Tag Archives: conflict

Micro-dynamics of Reciprocity in an Asymmetric Conflict (Updated)

Thomas Zeitzoff is a PhD candidate at New York University. I came across his research thanks to the Ushahidi network, and am really glad I did. He wrote a really neat paper earlier this year on “The Micro-dynamics of Reciprocity in an Asymmetric Conflict: Hamas, Israel, and the 2008-2009 Gaza Conflict,” which he is revising and submitting to peer-review.

Updated: Thomas kindly sent me the most recent version of his paper which you can download here (PDF).

I’ve done some work on conflict event-data and reciprocity analysis (see this study of Afghanistan), but Thomas is really breaking new ground here with the hourly temporal resolution of the conflict analysis, which was made possible by Al-Jazeera’s War on Gaza project powered by Ushahidi.

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Abstract

The Gaza Conflict (2008-2009) between Hamas and Israel was de fined the participants’ strategic use of force. Critics of Israel point to the large number of Palestinian casualties compared to Israelis killed as evidence of a disproportionate Israeli response. I investigate Israeli and Hamas response patterns by constructing a unique data set of hourly conflict intensity scores from new social media and news source over the nearly 600 hours of the conflict. Using vector autoregression techniques (VAR), I fi nd that Israel responds about twice as intensely to a Hamas escalation as Hamas responds to an Israeli escalation. Furthermore, I find that both Hamas’ and Israel’s response patterns change once the ground invasion begins and after the UN Security Council votes.

As Thomas notes, “Ushahidi worked with Al-Jazeera to track events on the ground in Gaza via SMS messages, email, or the web. Events were then sent in by reporters and civilians through the platform and put into a Twitter feed entitled AJGaza, which gave the event a time stamp. By cross-checking with other sources such as Reuters, the UN, and the Israeli newspaper Haaretz, I was able see that the time stamp was usually within a few minutes of event occurrence.”

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Key Highlights from the study:

  • Hamas’ cumulative response intensity to an Israeli escalation decreases (by about 17 percent) after the ground invasion begins. Conversely, Israel’s cumulative response intensity after the invasion increases by about three fold.
  • Both Hamas and Israel’s cumulative response drop after the UN Security Council vote on January 8th, 2009 for an immediate cease-fi re, but Israel’s drops more than Hamas (about 30 percent to 20 percent decrease).
  • For the period covering the whole conflict, Hamas would react (on average) to a “surprise” 1 event (15 minute interval) of Israeli misinformation/psy-ops with the equivalent of 1 extra incident of mortar re/endangering civilians.
  • Before the invasion, Hamas would respond to a 1 hour shock of targeted air strikes with 3 incidents of endangering civilians. Comparatively, after the invasion, Hamas would only respond to that same Israeli shock with 3 incidents of psychological warfare.
  • The results con rm my hypotheses that Israel’s reactions were more dependent upon Hamas and that these responses were contextually dependent.
  • Wikipedia’s Timeline of the 2008-2009 Gaza Conflict was particularly helpful in sourcing and targeting events that might have diverging reports (i.e. controversial).

Perhaps the main question I would have for Thomas is how he thinks his analysis and findings could be used for conflict early warning and rapid response to violent conflict.

Patrick Philippe Meier

Applying Earthquake Physics to Conflict Analysis

I’ve long found the analogies between earthquakes and conflicts intriguing. We often talk of geopolitical fault lines, mounting tensions and social stress. “If this sounds at all like the processes at work in the Earth’s crust, where stresses build up slowly to be released in sudden earthquakes … it may be no coincidence” (Buchanan 2001).

To be sure, violent conflict is “often like an earthquake: it’s caused by the slow accumulation of deep and largely unseen pressures beneath the surface of our day-to-day affairs. At some point these pressures release their accumulated energy with catastrophic effect, creating shock waves that pulverize our habitual and often rigid ways of doing things…” (Homer-Dixon 2006).

But are fore shocks and aftershocks in social systems really as discernible as well? Like earthquakes, both inter-state and internal wars actually occur with the same statistical pattern (see my previous blog post on this). Since earthquakes and conflicts are complex systems, they also exhibit emergent features associated with critical states. In sum, “the science of earthquakes […] can help us understand sharp and sudden changes in types of complex systems that aren’t geological–including societies…” (Homer-Dixon 2006).

The Model

To this end, I collaborated with Professor Didier Sornette and Dr. Ryan Woodard from the Swiss Federal Institute of Technology (ETHZ) to assess whether a mathematical technique developed for earthquake prediction might shed light on conflict dynamics. I presented this study along with our findings at the American Political Science Association (APSA) convention last year (PDF).

This geophysics technique, “superposed epoch analysis,” is used to identify statistical signatures before and after earthquakes. In other words, this technique allows us to discern whether any patterns are discernible in the data during foreshocks and aftershocks.

Earthquake physicists work from global spatial time series data of seismic events to develop models for earthquake prediction. We used a global time series dataset of conflict events generated from newswires over a 15-year period. The graph below explains the “superposed epoch analysis” technique as applied to conflict data.

eqphysics

The curve above represents a time series of conflict events (frequency) over a particular period of time. We select arbitrary threshold, such as “threshold A” denoted by the dotted line. Every peak that crosses this threshold is then “copied” and “pasted” into a new graph. That is, the peak, together with the data points 25 days prior to and following the peak is selected.

The peaks in the new graph are then superimposed and aligned such that the peaks overlap precisely. With “threshold A”, two events cross the threshold, five for “threshold B”. We then vary the thresholds to look for consistent behavior and examine the statistical behavior of the 25 days before and after the “extreme” conflict event.

Results

For this study, we performed the computational technique described above on the conflict data for the US, UK, Afghanistan, Columbia and Iraq.

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The foreshock and aftershock behaviors in Iraq and Afghanistan appear to be similar. Is this because the conflicts in both countries were the result of external intervention, i.e., invasion by US forces (exogenous shock)?

In the case of Colombia, an internal low intensity and protracted conflict, the statistical behavior of foreshocks and aftershocks are visibly different from those of Iraq and Afghanistan. Do the different statistical behaviors point to specific signature associated with exogenous and endogenous causes of extreme events? Does one set of behavior contrast with another one in the same way that old wars and new wars differ?

Future Research

Are certain extreme events endogenous or exogenous in nature? Can endogenous or exogenous signatures be identified? In other words, are extreme events just part of the fat tail of a power law due to self-organized criticality (endogeneity)? Or is catastrophism in action, extreme events require extreme causes outside the system (exogeneity)?

Another possibility still is that extreme events are the product of both endogenous and exogenous effects. How would this dynamic unfold? To answer these questions, we need to go beyond political science.

The distinction between responses to endogenous and exogenous processes is a fundamental property of physics and is quantified as the fluctuation-dissipation theorem in statistical mechanics. This theory has been successfully applied to social systems (such as books sales) as a way to help understand different classes of causes and effects.

Our goal is to use the same techniques to investigate the questions: Do conflict among actors in social systems display measurable endogenous and exogenous behavior?  If so, can a quantitative signature of precursory (endogenous) behavior be used to help recognize and then reduce growing conflict? The next phase of this research will be to apply the above techniques to the conflict dataset already used to examine the statistical behavior of foreshocks and aftershocks.

The Mathematics of War: Before the TED Talk

My new colleague Sean Gourely recently presented his research on “The Mathematics of War” at the TED 2009 conference. I met Sean in March this year, a month after TED, and soon realized we had been doing very similar research on the mathematics of war. Indeed, I carried out related research with Dr. Ryan Woodard while at the Santa Fe Institute (SFI) exactly three years ago, in June 2006.

However, the discovery that conflict follows a power law distribution was actually made by another physicist, Lewis Fry Richardson, some 60 years ago. A power law distribution relates the frequency and “magnitude” of events. For example, the Richter scale, relates the size of earthquakes to their frequency. Richardson found that the frequency of international wars and the number of casualities each produced followed a power law.

Before TED

More recently, my colleague Erik-Lars Cederman sought to explain Richardson’s findings in his 2003 peer-reviewed publication “Modeling the Size of Wars: From Billiard Balls to Sandpiles.” However, Lars used an invalid statistical technique to test for power law distributions.

In 2005, I began collaborating with Professors Neil Johnson and Michael Spagat on related research after I came across their fascinating co-authored study that tested casualty distributions in new wars (internal conflicts) for power laws. Turns out Sean also collaborated with Neil and Michael on the research he presented at TED, but he was not a co-author on the 2005 study, which explains why we only met 4 years later.

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

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

Disaster Casualties

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

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

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Conflict Casualties

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

The abstract and some findings are included below:

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

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Next Steps

Sean and I are hoping to collaborate in future research as there is still a lot of interesting work to be done in this area. In the meantime, however, we’re collaborating on Ushahidi’s Swift River, for which I recently developed a very basic pseudo code to score the veracity of incident reports.

Meeting Sean has reminded me just how interested and involved I was in the above research 3-4 years ago. While I haven’t pursued the power law research since, I did continue working with Dr. Woodard and produced another study last year on the application of geophsyics analysis to conflict data to identify for shocks and aftershocks in major conflicts. This will be the subject of my next blog post.

Mirror, Mirror on the Wall…

Which conflict forecasting model is the most accurate of them all? None are accurate to begin with. Has no one read Nassim Taleb’s “The Black Swan“?

Taleb

Recent empirical studies demonstrate that experts, i.e., us (and our sophisticated systems and methodologies) are only marginally better than novices in our ability to accurately forecast political and economic events. Furthermore, these studies show that neither group’s forecasts are much better than random guessing.

Of greater concern still is the empirical observation that experts nevertheless remain consistently overconfident of the accuracy of their own forecasts. This is compared to novices who tend to be more conservative vis-à-vis their forecasting abilities although they are equally (in)effective when it comes to accuracy. A separate study found that “somehow, the analysts’ self-evaluation did not decrease their error margin after their failures to forecast.”

Perhaps the most telling test of how academic methods fare in the real world was run by Spyros Makridakis, “who spent part of his career managing competitions between forecasters who practice a ‘scientific method’ called econometrics […]. Simply put, he made people forecast in real life and then he judged their accuracy” (1).

This led to the following lamentable conclusion “statistically sophisticated or complex methods do not provide more accurate forecasts than simpler ones” (2). And so, despite the fact that “billions of dollars have been invested in developing sophisticated data banks and early warnings, we have to note that even the most expensive systems have shown a striking inability to forecast political events,” not to mention galvanize any preventive measures (Rupesinghe 1988).

What I really don’t understand, however, is how some experts profess to forecast conflicts and at the same time use the word “discontinuous” to describe trends in conflict. If a process experiences tipping points (or punctuated equilibria) then no econometric model however fancy can provide accurate forecasts. Talk to anyone at the Santa Fe Institute (SFI) if you’re not convinced. Or read this piece by Charles Doran on “Why Forecasts Fail.”

Where to Study Conflict Early Warning?

A number of readers have contacted me via blog comments or by email to ask where they might be able to pursue a post-graduate degree or certificate in conflict early warning. That is indeed a good question. I don’t know of any graduate program (or undergraduate, for that matter) that includes courses specifically on conflict early warning.

I would therefore suggest looking for graduate programs that have a strong focus on conflict analysis and risk assessments. I would also recommend looking for programs with courses on international security, human security, human rights, complex emergencies and causes of conflict. Courses on international institutions, decision making, humanitarian logistics, etc., would also be a plus.

In addition, it is important to venture beyond your own field, say political science, and to learn as much as possible about how other fields such as public health, environmental studies, disaster management, etc., approach the challenge of early warning and rapid response. To be sure, some of the most valuable insights I have gained over the years have been from those fields.

Taken together, these courses will allow you to write research papers that focus on various aspects of conflict early warning that are of interest to you. You’ll want to develop good analytical skills, both qualitative and quantitative, as well as research methodology skills. So find a program that has a strong track record in methodology and research design.

Now, I realize no one program will necessarily have all the above courses. So it’s up to you to find out which courses appeal to you in particular and which professors you’d specifically like to work with. Scholarships, stipends, etc., will also play an important role (if not be the overriding factor). Finally, it’s important to feel good about location and environment.

So that would be my advice on the academic end. But you don’t have to wait until graduate school to get started and remember also that practical experience is important. I would encourage you to read as much of the literature and material available online as possible (for as long as you’re still interested!).

To get you started, here are similar syllabi for seminars I have taught on disaster and conflict early warning/response: syllabus 1 and syllabus 2. Feel free to get in touch if you can’t find any of the readings online and I’ll try to see whether I can share an electronic/scanned copy. I would also recommend reading the posts (and comments) on this blog! If you find any other blog on conflict early warning, please let me know!

Finally on experience, get in touch with practitioners and other scholars in the field. Ask them specific and informed questions on issues or ideas you’re thinking about and ask them for advice on further reading or other individuals to get in touch with. Offer to volunteer on projects of interest to you and ask about the availability of internships or other short-term research assignments.

Use papers you are writing in class as a reason to get in touch with practitioners and scholars. Write papers on projects or issues they are currently working on. This serves two purposes: first, your papers would become directly relevant to the “real world”; and second, you’d be able to share your papers with practitioners who will most likely appreciate and read your work. This is a great way to network and  could open up professional opportunities for the future.

If you still have any specific questions on issues I may not have addressed, please always feel free to get in touch. My contact information can be found in the “Contact” link above. If I don’t answer within a week it’s usually because I’m traveling or under a tight deadline. In any case, please contact me again if you don’t here from the first time around, perseverance is a good skill in any field!

OECD: The Future of Conflict Early Warning and Response

The OECD‘s publication on “Preventing Violence, War and State Collapse: The Future of Conflict Early Warning and Response,” (PDF) has finally been published. I was solicited by the OECD to be the main peer reviewer for the publication, which was authored by my colleague David Nyheim.

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I had a lot to add so the peer review process turned into a consulting assignment back in September 2008. My main contribution to the publication included paragraphs on:

  • Evaluating CEWARN, ECOWARN and CEWS
  • Fourth Generation Early Warning Systems
  • Current Trends in Warning and Response
  • People-Centered Early Warning
  • Forecasting Armed Conflict
  • Advances in Technology

I added references to the Harvard Humanitarian Initiative’s (HHI) Program on Crisis Mapping and Early Warning (CM&EW) as well as to Ushahidi‘s approach to crowdsourcing crisis information.

Patrick Philippe Meier

Sri Lanka: Citizen-based Early Warning and Response

Colleagues at the Foundation for Coexistence (FCE) in Sri Lanka just shared their report on “Citizen-based Early Warning and Response” with me (PDF). I’ve been following the Foundation’s work for the past five years so I was keen to get an update on their work in the field of conflict early warning and rapid response.

What follows is a brief review of the report and the FCE’s conflict early warning and rapid response initiative. I conclude with some of my own thoughts based on my early warning experience with FAST, CEWARN, ECOWARN, WANEP, MARRAC, EC, OSCE, OECD, UNDP, UNEP, OCHA, UNICEF,  WFP, USAID, IFES, BELUN, ICG, JRC, International Alert  and Ushahidi.

Introduction

The Foundation takes a human security approach to early warning, which focuses both on protection and empowerment. They note that in most standard definitions of early warning, e.g., “the systematic collection and analysis of information,” do not actually include giving a warning—a point which certainly resonates with my experience.

Evolving Generations

One of the conceptual innovations that FCE contributed to the field of conflict early warning is the notion of first, second and third generations early warning systems. A first generation system monitors and analyzes conflict from outside the conflict regions; they are typically based in the West. “The problems of the first generation are consistent with those of quantitative approaches; they use limited secondary sources which do not provide any certainty about their accuracy and they have difficulty in predicting eruption of armed conflict accurately.” In other words, they focus exclusively on prediction and “do not have effective procedures to communicate with [Track 1] decision-makers for early response.”

Second generation early warning systems conduct monitoring within conflict countries and regions. “However, analysis is still conducted outside conflict countries (in the West).” Second generations systems entail field-based monitoring, risk assessments and active lobbying. “The advantage of qualitative approaches is that [they offer] vastly more content-rich and contextual information than quantitative statistical analysis.” However, the actors engaged in “second generation” early response are no different from those of the first, they are strictly Track 1 actors.

Third generation early warning systems are created by people in conflict areas for themselves. “It can be referred to as ‘Early Warning and Early Response system of citizens, by citizens and for citizens.'” Unlike first and second generation initiatives, monitoring and analysis is conducted on-site. “The logic behind them is that closeness to the conflict area enables one to understand the situation better and intervene rapidly and appropriately.” According to FCE, third generation systems thus have a stronger link between early warning and rapid response.

Early Warning

The FCE uses an events-data software program called FCEWARN for early warning; the unique feature of which is “that it can be utilized to monitor conflicts at the ‘micro’ level, especially at the village level.” The software basically quantifies conflict and peace indicators to display them as descriptive statistics such as tables and graphs. The FCE combines this software with “Geographic Information Systems (GIS) software that visualizes spatial dimensions of conflict and peace indicators.”

The information fed into the software program is collected by the Foundation’s 37 field monitors operating in teh conflict zone.

“They are organic members of the communities they represent. They collect information on peace and conflict indicators and send it to the information center in Colombo in a specific format on a daily basis. [...] The field monitors collect information through co-existence committees, state and non-state actors, local media and interpersonal relationships

As a result, the information centre in Colombo [...] receives 30 event data forms in the least a day. In total this amounts to 600 event data on average per month.  This density of first hand information allows for adept trend analysis at the early warning stage.”

The FCE draws on the software and data to generate early warning products that “support the early response functions in the conflict zone by teh field monitors [...].” In addition, the Foundations makes use of SMS alerts. The FCEWARN software program has the flexibility to integrate a functionality for SMS alerts.

Rapid Response

The FCE claims that “the development of computer software (FCEWARN) for early warning” is their “key achievement” vis-a-vis their “venture into conflict early warning during the past five years.”

However, I would point to their success in responding to 156 cases of conflict as their key achievement. According to the Foundation, their early warning initiative has “intervened in a recorded number of 156 cases of conflict.” The Foundation nodes that “four independnent evaluations by international experts in the science of conflict resolution have attested that this system has prevented or mitigated or contributed to resove conflicts.”

Of note is that the FCE’s early response system is “based on the application of multi-track diplomacy,” unlike first and second generation systems. The Foundation “emphasizes making citizens a major stakeholder in the process of transforming the conflict.” They also recognize the need to build “sufficient capacity and power of mobilization to solicit substantial amount of stakeholder effort from different vantage points.”

To this end, the field monitors are “the primary coordinating hubs of information and early response interventions in the conflict zones. They collect and analyze information and initiate early response processes to prevent conflicts.” Field monitors should therefore have “substantial influences on the masses and/or stakeholders in the conflict zone.” In sum, the rapid response component has to “assume the role of a ‘near’ mediator.”

Unlike the vast majority of conflict early warning initiatives, the FCE actually “reviews the outcomes of one instance of intervention and builds analysis and prognosis for another phase of intervention. This cycle continues until the conditions to the precipitating event are transformed or diluted to a satisfactory level.”

Conclusion

The FCE continues to make important contributions to the field of conflict early warning by demonstrating what an alternative, third generation approach can accomplish compared to top-down first-generation systems. Perhaps what is missing from the report is a stronger emphasis on preparedness and contingency planning. In other words, it would be beneficial to many of us if we could read more on the pro-active and preventive operational measures taken by FCE field monitors beyond conflict resolution excercises.

I would also suggest the notion of “fourth generation” early warning systems. While third generation systems are supposed to be “of the people, for the people by the people,” I think a direct focus on empowering local communities to manage and prevent conflict themselves (as opposed to “external” field monitors) would constitute a fourth generation system. A partial example is Ushahidi, which allows villagers to report alerts by SMS and to also subscribe directly to SMS alerts of incidents taking place in their vicinity.