Learning from Kenya: using SMSs for a rapid response mechanism in Central African Republic

One of the biggest problem right now in Central African Republic is the perception in the two different communities, Christian and Muslims, that the two fighting movements, the Seleka and the Anti-Balaka, are the same thing than the communities themselves. This means that when the Seleka attack or kill people, the Christian community attack the Muslim communities living in their areas as a rapresail, and so it happens when the Anti-Balaka attack Muslims communities.

One month ago I had the pleasure to spend two full days with Rachel Brown, the person behind the creation of a peace building organization called SiSi Ni Amani (SNAK) in Kenya. Internews Global Initiative program asked Rachel to share with us her impressive knowledge and her lessons learned from her 3 years project in Kenya.

One of the most impressive and important part of her project for us was the way Rachel understood and used information dynamics to study the decision making processes that lead to violence in the context of the Kenyan society.

In this regard Rachel has done an incredible work based on the fact that violence behaviour is almost entirely based on information ecosystems dynamics, and how the way information is delivered, used, manipulated and spread has an impressive trickled down effect that affects entirely the outcome of a violent action or not.

During my stay in CAR I am having an additional confirmation of this kind of dynamic and I truly believe that the more we are able to adapt Rachel methodology to this context the more we can actually start designing some interesting way to mitigate violence in between the two communities.

Rachel created and carried out two very interested methodologies to understand violence and its development. She first was able to understand and realize that the violent behavior is not the result an immediate and sudden decision but it is the result of a process where information flows in a community and depending on the point in time, format, and the content itself, the informations triggers decision making processes that then results in specific action and behaviors. This dynamic is therefore not immediate but consequential, and therefore an escalating process that can be eventually predicted or guessed if the steps and the triggers are indentified in advance. Rachel called this the Football Match model.

The football match process basically looks at the ball as information. The ball is first kicked by player one in the field, and it is then taken by player two – player two can be of the same team or the opposite one. Once the ball in on player two he will also kick it and the all match continue until there is a score. If we look at this as an information system what happened is that information travelled Ina community from one person to  another and in the process people use that information to make decisons. This decisions and behaviors than trigger other players actions and behaviors. When it comes to violence this is normally translated into the escalation process.

If we look at the CAR dynamics of violence right now this is exactly what it is happening: Seleka fighters attack Christian civilians, and this triggers Anti-Balaka to attack Muslim civilians. This also triggers Christian civilians to attacks Muslim civilians and Muslim civilians to attacks Christian civilians. This all dynamic altogether also triggers civilians of both religions to flee from the areas wp they live in to escape violence, resulting in IDPS camps that become also source of tensions and targets for more violence to happen.

DO_NOT_USE_MARCUSC_2826353b                                              (photo from www.telegraph.co.uk)

Using the football match model Rachel did an analisys of the micro-local behavior that would lead to the final decision of actually engaging in a violent act. She did this by using a second analytical tool, whihc she called the Trigger analisys. The trigger analisys basically looked at whihc type of information, in which point in time would trigger a specific decision to be taken. Since the foot match model allowed her to identify the steps through which the information flows in the community, the trigger analisys was able to give her insights about which specific stage of the process was the one that would make people chose to spread an information or use it as a decision making base.

The third analitical tool Rachel used was what she called the hotspot analisys. The hot spot analisys basically used the insights from the two previous tools to indentify recognizable external evidence that a violent action was about to take place. This kind of analysis was only possible to be done because Rachel worked with members of the communities that had a deep knowledge of their own communities behaviors. It was also possible because Rachel staff had experienced already a violet outbreak, during the elections in 2007/2008 and those events provided very good insights on the development of violence in different communities in the country.

With the use if those three analitical tools SiSi Ni Amani was able to design very specific mitigation programs to use the already existing dynamic in their favor. How did that work?

Basically SiSi Ni Amani had local “monitors”, all members of the communities, that would simply observe their own community over time to identify when a behavior was associated with a hotspot. Once that behavior was indentified, the SiSi Ni Amani staff would use mobile phones to provide information that could potentially change the decision making process to avoid the decision to engage in violence.

Let’s see an example. One one the behavior that was identified by SNAK as an evidence of a possible decision to engage in violence was the fact that young people in certain areas were suddenly gathering in the street and talking in an animated way. This would normally follow the circulation of a rumor or information in the community about a recent violent event against the local community. Once the information was reported to SNAK the team would used already existing pe designed messages and send them as SMS to the local community youth.

Those messages had been designed by other youth in that same community in order to appeal to their peers. Basically the idea behind the design of those messages was that different people in the same community may be subscetible to different appeals. An example would be that young people are very susceptible to the idea of belonging to a group, and therefore if an action is seen as required to belong a certain group, they would most likely engage in the activity. A message that would break that dynamic would be to show them that the may be different other groups they could chose from, and that a certain action may not be the only choice to belong to a certain group.

The SiSi Ni Amani model proved to be effective – in the preliminary results of their extensive survey after the use of this system for the previous Kenyan elections, it looks like more than 45% of the people changed their mind after receiving a message from SiSi ni Amani. It also looks like that more than 60% of people forwarded the message or talk to other people about the issue.

What I am very interested about right now is on how we could potentially adapt this system to Central African Republic. We know that this trickling down dynamic is happening, and we know that rumors as well as information about attacks are at the base of people engaging in violent behaviors. Could we actually replicate this system in CAR to design a rapid response mechanism to prevent outbreaks of violence, at least the one committed by members of the communities against each others? (of course for this to happen the government would have to allow SMS again in the country).

Gallery | This entry was posted in Humanitarian Affairs, ICT4D, Mobile. Bookmark the permalink.

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