By Chris Orwa (@blackorwa)
Last week, the iHub Research team visited Mathare to interview residents to better understand any disjoint between offline and online worlds in respect to incident reporting during the 4th March elections. From our initial interviews, it is apparent that much more happened than was reported on social media (twitter) and mainstream media (newspapers). Insights from interviews helped us to better understand a phenomenon of online self-censorship. An assumption we held going into the field was that most residents in poorer communities like Mathare do not report incidents through social media because of lack of smartphones, awareness about such platforms, and/or disposable income to buy credit/data. On the contrary, one of the respondents we talked to knew at least five people who were on twitter; another interviewee had an active twitter account and blogged regularly. So, why minimal incident reports from these poorer areas?
It seems, based on deductions and admissions from our interviews, that online, no one wants to be associated with Mathare and those who do post material about Mathare should not post negative things about Mathare or they are castigated (usually offline) for putting up “negative” information about their communities online. This seems to suggest a type of self-censoring online community where everyone knows everyone (since it is a small network of Mathare residents who are online) that, if necessary, will clamp down on those who release negative information about their area. In comparison, in the middle-class estates, the story is completely different.
From our preliminary analysis, the highest number of election-related reporting and online discussions came from middle-class to upper-class estates (Langata, Westlands, Karen, Buruburu, Komarock etc), an indication that the online sharing and reporting (even of negative things) might be a culture of the well-to-do urbanite, a culture of the middle class. In Mathare, despite most respondents admitting to hearing gunshots during the electioneering period, our analysis of the 2.5 million Tweets collected during the election period have not picked up any such reports, other than a gunshot in Kitengela area. It brings to light what is considered “normal” in different areas of Nairobi; while in Kitengela, a gunshot is an incident worth reporting, in Mathare it is a normal happening, not worthy of a report.
As our research field team heads to other hotspot locations in the country, we hope these tales will enable us to create a robust crowdsourcing framework to encapsulate all the dynamics in Kenyan society.