely on post-processing procedures that evaluate quality, but on real-time algorithms that maintain a trail of trustworthiness for every piece of information the user receives.”

• “Monitor the evolving ways in which information reaches users, in particular citizens near election time.”

•  ”Establish a personalizable model that captures the parameters involved in the determination of trustworthiness of in- formation in real-time information channels, such as Twitter, extending the work of measuring quality in more static information channels, and by applying machine learning and data mining algorithms. To implement this task, we will design online algorithms that support the determination of quality via the maintenance of trails of trustworthiness that each piece of information carries with it, either explicitly or implicitly. Of particular importance, is that these algorithms should help maintain privacy for the user’s trusting network.”

• “Design algorithms that can detect attacks on [real-time information channels]. For example we can automatically detect bursts of activity re- lated to a subject, source, or non-independent sources. We have already made progress in this area. Recently, we advised and provided data to a group of researchers at Indiana University to help them implement “truthy”, a site that monitors bursty activity on Twitter.  We plan to advance, fine-tune and automate this process. In particular, we will develop algorithms that calculate the trust in an information trail based on a score that is affected by the influence and trustworthiness of the informants.”

In conclusion, the authors “mention that in a month from this writing, Ushahidi […] plans to release SwiftRiver, a platform that ‘enables the filtering and verification of real-time data from channels like Twitter, SMS, Email and RSS feeds’. Several of the features of Swift River seem similar to what we propose, though a major difference appears to be that our design is personalization at the individual user level.”

Indeed, having been involved in SwiftRiver research since early 2009 and currently testing the private beta, there are important similarities and some differences. But one such difference is not personalization. Indeed, Swift allows full personalization at the individual user level.

Another is that we’re hoping to go beyond just text-based information with Swift, i.e., we hope to pull in pictures and video footage (in addition to Tweets, RSS feeds, email, SMS, etc) in order to cross-validate information across media, which we expect will make the falsification of crowdsourced information more challenging, as I argue here. In any case, I very much hope that the system being developed by the authors will be free and open source so that integration might be possible.

A copy of the paper is available here (PDF). I hope to meet the authors at the Berkman Center’s “Truth in Digital Media Symposium” and highly recommend the wiki they’ve put together with additional resources. I’ve added the majority of my research on verification of crowdsourced information to that wiki, such as my 20-page study on “Information Forensics: Five Case Studies on How to Verify Crowdsourced Information from Social Media.”

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Imagery and Humanitarian Assistance: Gems, Errors and Omissions

Posted on February 29, 2012 | 1 Comment

The Center for Technology and National Security Policy based at National Defense University’s Institute for National Strategic Studies just published an 88-page report entitled “Constructive Convergence: Imagery and Humanitarian Assistance.” As noted by the author, “the goal of this paper is to illustrate to the technical community and interested humanitarian users the breadth of the tools and techniques now available for imagery collection, analysis, and distribution, and to provide brief recommendations with suggestions for next steps.” In addition, the report ”presents a brief overview of the growing power of imagery, especially from volunteers and victims in disasters, and its place in emergency response. It also highlights an increasing technical convergence between professional and volunteer responders—and its limits.”

The study contains a number of really interesting gems, just a few errors and some surprising omissions. The point of this blog post is not to criticize but rather to provide constructive-and-hopefully-useful feedback should the report be updated in the future.

Lets begin with the important gems, excerpted below.

“The most serious issues overlooked involve liability protections by both the publishers and sources of imagery and its data. As far as our research shows there is no universally adopted Good Samaritan law that can protect volunteers who translate emergency help messages, map them, and distribute that map to response teams in the field.”

Whether a Good Samaritan law could ever realistically be universally adopted remains to be seen, but the point is that all of the official humanitarian data protection standards that I’ve reviewed thus far simply don’t take into account the rise of new digitally-empowered global volunteer networks (let alone the existence of social media). The good news is that some colleagues and I are working with the International Committee of the Red Cross (ICRC) and a consor-tium of major humanitarian organizations to update existing data protection protocols to take some of these new factors into account. This new document will hopefully be made publicly available in October 2012.

“Mobile devices such as tablets and mobile phones are now the primary mode for both collecting and sharing information in a response effort. A January 2011 report published by the Mobile Computing Promotion Consortium of Japan surveyed users of smart phones. Of those who had smart phones, 55 percent used a map application, the third most common application after Web browsing and email.”

I find this absolutely fascinating and thus read the January 2011 report, which is where I found the graphic below.

“The rapid deployment of Cellular on Wheels [COW] is dramatically improving. The Alcatel-Lucent Light Radio is 300 grams (about 10 ounces) and stackable. It also consumes very little power, eliminating large generation and storage requirements. It is capable of operating by solar, wind and/or battery power. Each cube fits into the size of a human hand and is fully integrated with radio processing, antenna, transmission, and software management of frequency. The device can operate on multiple frequencies simultaneously and work with existing infrastructure.”

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“In Haiti, USSOUTHCOM found imagery, digital open source maps, and websites that hosted them (such as Ushahidi and OpenStreetMap) to occasionally be of greater value than their own assets.”

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“It is recommended that clearly defined and restricted use of specialized #hashtags be implemented using a common crisis taxonomy. For example:

#country + location + emergency code + supplemental data

The above example, if located in Washington, DC, U.S.A., would be published as:

#USAWashingtonDC911Trapped

The specialized use of #hashtags could be implemented in the same cultural manner as 911, 999, and other emergency phone number systems. Metadata using these tags would also be given priority when sent over the Internet through communication networks (landline, broadband Internet, or mobile text or data). Abuse of ratified emergency #hashtag’s would be a prosecutable offense. Implementing such as system could reduce the amount of data that crisis mappers and other response organizations need to monitor and improve the quality of data to be filtered. Other forms of #Hashtags syllabus can also be implemented such as:

#country + location + information code (411) + supplemental data
#country + location + water (H20) + supplemental data
#country + location + Fire (FD) + supplemental data”

I found this very interesting and relevant to this earlier blog post: “Calling 911: What Humanitarians Can Learn from 50 Years of Crowdsourcing.” Perhaps a reference to Tweak the Tweet would have been worthwhile.

I also had not come across some of the platforms used in response to the 2011 earthquake in New Zealand. But the report did an excellent job sharing these.

EQviewer.co.nz

Some errors that need correcting:

“Open source mapping tools such as Google Earth use imagery as a foundation for layering field data.”

Google Earth is not an open source tool.

“CrisisMappers.net, mentioned earlier, is a group of more than 1,600 volunteers that have been brought together by Patrick Meier and Jen Ziemke. It is the core of collaboration efforts that can be deployed anywhere in the world. CrisisMappers has established workshops and steering committees to set guidelines and standardize functions and capabilities for sites that deliver imagery and layered datasets. This group, which today consists of diverse and talented volunteers from all walks of life, might soon evolve into a professional volunteer organization of trusted capabilities and skill sets and they are worth watching.”

CrisisMappers is not a volunteer network or an organization that deploys in any formal sense of the word. The CrisisMappers website explains what the mission and purpose of this informal network is. The initiative has some 3,500 members.

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“Figure 16. How Ushahidi’s Volunteer Standby Task Force was Structured for Libya. Ushahidi’s platform success stems from its use by organized volunteers, each with skill sets that extract data from multiple sources for publication.”

The Standby Volunteer Task Force (SBTF) does not belong to Ushahidi, nor is the SBTF an Ushahidi project. A link to the SBTF website would have been appropriate. Also, the majority of applications of the Ushahidi platform have nothing to do with crises, or the SBTF, or any other large volunteer networks. The SBTF’s original success stems from organized volunteers who where well versed in the Ushahidi platform.

“Ushahidi accepts KML and KMZ if there is an agreement and technical assistance resources are available. An end user cannot on their own manipulate a Ushahidi portal as an individual, nor can external third party groups unless that group has an arrangement with the principal operators of the site. This offers new collaboration going forward. The majority of Ushahidi disaster portals are operated by volunteer organizations and not government agencies.”

The first sentence is unclear. If someone sets up an Ushahidi platform and they have KML/KMZ files that they want to upload, they can go ahead and do so. An end-user can do some manipulation of an Ushahidi portal and can also pull the Ushahidi data into their own platform (via the GeoRSS feed, for example). Thanks to the ESRI-Ushahidi plugin, they can then perform a range of more advanced GIS analysis. In terms of volunteers vs government agencies, indeed, it appears the former is leading the way vis-a-vis innovation.

Finally, below are some omissions and areas that I would have been very interested to learn more about. For some reason, the section on the Ushahidi deployment in New Zealand makes no reference to Ushahidi.

Staying on the topic of the earthquake in Christchurch, I was surprised to see no reference to the Tomnod deployment:

I had also hoped to read more about the use of drones (UAVs) in disaster response since these were used both in Haiti and Japan. What about the rise of DIY drones and balloon mapping? Finally, the report’s reference to Broadband Global Area Network (BGAN) doesn’t provide information on the range of costs associated with using BGANs in disasters.

In conclusion, the report is definitely an important contribution to the field of crisis mapping and should be required reading.

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Posted in Crisis Mapping, Crowdsourcing, Humanitarian Tech, Satellite Imagery, Ushahidi

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