Tag Archives: Egypt

Social Media as Passive Polling: Prospects for Development & Disaster Response

My Harvard/MIT colleague Todd Mostak wrote his award-winning Master’s Thesis on “Social Media as Passive Polling: Using Twitter and Online Forums to Map Islamism in Egypt.” For this research, Todd evaluated the “potential of Twitter as a source of time-stamped, geocoded public opinion data in the context of the recent popular uprisings in the Middle East.” More specifically, “he explored three ways of measuring a Twitter user’s degree of political Islamism.” Why? Because he wanted to test the long-standing debate on whether Islamism is associated with poverty.

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So Todd collected millions of geo-tagged tweets from Egypt over a six month period, which he then aggregated by census district in order to regress proxies for poverty against measures of Islamism drived from the tweets and the users’ social graphs. His findings reveal that “Islamist sentiment seems to be positively correlated with male unemployment, illiteracy, and percentage of land used in agriculture and negatively correlated with percentage of men in their youth aged 15-25. Note that female variables for unemployment and age were statistically insignificant.” As with all research, there are caveats such as the weighting scale used for the variables and questions over the reliability of census variables.

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To carry out his graduate research, Todd built a web-enabled database (MapD) powered by a Graphics Processing Units (GPU) to perform real-time querying and visualization of big datasets. He is now working with Harvard’s Center for Geographic Analysis (CGA) to put make this available via a public web interface called Tweetmap. This Big Data streaming and exploration tool presen-tly displays 119 million tweets from 12/10/2012 to 12/31/2012. He is adding 6-7 million new georeferenced tweets per day (but these are not yet publicly available on Tweetmap). According to Todd, the time delay from live tweet to display on the map is about 1 second. Thanks to this GPU-powered approach, he expects that billions of tweets could be displayed in real-time.

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As always with impressive projects, no one single person was behind the entire effort. Ben Lewis, who heads the WorldMap initiative at CGA deserves a lot of credit for making Tweetmap a reality. Indeed, Todd collaborated directly with CGA’s Ben Lewis throughout this project and benefited extensively from his expertise. Matt Bertrand (lead developer for CGA) did the WorldMap-side integration of MapD to create the TweetMap interface.

Todd and I recently spoke about integrating his outstanding work on automated live mapping to QCRI’s Twitter Dashboard for Disaster Response. Exciting times. In the meantime, Todd has kindly shared his dataset of 700+ million geotagged tweets for my team and I to analyze. The reason I’m excited about this approach is best explained with this heatmap of the recent snow-storm in the northeastern US. Todd is already using Tweetmap for live crisis mapping. While this system filters by keyword, our Dashboard will use machine learning to provide more specific streams of relevant tweets, some of which could be automatically mapped on Tweetmap. See Todd’s Flickr page for more Tweetmap visuals.

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I’m also excited by Todd’s GPU-powered approach for a project I’m exploring with UN and World Bank colleagues. The purpose of that research project is to determine whether socio-economic trends such as poverty and unemployment can be captured via Twitter. Our first case study is Egypt. Depending on the results, we may be able to take it one step further by applying sentiment analysis to real-time, georeferenced tweets to visualize Twitter users’ per-ception vis-a-vis government services—a point of interest for my UN colleagues in Cairo.

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

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.

Evolution in Live Mapping: The 2012 Egyptian Presidential Elections

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.

Using Rayesna to Track the 2012 Egyptian Presidential Candidates on Twitter

My (future) colleague at the Qatar Foundation’s Computing Research Institute (QCRI) have just launched a new platform that Al Jazeera is using to track the 2012 Egyptian Presidential Candidates on Twitter. Called Rayesna, which  means “our president” in colloquial Egyptian Arabic, this fully automated platform uses cutting-edge Arabic computational linguistics processing developed by the Arabic Language Technology (ALT) group at QCRI.

“Through Rayesna, you can find out how many times a candidate is mentioned, which other candidate he is likely to appear with, and the most popular tweets for a candidate, with a special category for the most retweeted jokes about the candidates. The site also has a time-series to explore and compares the mentions of the candidate day-by-day. Caveats: 1. The site reflects only the people who choose to tweet, and this group may not be representative of general society; 2. Tweets often contain foul language and we do not perform any filtering.”

I look forward to collaborating with the ALT group and exploring how their platform might also be used in the context of humanitarian response in the Arab World and beyond. There may also be important synergies with the work of the UN Global Pulse, particularly vis-a-vis their use of Twitter for real-time analysis of vulnerable communities.

Building Egypt 2.0: When Institutions Fail, Crowdsourcing Surges

I recently presented at Where 2.0 and had the chance to catch Adel Youssef’s excellent talk on “How Location Based Services is Used to Build Egypt 2.0.” He shared some important gems on digital activism. For example, while Facebook allowed Egyptians to “like” a protest event or say they were headed to the streets, check-in’s were a more powerful way to recruit others because they let your friends know that you were actively in the location and actually protesting. In other words, activists were not checking into a place per se, but rather creating an event and checking into that to encourage people to participate in said event.

Adel also shared some interesting insights on how location-aware mobile tech-nologies are being used to build a new Egypt. “After the revolution, the police force just disappeared, there is no police; and there is no traffic control. But this drove more crowdsourced traffic control, crowdsourced police, crowdsourced services. And this has been happening in the last year alone. Crowdsourcing revolution. But not a revolution to overthrow a tyrant but a revolution to build a developed country. [...] People going to clean the streets, planting trees, repainting the streets. And they are feeling ownership of their campaign.”

Adel shared several other crowdsourcing initiatives in his talk, from OneYad (matching volunteers) and Zabatak (monitoring corruption) to EntaFeen (check-in’s for good), Bey2Ollak and Wasalny (both addressing the problem of road traffic). I’m excited by all this innovation happening elsewhere than Silicon Valley and hope these platforms will go mainstream beyond the region in the near future. Indeed, I just signed up for the OneYad beta because I really think this kind of tool could be used in the West.

Adel: ”We see a lot of crowdsourced networks built after the revolution because we need to build the country and we want to do this bottom-up, want to do it by the people, you want to empower the people.” The point, for Adel, is to go “from social networking to social working” and thus fill the gaps in services that institutions are failing to provide. This reminded me of Tunisian Ambassador Mohamed Salah Tekaya’s remarks last year: “During the Arab Spring, we have seen the power of Twitter and Facebook… Now we need to use the power of LinkedIn.”

Crowdsourcing Humanitarian Convoys in Libya

Many activists in Egypt donated food and medical supplies to support the Libyan revolution in early 2011. As a result, volunteers set up and coordinated humanitarian convoys from major Egyptian cities to Tripoli. But these convoys faced two major problems. First, volunteers needed to know where the convoys were in order to communicate this to Libyan revolutionists so they could wait for the fleet at the border and escort them to Tripoli. Second, because these volunteers were headed into a war zone, their friends and family wanted to keep track of them to make sure they were safe. The solution? IntaFeen.com.

Inta feen? means “where are you?” in Arabic and IntaFeen.com is a mobile check-in service like Foursquare but localized for the Arab World. Convoy drivers used IntaFeen to check-in at different stops along the way to Tripoli to provide regular updates on the situation. This is how volunteers back in Egypt who coordinated the convoy kept track of their progress and communicated updates in real-time to their Libyan counterparts. Volunteers who went along with the convoys also used IntaFeen and their check-in’s would also get posted on Twitter and Facebook, allowing families and friends in Egypt to track their whereabouts.

Al Amain Road is a highway between Alexandria and Tripoli. These tweets and check-in’s acted as a DIY fleet management system for volunteers and activists.

The use of IntaFeen combined with Facebook and Twitter also created an interesting side-effect in terms of social media marketing to promote activism. The sharing of these updates within and across various social networks galvanized more Egyptians to volunteer their time and resulted in more convoys.

I wonder whether these activists knew about another crowdsourced volunteer project taking place at exactly the same time in support of the UN’s humanitarian relief operations: Libya Crisis Map. Much of the content added to the map was sourced from social media. Could the #LibyaConvoy project have benefited from the real-time situational awareness provided by the Libya Crisis Map?

Will we see more convergence between volunteer-run crisis maps and volunteer-run humanitarian response in the near future?

Big thanks to Adel Youssef from IntaFeen.com who spoke about this fascinating project (and Ushahidi) at Where 2.0 this week. More information on #Libya Convoy is available here. See also my earlier blog posts on the use of check-in’s for activism and disaster response.

Digital Activism, Epidemiology and Old Spice: Why Faster is Indeed Different

The following thoughts were inspired by one of Zeynep Tufekci’s recent posts entitled “Faster is Different” on her Technosociology blog. Zeynep argues “against the misconception that acceleration in the information cycle means would simply mean same things will happen as would have before, but merely at a more rapid pace. So, you can’t just say, hey, people communicated before, it was just slower. That is wrong. Faster is different.”

I think she’s spot on and the reason why goes to the heart of complex systems behavior and network science. “Combined with the reshaping of networks of connectivity from one/few-to-one/few (interpersonal) and one-to-many (broadcast) into many-to-many, we encounter qualitatively different dynamics,” writes Zeynep. In a very neat move, she draws upon “epidemiology and quarantine models to explain why resource-constrained actors, states, can deal with slower diffusion of protests using ‘whack-a-protest’ method whereas they can be overwhelmed by simultaneous and multi-channel uprisings which spread rapidly and ‘virally.’ (Think of it as a modified disease/contagion model).” She then uses the “unsuccessful Gafsa protests in 2008 in Tunisia and the successful Sidi Bouzid uprising in Tunisia in 2010 to illustrate the point.”

I love the use of epidemiology and quarantine models to demonstrate why faster is indeed different. One of the complex systems lectures we had when I was at the Sante Fe Institute (SFI) focused on explaining why epidemics are so unpredictable. It was a real treat to have Duncan Watts himself present his latest research on this question. Back in 1998, he and Steven Strogatz wrote a seminal paper presenting the mathematical theory of the small world phenomenon. One of Duncan’s principle area of research has been information contagion and for his presentation at SFI, he explained that, amazingly, mathematical  epidemiology currently has no way to answer how big a novel outbreak of an infectious disease will get.

I won’t go into the details of traditional mathematical epidemiology and the Standard (SIR) Model but suffice it to say that the main factor thought to determine the spread of an epidemic was the “Basic Reproduction Number”, i.e., the average number of newly infected individuals by a single infected individual in a susceptible population. However, the following epidemics, while differing dramatically in size, all have more or less the same Basic Reproduction Number.

Standard models also imply that outbreaks are “bi-modal” but empirical research clearly shows that epidemics tend to be “multi-modal.” Real epidemics are also resurgent with several peaks interspersed with lulls. So the result is unpredictability: Multi-modal size distributions imply that any given outbreak of the same disease can have dramatically different outcomes while Resurgence implies that even epidemics which seem to be burning out can regenerate themselves by invading new populations.

To this end, there has been a rapid growth in “network epidemiology” over the past 20 years. Studies in network epidemiology suggest that the size of an epidemic depends on Mobility: the expected number of infected individuals “escaping” a local context; and Range: the typical distance traveled.” Of course, the “Basic Reproduction Number” still matters, and has to be greater than 1 as a necessary condition for an epidemic in the first place. However, when this figure is greater than 1, the value itself tells us very little about size or duration. Epidemic size tends to depend instead on mobility and range, although the latter appears to be more influential. To this end, simply restricting the range of travel of infected individuals may be an effective strategy.

There are, however, some important differences in terms of network models being compared here. The critical feature of biological disease in contrast with information spread is that individuals need to be co-located. But recall when during the recent Egyptian revolution the regime had cut off access to the Internet and blocked cell phone use. How did people get their news? The good old fashioned way, by getting out in the streets and speaking in person, i.e., by co-locating. Still, information can be contagious regardless of co-location. This is where Old Spice comes in vis-a-vis their hugely effective marking campaign in 2010 where their popular ads on YouTube went viral and had a significant impact on sales of the deodorant, i.e., massive offline action. Clearly, information can lead to a contagion effect. This is the “information cascade” that Dan Drezner and others refer to in the context of digital activism in repressive environments.

“Under normal circumstances,” Zeynep writes, “autocratic regimes need to lock up only a few people at a time, as people cannot easily rise up all at once. Thus, governments can readily fight slow epidemics, which spread through word-of-mouth (one-to-one), by the selective use of force (a quarantine). No country, however, can jail a significant fraction of their population rising up; the only alternative is excessive violence. Thus, social media can destabilize the situation in unpopular autocracies: rather than relatively low-level and constant repression, regimes face the choice between crumbling in the face of simultaneous protests from many quarters and massive use of force.”
 
For me, the key lesson from mathematical epidemiology is that predicting when an epidemic will go “viral” and thus the size of this epidemic is particularly challenging. In the case of digital activism, the figures for Mobility and Range are even more accentuated than the analogous equivalent for biological systems. Given the ubiquity of information communication networks thanks to the proliferation of social media, Mobility has virtually no limit and nor does Range. That accounts for the speed of “infection” that may ultimately mean the reversal of an information cascade. This unpredictability is why, as Zeynep puts it, “faster is different.” This is also why regimes like that of Mubarak’s and Al-Assad’s try to quarantine information communication and why doing so completely is very difficult, perhaps impossible.
 
Obviously, offline action that leads to more purchases of Old Spice versus offline action that spurs mass protests in Tahrir Square are two very different scenarios. The former may only require weak ties while the latter, due to high-risk actions, may require strong ties. But there are many civil resistance tactics that can be considered as micro-contributions and hence don’t involve relatively high risk to carry out. So communication can still change behavior which may then catalyze high-risk action, especially if said communication comes from someone you know within your own social network. This is one of the keys to effective marketing and advertising strategies. You’re more likely to consider taking offline action if one of your friends or family members do even if there are some risks involved. This is where the “infection” is most likely to take place. These infections can spur low-risk actions at first, which can synchronize “micro-motives” that lead to more risky “macro-behavior” and thus reversals in information cascades.

Identifying Strategic Protest Routes for Civil Resistance: An Analysis of Optimal Approaches to Tahrir Square

My colleague Jessica recently won the Tufts GIS Poster Expo with her excellent poster on civil resistance. She used GIS data to analyze optimal approaches to Tahrir Square in Cairo. According to Jessica, many previous efforts to occupy the square had failed. So Egyptian activists spent two weeks brainstorming the best strategies to approach Tahrir Square.

Out of curiosity, Jessica began to wonder whether the use of GIS data and spatial analysis might shed some light on possible protest routes. She began her analysis by  identifying three critical strategic elements for a successful protest route:

“1) Gathering points where demonstrators initiate protests; 2) two types of routes—protest collection areas of high population density through which protesters walk to collect additional supporters and protest approach routes on major streets that accommodate large groups that are more difficult to disperse; and 3) convergence points where smaller groups of protester merge to increase strength in order to approach the destination.”

For her analysis, Jessica took gathering points and convergence points into consideration. For example, many Egyptian activist met at Mosques. So she selected optimal Mosques based on their distance to police stations (the farther the better) and high road density area “as a proxy for population density.” In terms of convergence points, smaller groups of protestors converged on major roads and intersections. The criteria that Jessica used to select these points were: distance to Tahrir Square, high density of road junctions and open space to allow for large group movement. She also took into account protest route collection areas. These tend to be “densely populated and encourage residents to join, increasing participation.” So Jessica selected these based on high road density and most direct route to Tahrir Square using major roads.

Overlaying the data and using GIS analysis on each strategic element yields the following optimal routes to Tahrir:

Jessica writes that “the results of this project demonstrate that GIS tools can be used for plotting strategic routes for protest using criteria that can change based on the unique geospatial environment. In Cairo, the optimal gathering points, strategic routes and convergence points are not always located in an obvious path (i.e. optimal mosques located in areas with low road density or convergence points without gathering points in the close proximity). The map does, however, provide protest organizers with some basic instruction on where to start, what direction to head and where to converge for the final approach.”

She does also acknowledge some of the limitations of the study owing to lack of high-resolution spatial data. I would add temporal data since civil resistance is fluid and changes, which requires rapid adaptation and re-strategizing. If her analysis could be combined with real time information coming from crowdsourced data such as U-Shahid, then I think this could be quite powerful.

For more on the civil resistance tactics used in Egypt during the revolution, please see this blog post.

How Egyptian Activists Kept Their Ushahidi Project Alive Under Mubarak

This is my second blog post on the U-Shahid project in Egypt. The first one analyzed 2,000+ reports mapped on the Ushahidi platform during the country’s recent Parliamentary Elections. Egypt is one of my dissertation case studies and in this blog post I summarize some initial findings based on a series of interviews I had several Egyptian activists who were part of the U-Shahid project.

The Egyptian government began asking questions about U-Shahid well before the project was even launched. They found out about the project by tapping phone lines and emails. Once the project was launched, the Egyptian Ministry of the Interior continued to shadow the project in several ways. They requested copies of all meeting agendas and a list of names for everyone who was trained on the Ushahidi platform, for example.

In order to remain operational, the Egyptian activists spearheading the U-Shahid project said that they “stressed the technical aspect of the project, and remained fully open and transparent about our work. We gave Egyptian National Security a dedicated username and password [to access the Ushahidi platform], one that we could control and monitor [their actions]. This gave them a false sense of control, we could restore anything they deleted.” That said, one activist recounted how “there were attempts by the government to overload our website with many fake reports […] but we were on it and we were able to delete them. This happened a minute or two every three hours or so, attacks, overload, but eventually they gave up.”

When asked why the regime had not shut down the platform given the potential threat that U-Shahid represented, one blogger explained that “many of the activists who began using Ushahidi had many followers on Facebook and Twitter, they also had the attention of the international media, which could create unwanted attention on the regime’s actions.” This same blogger also noted that many of the activists who collaborated on the U-Shahid project were “connected with people in the US Congress, directors of international human rights NGOs, and so on.” Perhaps the Mubarak Regime was concerned that cracking down on the U-Shahid project would backfire.

In any case, the activists “did a lot of scenario building, considered many ‘what if’ situations. The fact that we were so well prepared is why they [the regime] could not touch us. We tried to connect all the data on Facebook and Twitter so that if they closed our Ushahidi map, we would move to a new domain name and let all our followers know. We also had a large database of SMS numbers, which would allow us to text our followers with information on the new website. Finally, we had a fully trained team in Lebanon ready to take over the project if we were completely shut down.”

“We were well prepared,” added another blogger, “we knew they could not arrest all of us on the day of the election, and just in case, we trained a group in Lebanon who could take over all operations if we were stopped.” According to one activist, “using this mapping technology provided a way to collect and recruit a lot of activists, and not just any activists, but more effective ones. This actually created a headache for the regime because a growing number of digital activists became interested in using the Ushahidi platform.” Another interviewee added that the technology acted as a “magnet” for activists. One activist also remarked that “they [the government] don’t understand how we work; we can learn very fast but the government has many rules and processes, they have to write up reports, submit them for approval, and allocate funding to acquire technology. But for us, we don’t need permission. If we want to use Tor, we simply use Tor.”

Another explained that their project’s credibility came from the realization by many that they were simply focused on “getting the facts out without agenda. We were both transparent and moderate, with no political or party affiliation, and we emphasized that our goal was to try and make the election process transparent.” In sum, said another activist, “we let people decide for themselves whether the content mapped on Ushahidi was good or not.” Another activist argued that the use of the Ushahidi platform “created more transparency around the elections, allowing easier access than in any previous election.” More specifically, “in previous elections and before the existence of Ushahidi, many NGOs made reports of election irregularities, but these were rarely shared publicly with policy maker or even with other NGOs. And even after the elections had taken place, it was very difficult to access these repots. But the Ushahidi [platform] is open and online, allowing anyone to access any of the information mapped in near real-time.”

Still it is really challenging to fully assess the potential political impact (if any) the U-Shahid project had–something the activists are very aware of. One can only investigate so much for so long. One activist noted that “next time we use the Ushahidi platform, this year for the presidential elections, we will be sure to track the reports submitted to the judicial courts and compare them with those we collect. We also plan to better advertise our project with lawyers and political candidates so that they can use our reports including videos and photos in court and for trials.”

What I’m particularly pleased about in addition all the learning that has taken place is the fact that the U-Shahid project spawned off a number of *copy cats during the elections and new maps are being launched almost every other month in Egypt now. The project also increased the number of Egyptian who participated in directly monitoring their own elections. Lastly, I’m excited that the Egyptians who spearheaded the U-Shahid project are now training activists in Tunisia and other Arab countries. They have acquired a wealth of practical knowledge and experience in using the platform in authoritarian environments, and now they’re sharing all this hard-won expertise.

There’s a lot more to share from the interviews, and I hope to do so in future posts. I also plan to blog about the findings from my case study of the Sudan.

 

Analyzing U-Shahid’s Election Monitoring Reports from Egypt

I’m excited to be nearing the completion of my dissertation research. As regular iRevolution readers will know, the second part of my dissertation is a qualitative and comparative analysis of the use of the Ushahidi platform in both Egypt and the Sudan. As part of this research, I am carrying out some content analysis of the reports mapped on U-Shahid and SudanVoteMonitor. The purpose of this blog post is to share my preliminary analysis of the 2,700 election monitoring reports published on U-Shahid during Egypt’s Parliamentary Elections in November & December 2010.

All of U-Shahid‘s reports are available in this Excel file. The reports were originally submitted in Arabic, so I’ve had them translated into English for my research. While I’ve spent a few hours combing through these reports, I’m sure that I didn’t pick up on all the interesting ones, so if any iRev readers do go through the data, I’d super grateful if you could let me know about any other interesting tid-bits you uncover.

Before I get to the content analysis, I should note that the Development and Institutionalization Support Center (DISC)—the Egyptian group based in Cairo that launched the U-Shahid project—used both crowdsourcing and “blogger-sourcing.” That is, the group trained some 130 bloggers and activists in five key cities around Egypt to monitor the elections and report their observations in real-time on the live map they set up. For the crowdsourced reports, DISC worked with a seasoned journalist from Thomson-Reuters to set up verification guidelines that allowed them to validate the vast majority of such reports.

My content analysis of the reports focused primarily on those that seemed to shed the most transparency on the elections and electoral campaigns. To this end, the analysis sought to pick up any trends or recurring patterns in the U-Shahid reports. The topics most frequently addressed in the reports included bribes for buying off votes, police closing off roads leading to polling centers, the destruction and falsification of election ballets, evidence of violence in specific locations, the closing of polling centers before the official time and blocking local election observers from entering polling centers.

What is perhaps most striking about the reports, however, are how specific they are and not only in terms of location, e.g., polling center. For example, reports that document the buying of votes often include the amount paid for the vote. This figure varied from 20 Egyptian Pounds (about $3) to 300 Egyptian Pounds (around $50). As to be expected, perhaps, the price increased through the election period, with one report citing that the bribe price at one location had gone from 40 Pounds to 100 over night.

Another report submitted on December 5, 2010 was even more specific: “Buying out votes in Al Manshiaya Province as following: 7:30[am] price of voter was 100 pound […]. At 12[pm] the price of voter was 250 pound, at 3 pm the price was 200 pound, at 5 pm the price was 300 pound for half an hour, and at 6 pm the price was 30 pound.” Another report revealed “bribe-fixing” by noting that votes ranged from 100-150 Pounds as a result of a “coalition between delegates to reduce the price in Ghirbal, Alexandria.” Other reports documented non-financial bribes, including mobile phones, food, gas and even “sex stimulators”, “Viagra” and “Tramadol tablets”.

Additional incidents mapped on the Ushahidi platform included reports of deliberate power cuts to prevent people from voting. As a result, one voter complained in “Al Saaida Zaniab election center: we could not find my name in voters lists, despite I voted in the same committee. Nobody helped to find my name on list because the electricity cut out.” In general, voters also complained about the lack of phosphoric ink for voting and the fact that they were not asked for their IDs to vote.

Reports also documented harassment and violence by thugs, often against Muslim Brotherhood candidates, the use of Quran verses in election speeches and the use of mini buses at polling centers to bus in people from the National Party. For example, one reported noted that “Oil Minister Samir Fahmy who is National nominee for Al Nassr City for Peoples Council uses his power to mobilize employees to vote for him. The employees used the companies buses carrying the nominee’ pictures to go to the election centers.” Several hundred reports included pictures and videos, some clearly documenting obvious election fraud. In contrast, however, there were also several reports that documented calm, “everything is ok” around certain voting centers.

In a future blog post, I’ll share the main findings from my interviews with the key Egyptian activists who were behind the U-Shahid project. In the meantime, if you choose to look through the election monitoring reports, please do let me know if you find anything else of interest, thank you!