Tag Archives: Communication

Quantifying Information Flow During Emergencies

I was particularly pleased to see this study appear in the top-tier journal, Nature. (Thanks to my colleague Sarah Vieweg for flagging). Earlier studies have shown that “human communications are both temporally & spatially localized following the onset of emergencies, indicating that social propagation is a primary means to propagate situational awareness.” In this new study, the authors analyze crisis events using country-wide mobile phone data. To this end, they also analyze the communication patterns of mobile phone users outside the affected area. So the question driving this study is this: how do the communication patterns of non-affected mobile phone users differ from those affected? Why ask this question? Understanding the communication patterns of mobile phone users outside the affected areas sheds light on how situational awareness spreads during disasters.

Nature graphs

The graphs above (click to enlarge) simply depict the change in call volume for three crisis events and one non-emergency event for the two types of mobile phone users. The set of users directly affected by a crisis is labeled G0 while users they contact during the emergency are labeled G1. Note that G1 users are not affected by the crisis. Since the study seeks to assess how G1 users change their communication patterns following a crisis, one logical question is this: do the call volume of G1 users increase like those of G0 users? The graphs above reveal that G1 and G0 users have instantaneous and corresponding spikes for crisis events. This is not the case for the non-emergency event.

“As the activity spikes for G0 users for emergency events are both temporally and spatially localized, the communication of G1 users becomes the most important means of spreading situational awareness.” To quantify the reach of situational awareness, the authors study the communication patterns of G1 users after they receive a call or SMS from the affected set of G0 users. They find 3 types of communication patterns for G1 users, as depicted below (click to enlarge).

Nature graphs 2

Pattern 1: G1 users call back G0 users (orange edges). Pattern 2: G1 users call forward to G2 users (purple edges). Pattern 3: G1 users call other G1 users (green edges). Which of these 3 patterns is most pronounced during a crisis? Pattern 1, call backs, constitute 25% of all G1 communication responses. Pattern 2, call forwards, constitutes 70% of communications. Pattern 3, calls between G1 users only represents 5% of all communications. This means that the spikes in call volumes shown in the above graphs is overwhelmingly driven by Patterns 1 and 2: call backs and call forwards.

The graphs below (click to enlarge) show call volumes by communication patterns 1 and 2. In these graphs, Pattern 1 is the orange line and Pattern 2 the dashed purple line. In all three crisis events, Pattern 1 (call backs) has clear volume spikes. “That is, G1 users prefer to interact back with G0 users rather than contacting with new users (G2), a phenomenon that limits the spreading of information.” In effect, Pattern 1 is a measure of reciprocal communications and indeed social capital, “representing correspondence and coordination calls between social neighbors.” In contrast, Pattern 2 measures the dissemination of the “dissemination of situational awareness, corresponding to information cascades that penetrate the underlying social network.”

Nature graphs 3

The histogram below shows average levels of reciprocal communication for the 4 events under study. These results clearly show a spike in reciprocal behavior for the three crisis events compared to the baseline. The opposite is true for the non-emergency event.Nature graphs 4

In sum, a crisis early warning system based on communication patterns should seek to monitor changes in the following two indicators: (1) Volume of Call Backs; and (2) Deviation of Call Backs from baseline. Given that access to mobile phone data is near-impossible for the vast majority of academics and humanitarian professionals, one question worth exploring is whether similar communication dynamics can be observed on social networks like Twitter and Facebook.

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How People in Emergencies Use Communication to Survive

“Still Left in the Dark? How People in Emergencies Use Communication to Survive — And How Humanitarian Agencies Can Help” is an excellent report pub-lished by the BBC World Service Trust earlier this year. It is a follow up to the BBC’s 2008 study “Left in the Dark: The Unmet Need for Information in Humanitarian Emergencies.” Both reports are absolute must-reads. I highlight the most important points from the 2012 publication below.

Are Humanitarians Being Left in the Dark?

The disruptive impact of new information and communication technologies (ICTs) is hardly a surprise. Back in 2007, researchers studying the use of social media during “forest fires in California concluded that ‘these emergent uses of social media are pre-cursors of broader future changes to the institutional and organizational arrangements of disaster response.’” While the main danger in 2008 was that disaster-affected communities would continue to be left in the dark since humanitarian organizations were not prioritizing information delivery, in 2012, “it may now be the humanitarian agencies themselves […] who risk being left in the dark.” Why? “Growing access to new technologies make it more likely that those affected by disaster will be better placed to access information and communicate their own needs.” Question is: “are humanitarian agencies prepared to respond to, help and engage with those who are communicating with them and who demand better information?” Indeed, “one of the consequences of greater access to, and the spread of, communications technology is that communities now expect—and demand—interaction.”

Monitoring Rumors While Focusing on Interaction and Listening

The BBC Report invites humanitarian organizations to focus on meaningful interaction with disaster-affected communities, rather than simply on message delivery. “Where agencies do address the question of communication with affected communities, this still tends to be seen as a question of relaying infor-mation (often described as ‘messaging’) to an unspecified ‘audience’ through a channel selected as appropriate (usually local radio). It is to be delivered when the agency thinks that it has something to say, rather than in response to demand. In an environment in which […] interaction is increasingly expected, this approach is becoming more and more out of touch with community needs. It also represents a fundamental misunderstanding of the nature and potential of many technological tools particularly Twitter, which work on a real time many-to-many information model rather than a simple broadcast.”

Two-way communication with disaster-affected communities requires two-way listening. Without listening, there can be no meaningful communication. “Listening benefits agencies, as well as those with whom they communicate. Any agency that does not monitor local media—including social media—for misinformation or rumors about their work or about important issues, such as cholera awareness risks, could be caught out by the speed at which information can move.” This is an incredibly important point. Alas, humanitarian organ-izations have not caught up with recent advances in social computing and big data analytics. This is one of the main reasons I joined the Qatar Computing Research Institute (QCRI); i.e., to spearhead the development of next-generation humani-tarian technology solutions.

Combining SMS with Geofencing for Emergency Alerts

Meanwhile, in Haiti, “phone company Digicel responded to the 2010 cholera outbreak by developing methods that would send an SMS to anyone who travelled through an identified cholera hotspot, alerting them to the dangers and advising on basic precautions.” The later is an excellent example of geofencing in action. That said, “while responders tend to see communication as a process either of delivering information (‘messaging’) or extracting it, disaster survivors seem to see the ability to communicate and the process of communication itself as every bit as important as the information delivered.”

Communication & Community-Based Disaster Response Efforts

As the BBC Report notes, “there is also growing evidence that communities in emergencies are adept at leveraging communications technology to organize their own responses.” This is indeed true as these recent examples demonstrate:

“Communications technology is empowering first responders in new and extremely potent ways that are, at present, little understood by international humanitarians. While aid agencies hesitate, local communities are using commu-nications technology to reshape the way they prepare for and respond to emergencies.” There is a definite payoff to those agencies that employ an “integrated approach to communicating and engaging with disaster affected communities […]” since they are “viewed more positively by beneficiaries than those that [do] not.” Indeed, “when disaster survivors are able to communicate with aid agencies their perceptions become more positive.”

Using New Technologies to Manage Local Feedback Mechanisms

So why don’t more agencies follow suite? Many are concerned that establishing feedback systems will prove impossible to manage let alone sustain. They fear that “they would not be able to answer questions asked, that they [would] not have the skills or capacity to manage the anticipated volume of inputs and that they [would be] unequipped to deal with people who would (it is assumed) be both angry and critical.”

I wonder whether these aid agencies realize that many private sector companies have feedback systems that engage millions of customers everyday; that these companies are using social media and big data analytics to make this happen. Some are even crowdsourcing their customer service support. It is high time that the humanitarian community realize that the challenges they face aren’t that unique and that solutions have already been developed in other sectors.

There are only a handful of examples of positive deviance vis-a-vis the setting up of feedback systems in the humanitarian space. Oxfam found that simply com-bining the “automatic management of SMS systems” with “just one dedicated local staff member […] was enough to cope with demand.” When the Danish Refugee Council set up their own SMS complaints mechanism, they too expected be overwhelmed with criticisms. “To their surprise, more than half of the SMS’s they received via their feedback system […] have been positive, with people thanking the agency for their assistance […].” This appears to be a pattern since “many other agencies reported receiving fewer ‘difficult’ questions than anticipated.”

Naturally, “a systematic and resourced approach for feedback” is needed either way. Interestingly, “many aid agencies are in fact now running de facto feedback and information line systems without realizing it. […] most staff who work directly with disaster survivors will be asked for contact details by those they interact with, and will give their own personal mobile numbers.” These ad hoc “systems” are hardly efficient, well-resourced or systematic, however.

User-Generated Content, Representativeness and Ecosystems

Obviously, user-generated content shared via social media may not be represen-tative. “But, as costs fall and coverage increases, all the signs are that usage will increase rapidly in rural areas and among poorer people. […] As one Somali NGO staff member commented […], ‘they may not have had lunch — but they’ll have a mobile phone.’” Moreover, there is growing evidence that individuals turn to social media platforms for the first time as a result of crisis. “In Thailand, for example, the use of social media increased 20% when the 2010 floods began–with fairly equal increases found in metropolitan Bangkok and in rural provinces.”

While the vast majority of Haitians in Port-au-Prince are not on Twitter, “the city’s journalists overwhelmingly are and and see it as an essential source of news and updates.” Since most Haitians listen to radio, “they are, in fact, the indirect beneficiaries of Twitter information systems.” Another interesting fact: “In Kenya, 27% of radio listeners tune in via their mobile phones.” This highlights the importance of an ecosystem approach when communicating with disaster-affected communities. On a related note, recent statistics reveal that individuals in developing countries spend about 17.5% of their income on ICTs compared to just 1.5% in developing countries.

Communicating with Disaster Affected Communities (CDAC)

Communication is Aid: Curated tweets and commentary from the CDAC Network’s Media and Technology Fair, London 2012. My commentary in blue. This is the first time I’ve used Storify to curate content. (I bumped into the co-founder of the platform at SXSW which reminded me I really needed to get in on the action).

  1. Sha

    re
    “After the Japan earthquake, >20% of ALL web queries issued were on tsunamis.” @spangledrongo #commisaid

    Thu, Mar 22 2012 08:53:43
  2. Would be great to see how this type of search data compares to data from Tweets. Take this analysis of tweets following the earthquake in Chile, for example.
  3. Share
    RT @UNFPA: Professional systems are being replaced by consumer tools says @Google Crisis Response #commisaid

    Thu, Mar 22 2012 08:48:58
  4. And as a result, crisis-affected communities are increasingly becoming digital as I note in this blog post.
  5. Share
    Closed systems closed data will be left behind and unused:crisis response is social and collaboration is empowering @CDACNetwork #commisaid

    Thu, Mar 22 2012 08:49:58
  6. Share
    RT @catherinedem: Crisis response is #social – online social collaboration spikes during and after disaster @spangledrongo #commisaid

    Thu, Mar 22 2012 08:54:03
  7. Share
    “It is essential to have authoritative content” Nigel Snoad at @CDACNetwork’s Media & Tech Fair #commisaid

    Thu, Mar 22 2012 08:58:28
  8. Does this mean that all user-generated content should be ignored because said content does not necessarily come from a known and authoritative source? Who decides what is authoritative?
  9. Share
    we don’t empower communities by giving them info,they empower themselves by giving us info that we can act on-@komunikasikan #commisaid

    Thu, Mar 22 2012 11:31:02
  10. What if this information is not authoritative because it does not come from official sources?
  11. Share
    RT @ushahidi: “In a crisis, the mobile internet stays most resilient, even more than SMS.” #commisaid Nigel Snoad

    Thu, Mar 22 2012 09:02:53
  12. Share
    RT @jqg: Empower local communities to generate their own tools and figure out their own solutions #commisaid

    Thu, Mar 22 2012 09:10:43
  13. See this blog post on Democratizing ICT for Development Using DIY Innovation and Open Data.
  14. Share
    Through #Mission4636 SMS system, radio presenter @carelpedre was able to communicate directly with affected people in Haiti #commisaid

    Thu, Mar 22 2012 12:20:14
  15. This is rather interesting, I hadn’t realized that radio stations in Haiti actively used the information from the Ushahidi Haiti 4636 project.
  16. Share
    Fascinating talk with @carelpedre- many of #Haiti ‘s pre-earthquake twitter users came from @juno7′s lottery push notifications #Commisaid

    Thu, Mar 22 2012 11:11:43
  17. Share
    More about @Carelpedre using 4636 project after #Haiti earthquake bit.ly/plgzXJ #commisaid

    Thu, Mar 22 2012 12:17:52
  18. Share
    Internews: Innovation comes within, info comes from within, people will find ways to communicate no matter what #commisaid @CDACNetwork

    Thu, Mar 22 2012 09:26:25
  19. So best of luck to those who wish to regulate this space! As my colleague Tim McNamara has noted “Crisis mapping is not simply a technological shift, it is also a process of rapid decentralisation of power. With extremely low barriers to entry, many new entrants are appearing in the fields of emergency and disaster response. They are ignoring the traditional hierarchies, because the new entrants perceive that there is something that they can do which benefits others.”
  20. Share
    @souktel: “be simple, be creative and learn from the community around you” #commisaid

    Thu, Mar 22 2012 10:57:09
  21. Share
    Tools shouldn’t own data. RT @whiteafrican: “It’s not about the platform being open, it’s about the data being open”- @jcrowley #commisaid

    Thu, Mar 22 2012 11:56:08
  22. Share
    Humanitarians have to get their heads around media and tech or risk being left behind #m4d #media #tech #commisaid

    Thu, Mar 22 2012 11:56:58
  23. Share
    Cutting edge is to get the #crowd & the #algorithm to filter each other in filtering massive overload of information in a crisis #commisaid

    Thu, Mar 22 2012 12:01:17
  24. As Robert Kirkpatrick likes to say, “Use the hunch of the expert, machine algorithms and the wisdom of the crowd.”
  25. Share
    “How long until the disaster affected communities start analyzing the aid agencies?” #commisaid

    Thu, Mar 22 2012 12:14:50
  26. Yes! Sousveillance meets analysis of big data on the humanitarian sector.
  27. Share
    Why is it such a big deal, for the humanitarian industry to get feedback from a community? Companies have done it for decades. #commisaid

    Thu, Mar 22 2012 12:17:31
  28. Some of my thoughts on what the humanitarian community can learn from the private sector vis-a-vis customer support.
  29. Share
    People who are not traditional humanitarian actors are taking on humanitarian roles, driven by the democratisation of technology #commisaid

    Thu, Mar 22 2012 13:00:12
  30. Indeed, not only are disaster-affected communities increasingly digital, so are global volunteer networks like the Standby Volunteer Task Force (SBTF).
  31. Share
    Technology is shifting the power balance – it’s helping local communities to organise their own responses to disasters #commisaid

    Thu, Mar 22 2012 13:11:18
  32. Indeed, as a result of these mobile technologies, affected populations are increasingly able to source, share and generate a vast amount of information, which is completely transforming disaster response. More on this here.
  33. Share
    Like Paul Currion’s analogy – humanitarian sector risks obsolescence in the same way the record industry did. Watch out? #commisaid

    Thu, Mar 22 2012 13:17:36
  34. Share


    Thu, Mar 22 2012 14:57:13
  35. One of my favorite books, The Starfish and the Spider: The Unstoppable Power of Leaderless Organizations, has an excellent case study on the music industry. The above picture is taken from that chapter and charts the history of the industry from the perspective of hierarchies vs networks. I’ve argued a couple years ago that the same dynamic is taking place within humanitarian response. See this blog post on Disaster Relief 2.0: Toward a Multipolar System.
  36. Share
    A thousand flowers can bloom beautifully IF common data standards allow sharing. Right now no natural selection improving quality #commisaid

    Thu, Mar 22 2012 13:43:19
  37. Share
    @GSMADisasterRes :free phone numbers &short codes r not silver bullets 4 meaningful communication w/disaster affected communities #commisaid

    Thu, Mar 22 2012 13:58:44
  38. Share
    Scale horizontally, not vertically. The end of command and control?! #commisaid

    Thu, Mar 22 2012 14:07:54
  39. Share
    RT @reeniac: what now? communities have the solution, we need to listen. start by including them in the discussions – Dr Jamilah #commisaid

    Thu, Mar 22 2012 14:14:55