Tag Archives: Protests

Global Heat Map of Protests in 2013

My colleague Kalev Leetaru recently launched GDELT (Global Data on Events, Location and Tone), which includes over 250 million events ranging from riots and protests to diplomatic exchanges and peace appeals. The data is based on dozens of news sources such as AFP, AP, BBC, UPI, Washington Post, New York Times and all national & international news from Google News. Given the recent wave of protests in Cairo and Istanbul, a collaborator of Kalev’s, John Beieler, just produced this digital dynamic map of protests events thus far in 2013. John left out the US because “it was a shining beacon of protest activity that distracted from the other parts of the map.” Click on the maps below to enlarge & zoom in.

World

Heat Map Protests

Egypt

Egypt Protests

India

GDELT India

As Kalev notes, “Right now its just a [temporally] static map, it was done as a pilot just to see what it would look like in the first place, but the ultimate goal would be to do realtime updates, we just need to find someone with the interest and time to do this.” Any readers want to take up the challenge? Having a live map of protests (including US data) with “slow motion replay” functionality could be quite insightful given current upheavals. In the meantime, other stunning visualizations of the GDELT data are available here.

And to think that the quantitative analysis section of my doctoral dissertation was an econometric analysis of protest data coded at the country-year level based on just one news source, Reuters. I wonder if/how my findings would change with GDELT’s data. Anyone looking for a dissertation topic?

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Crisis Mapping the End of Sudan’s Dictatorship?

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.

Detecting Emerging Conflicts with Web Mining and Crisis Mapping

My colleague Christopher Ahlberg, CEO of Recorded Future, recently got in touch to share some exciting news. We had discussed our shared interests a while back at Harvard University. It was clear then that his ideas and existing technologies were very closely aligned to those we were pursuing with Ushahidi’s Swift River platform. I’m thrilled that he has been able to accomplish a lot since we last spoke. His exciting update is captured in this excellent co-authored study entitled “Detecting Emergent Conflicts Through Web Mining and Visualization” which is available here as a PDF.

The study combines almost all of my core interests: crisis mapping, conflict early warning, conflict analysis, digital activism, pattern recognition, natural language processing, machine learning, data visualization, etc. The study describes a semi-automatic system which automatically collects information from pre-specified sources and then applies linguistic analysis to user-specified extract events and entities, i.e., structured data for quantitative analysis.

Natural Language Processing (NLP) and event-data extraction applied to crisis monitoring and analysis is of course nothing new. Back in 2004-2005, I worked for a company that was at the cutting edge of this field vis-a-vis conflict early warning. (The company subsequently joined the Integrated Conflict Early Warning System (ICEWS) consortium supported by DARPA). Just a year later, Larry Brilliant told TED 2006 how the Global Public Health Information Net-work (GPHIN) had leveraged NLP and machine learning to detect an outbreak of SARS 3 months before the WHO. I blogged about this, Global Incident Map, European Media Monitor (EMM), HavariaHealthMap and Crimson Hexagon back in 2008. Most recently, my colleague Kalev Leetaru showed how applying NLP to historical data could have predicted the Arab Spring. Each of these initiatives represents an important effort in leveraging NLP and machine learning for early detection of events of interest.

The RecordedFuture system works as follows. A user first selects a set of data sources (websites, RSS feeds, etc) and determines the rate at which to update the data. Next, the user chooses one or several existing “extractors” to find specific entities and events (or constructs a new type). Finally, a taxonomy is selected to specify exactly how the data is to be grouped. The data is then automatically harvested and passed through a linguistics analyzer which extracts useful information such as event types, names, dates, and places. Finally, the reports are clustered and visualized on a crisis map, in this case using an Ushahidi platform. This allows for all kinds of other datasets to be imported, compared and analyzed, such as high resolution satellite imagery and crowdsourced data.

A key feature of the RecordedFuture system is that extracts and estimates the time for the event described rather than the publication time of the newspaper article parsed, for example. As such, the harvested data can include both historic and future events.

In sum, the RecordedFuture system is composed of the following five features as described in the study:

1. Harvesting: a process in which text documents are retrieved from various sources and stored in the database. The documents are stored for long-term if permitted by terms of use and IPR legislation, otherwise they are only stored temporarily for the needed analysis.

2. Linguistic analysis: the process in which the retrieved texts are analyzed in order to extract entities, events, time and location, etc. In contrast to other components, the linguistic analysis is language dependent.

3. Refinement: additional information can be obtained in this process by synonym detection, ontology analysis, and sentiment analysis.

4. Data analysis: application of statistical and AI-based models such as Hidden Markov Models (HMMs) and Artificial Neural Networks (ANNs) to generate predictions about the future and detect anomalies in the data.

5. User experience: a web interface for ordinary users to interact with, and an API for interfacing to other systems.

The authors ran a pilot that “manually” integrated the RecordedFuture system with the Ushahidi platform. The result is depicted in the figure below. In the future, the authors plan to automate the creation of reports on the Ushahidi platform via the RecordedFuture system. Intriguingly, the authors chose to focus on protest events to demo their Ushahidi-coupled system. Why is this intriguing? Because my dissertation analyzed whether access to new information and communication technologies (ICTs) are statistically significant predictors of protest events in repressive states. Moreover, the protest data I used in my econometric analysis came from an automated NLP algorithm that parsed Reuters Newswires.

Using RecordedFuture, the authors extracted some 6,000 protest event-data for Quarter 1 of 2011. These events were identified and harvested using a “trained protest extractor” constructed using the system’s event extractor frame-work. Note that many of the 6,000 events are duplicates because they are the same events but reported by different forces. Not surprisingly, Christopher and team plan to develop a duplicate detection algorithm that will also double as a triangulation & veracity scoring feature. I would be particularly interested to see them do this kind of triangulation and validation of crowdsourced data on the fly.

Below are the protest events picked up by RecordedFuture for both Tunisia and Egypt. From these two figures, it is possible to see how the Tunisian protests preceded those in Egypt.

The authors argue that if the platform had been set up earlier this year, a user would have seen the sudden rise in the number of protests in Egypt. However, the authors acknowledge that their data is a function of media interest and attention—the same issue I had with my dissertation. One way to overcome this challenge might be by complementing the harvested reports with crowdsourced data from social media and Crowdmap.

In the future, the authors plan to have the system auto-detect major changes in trends and to add support for the analysis of media in languages beyond English. They also plan to test the reliability and accuracy of their conflict early warning algorithm by comparing their forecasts of historical data with existing conflict data sets. I have several ideas of my own about next steps and look forward to speaking with Christopher’s team about ways to collaborate.

Crisis Mapping Sudan: Protest Map of Khartoum

Unlike the many maps of the #Jan25 protests in neighboring Egypt there is but this one map for the #Jan30 protests taking place in the Sudan and Khartoum in particular. The map was requested by Sudanese colleagues in Khartoum who in their own words wanted a public map for the world to see what is happening in their own country.

Some 70 individual reports have been mapped thus far. These capture a range of incidents including the following:

  • Police use gas bombs against medical students [View Report]
  • Peaceful gatherings and demonstrations [View1 View2]
  • Sudanese security harassing foreign journalists [View1 View2]
  • Picture of police beating protesters on Palace Street [View]
  • Videos of protest in Khartoum [View]

While all eyes of the media are on Egypt, few are sharing the developments in the Sudan. This makes the Sudan map even more important. As Philip Howard has found in his comprehensive new study on “The Digital Origins of Dictatorship and Democracy: Information Technology and Political Islam,” the presence of a comparatively active online civil society appears to be one of the key ingredients for democratic transition. Compared to the online civil society in Egypt, the one in the Sudan is far smaller. But activists in Khartoum have reached out to digital activists outside the country for support. And this joint effort has  resulted in more than just a map.

Sudanese contacts have been sharing relevant information via email  and Skype throughout the day, some of which is mapped, and some which is included in the News section of the map. In addition, digital activists have provided training on Twitter and have set up a Flickr account for the Sudanese activists (at their request). See this DigiActive guide on how to use Twitter for activism, also available in Arabic (PDF).

The group has also been trying hard to set up a local FrontlineSMS number for activists to text their reports directly to the map. The first phone they tried didn’t work, so they’re looking to use a GSM modem in the coming days. (Update: an international number has been set up). Once a number is set up, the activists want to share it widely, including the 16,000+ members of the Jan30 Facebook group. Local activists hope this will help them overcome some of the coordination challenges that cropped up today when there was confusion over where and when the demonstrations were meant to take place. This resulted in smaller dispersed protests instead of mass action. You can read more on first hand accounts of this in the News section which includes an email written by Sudanese activist about what they saw today.

Despite the constraints in organization, activists still took to the streets but did face higher risks by being in smaller more dispersed groups. I’m hoping they’ll be able to regroup and plan their future protests in such a way that there is less confusion. The activists do have a full copy of the mass action strategy guide used by Egyptian protesters this week. This may serve them well if they can circulate it widely in the country.

Crisis Mapping Egypt: Collection of Protest Maps (Updated)

The CrisisMappers Twitter feed has shared a number of maps depicting the ongoing protests in Egypt. Here is a collection of them. Do let me know if we’re missing any. To learn more about crisis mapping, read this blog post: What is Crisis Mapping? and join www.CrisisMappers.net. For a protest map of the demonstrations in Khartoum, Sudan, see this link.

Update: The Cairo-based Development and Institutionalization Support Center (DISC) has launched the Ushahidi map below. DISC has previously used the platform to monitor the country’s Parliamentary Elections last November and December  (see this post for more info).

Update: These Twitter maps Hypercities provide another way to visualize the event unfolding across the country.

Update: Storyful has this Google Map of the protests in downtown Cairo:

Update: OpenEgypt, an independent group of volunteers have set up the Open Egypt Crowdmap below:

The Arabic Network for Human Rights Information (ANHRI) has put up this Jan 25th CrowdMap:

The company ESRI has produced the following Web Map of Egypt:

The New York Times has also put this protest map together:

Finally, the LA Times has this map up on their website:

Maptivism: Live Tactical Mapping for Protest Swarming

My colleague Adeel Khamisa from GeoTime kindly shared this news story on how student protesters created a live tactical map to outwit police in London during yesterday’s demonstrations.

Check out these real time updates:

The students also caught the following picture:

The map depicts the tactics employed by the students:

The limits of using Google Maps

As I looked closer at the map, it occurred to me how much this resembles a computer game with moving characters. The strategy employed by the police can be discerned by the pattern below.

But I doubt that students were able to update their Google map in real-time directly from their mobile phones, let alone via SMS, Twitter, Smartphone App, camera phone or Facebook. Nor can they subscribe to alerts and receive them directly via an automated email or SMS. Indeed, it appears they were using Google Forms to “crowdsource” information and this Twitter account to disseminate important updates.

This is why I got in touch with the group and recommended that they think of using Crowdmap (free and open source):

Or GroundCrew (partially free, not open source):

See the following links for more info on Maptivism:

An Analytical Framework to Understand Twitter’s use in Iran?

The digital activism and resistance witnessed in Iran go to the heart of my dissertation research, which asks whether the information revolution empowers coercive regimes at the expense of resistance movements or vice versa? Iran is one of my case studies for my upcoming field research in addition to Burma, Tunisia and Ukraine.

Introduction

There have been a number of excellent blog posts on the intersection between technology and resistance in Iran, and especially on the use of Twitter. The mainstream press is also awash with references to Twitter’s role. For example, Agence France Presse (AFP) recently cited my research in this piece entitled “Twitter Streams Break Iran News Dam.”

However, what I haven’t seen in the blogosphere and mainstream press is the application of an analytical and theoretical framework to place Twitter’s use in Iran into context.

For example, just how important is/was Twitter’s role vis-a-vis the mobilization and organization of anti-government protests in Iran? We can draw on anecdotes here and there but this process is devoid of any applied social science methodology.

This post seeks to shed light on how, when and why information and communication technologies (ICTs) are used by resistance movements in repressive environments. The framework I draw on (summarized below) is informed by Kelly Garrett’s excellent publication on “Protest in an Information Society: A Review of the Literature on Social Movements and New ICTs” (2006).

Framework

The framework seeks to “explain the emergence, development and outcomes of social movements by addressing three interrelated factors: mobilizing structures, opportunity structures and framing processes”  within the context of ICTs. (The figure below is excerpted from my dissertation, hence the figure 4 reference).

PhDFramework

  • Mobilizing Structures are the mechanisms that facilitate organization and collective action. These include social structures and tactical repertoires.
  • Opportunity Structures are conditions that favor social movement activity. For example, these include factors such as the state’s capacity and propensity for repression.
  • Framing Processes are “strategic attempts to craft, disseminate, and contest the language and narratives used to describe a movement.”

These three factors should be further disaggregated to facilitate analysis. For example, mobilizing structures can be divided into categories susceptible to the impact of ICTs:

  • Participation levels (recruitment);
  • Contentious activity;
  • Organizational issues.

These sub-indicators are still to broad, however. Take, for example, participation levels; what is participation a function of? What underlying mechanisms are facilitated or constrained by the wider availability and use of ICTs? Participation levels may change as a function of three factors:

  • Reduction of participation costs;
  • Promotion of collective identity;
  • Creation of community.

These activities are of course not mutually exclusive but often interdependent. In any case, taking the analysis of ICTs in repressive environments to the tactical level facilitates the social science methodology of process tracing.

Application

We can apply the above framework to test a number of hypotheses regarding Twitter’s use in Iran. Take Mobilizing Structures, for example. The following hypothesis could be formulated.

  • Hypothesis 1: The availability of Twitter in Iran increased participation levels, contentious activity and organizational activity.

Using process tracing and the above framework, one could test hypothesis 1 as follows:

hypo1

These causal chains, or “micro theories,” are posited with the “⎥” marker to signify that the causal relationship is contended. The direction of the arrows above reflects the theoretical narratives extracted from the theoretical framework presented above. Note that the above “micro” theories are general and not necessarily reflective of Twitter’s use in Iran.

Iran Case Study

When the arrows are tallied, the results suggest the following general theory: there is a direct and positive relationship between the impact of Twitter and the incidents of protests and riots. The next step is to test these “micro theories” in the context of Iran by actually “weighting” the arrows. And of course, to do so comparatively by testing the use of Twitter relative to the use of mobile phones and the Internet. Furthermore, the results of this hypothesis testing should be compared to those for Opportunity Structures and Framing Processes.

I plan to carry out field research to qualitatively test these hypotheses once the first phase of my dissertation is completed. The first phase is a large-N quantitative study to determine whether increasing access to ICTs in repressive regimes is a statistically significant predictor of anti-government protests.

Patrick Philippe Meier