Over the past year, the role of social media in society has appeared to shift. Until recently, the predominant view was quite positive about increasing connections and access to information. Lately the tone has turned far more negative, focusing on the consequences, unanticipated or not, of widespread social monitoring.

Like many individuals and institutions, humanitarian organizations are also contending with these at-times-bewildering shifts in perception, policy and technology.

Rather than simply celebrating social media uncritically or disengaging from it given certain dystopian fears, it may be possible to find a more productive engagement with social media as a force for good. Humanitarian organizations can use these services in striking new ways, by focusing on what can be learned from the data being produced at greater-than-ever scale and speed.

Direct Relief, for instance, not only delivers messages through its social channels; it also derives insight from social media data sources to inform its understanding and advance its core mission of strengthening the health and well-being of people in situations of crisis and poverty. By drawing analytically upon these novel sources of data for good, Direct Relief and others have begun to see the outlines of an alternate future for how social media – treated ethically and responsibly – may play a more realistic and hopeful role in humanitarian operations.

The Best (and Worst) of Times for Social Media

To see what’s possible in the future, it’s useful to understand more about the recent past.

Social media has existed for about 15 years. For most of that time, the platforms which marked its rise, including Facebook, Twitter and similar services, emphasized scaling personal communications and expanding new forms of marketing. The business model popularized by Google, and then later by Facebook, of monetizing user data to create targeted advertising, has been ascendant within and beyond the technology sector for the better part of two decades. Harvard professor emeritus Shoshana Zuboff goes so far as to describe it in her book, “The Age of Surveillance Capitalism,” as an emergent economic system where profitability has been re-founded upon pervasive, commercially-focused monitoring by networks of apps, databases and mobile devices.

During the first decade of social media’s rise, the creation of these new forms of digital interaction and commerce were viewed with near-utopian reverence. That sentiment shifted dramatically in recent years. Election hacking and Black Mirror-style social rating systems, among other things, have taken some of the proverbial bloom off the social media rose.

One of the key answers to this best-of-times/worst-of-times dilemma for social media in the humanitarian space has been for companies to create “data for good” programs. Rather than just using the tools on their own, “data for good” programs promote structured access by analysts to the core data resources. Through data sharing and protection agreements, companies with valuable private data can enable its use at enormous scale and frequency to conduct analysis and guide programs for the public benefit.

Direct Relief now engages in several corporate “data for good” efforts, from social media to location intelligence to news publication and healthcare. These different services, on their own and in combination, are opening new possibilities for answering timeless questions about people and communities in crisis, their needs, and changes over time, especially during emergencies.

The Thomas Fire & Facebook Disaster Maps

Direct Relief’s first experience with social media data for humanitarian use was a trial by fire.

In December 2017, the hills above Santa Barbara, where Direct Relief is headquartered, were an inferno. The Thomas Fire, at that time the largest in California’s history, tore through neighboring Ventura County and carved its way north at an astounding rate. The air, right down to the shores of the Pacific Ocean, was a choking cloud of smoke, filled with particulate pollution. Direct Relief responds to many such wildfire events each year, but this one was different because of the scale, and its proximity to its headquarters.

In collaboration with the Santa Barbara and Ventura County Public Health Departments, Direct Relief staff fanned out to distribute thousands of N-95 masks for protection from the smoke.

Where should these masks be distributed for maximum effect? The fire was dynamic, changing literally with the winds. How could staff know where people would be at different times, and how many masks they might need?

A few weeks earlier, Nethope.org hosted a webinar for a new product from Facebook’s Data for Good team called “Disaster Maps.” Facebook’s user base is massive and spread out in dense patterns over virtually the entire planet. If people opt into a setting called location history on their mobile phones, Facebook is able to anonymize and aggregate this data at a neighborhood level and determine how, when and where populations move. Using these aggregated insights, Facebook can create maps of astonishing clarity about the dynamics of entire populations, in real time.

Facebook Disaster Maps are comprised of aggregated user locations within grid squares that are 600 meters on a side and are updated daily. The implications of these data for humanitarian aid are profound.

With access to such maps, which Facebook provides for free to organizations like Direct Relief that sign data-sharing agreements, questions about where and when to maximize things like N-95 mask distribution could start to be answered in new ways. Evacuation patterns could be analyzed to understand the degree to which people were evacuating their neighborhoods or staying behind. The ebb and flow of population density around planned distribution sites or health centers could be tracked throughout the day. The smoke plume pouring off the hills could be overlaid on that movement pattern to determine how many people were in areas of heightened respiratory risk.

Before too long, Direct Relief was making maps routinely from the Facebook data. Daily briefings filled with news of populations in motion. Connections emerged between these mobile clusters of people and information about pre-existing social vulnerabilities, which led to more detailed assessments of areas in need. The town of Montecito was hit in January 2018 with deadly mudslides. Within hours, Facebook disaster maps revealed the residents’ movements, or lack thereof, in the affected area. Questions could be posed empirically of how those numbers lined up with official evacuation zones.

Social Media as an Operational Humanitarian Platform

When the emergencies of late 2017 and early 2018 finally subsided, a threshold had been crossed. Instead of making do with hypothetical assumptions about how people should behave during emergencies, humanitarian agencies like Direct Relief could base their actions on how people actually behave.

With each passing event, more can be learned about how to respond effectively and anticipate the needs of people in crisis, but it’s not enough for it to reside at the 30,000-foot analyst view. For data like Disaster Maps to be truly impactful, it must get to the operational levels of humanitarian response. For Direct Relief, that means figuring out new ways to get data, and, more importantly, interpretations of that data, into the hands of people best placed to use it. By April and May 2018, workshops had been hosted with non-profit primary health centers in Texas to help them prepare for the upcoming hurricane season. The workshops demonstrated how Facebook Disaster Maps might have helped during Hurricane Harvey, had the tool been available at the time.

Simple insights from social media data could be revelatory in the right context. During Hurricane Harvey, the outlying areas of Houston saw elevated population levels for days. In contrast to news about overcrowded shelters downtown, the health centers in retrospect saw their broader lived realities reflected in the Facebook data. Resources were often needed most in the suburban and exurban zones, far from the city center. The same pattern played out later in the year with Hurricane Florence in the Carolinas and Hurricane Michael in Florida, where enormous pockets of need aligned with areas of high social vulnerability, in outlying areas, and away from the urban cores.

Part of the operational dimension of social media for humanitarian aid lies in linking new analytical capacities with the coordination capacity of the more familiar elements of the platforms. In the case of Facebook, Direct Relief piloted the use of groups to encourage coordination among health centers as well as a venue for distributing Disaster Maps. Through Facebook Groups, positive feedback loops emerged, helping guide analytical insights to those on the front lines of crisis while learning from them about the ground-level realities of events and the impacts of their actions.

Facebook Community Help, a service of Facebook Crisis Response that allows individuals to post their needs during an emergency and others to post their ability to meet those needs, also points the way towards a new humanitarian future where the services we’re using to communicate resemble price signaling marketplaces. The demand for and supply of assistance can become increasingly precise and knowable even under the most chaotic conditions. Direct Relief secured the ability of primary health centers to post information into Community Help as institutions rather than individuals, which means that in upcoming emergencies real-time maps of need, supply, and response activity might be feasible.

Learning from Facebook Data for Good

Privacy concerns for all these new developments need to be kept front and center, given the recent cascade of revelations around privacy failures. How do humanitarian actors use granular information about populations in crises without jeopardizing them even more through the release of information which might be used to target or take advantage of them? Here too, the Data for Good team at Facebook arguably marks out a kind of best practice in the field. In order to access Disaster Maps or the underlying datasets of Community Help, Direct Relief agrees to stringent data protection protocols. Strong limits are placed on access, even blocking the use of APIs, to prevent unplanned or unwanted release of information. Companies that deal in private data could take more than one lesson in proper information management from the standards and trade-offs governing Facebook Data for Good.

Towards the end of 2018, after engaging with Facebook Data for Good for the better part of the year, Direct Relief began seeing an uptick in conversations with businesses about how their core datasets could likewise become useful during humanitarian response. Financial services, location intelligence, news media, healthcare and many other sectors began posing interesting questions about the terms, conditions and use cases that might transform their data assets into social goods for communities experiencing disasters.

Each company requires an answer that’s distinctive to their corporate culture and the content of their data. Taken together though, these private datasets, which track money, health and the whereabouts of large-scale populations on a near-constant basis, and which in many ways now hold the highest value for humanitarian response, may find their way into a new common operational picture, at once public and private. When and if they do, humanitarian actors need to make sure that picture is governed by reasonable standards of privacy and effective information management, of the sort marked out in part by the Facebook Data for Good team.

To the surprise of the world, which at the close of 2018 seemed practically consumed by newfound fears of social media, and a repudiation of the earlier utopian impulses, perhaps the true legacy of Facebook’s Data for Good initiative might be to illuminate a third path. It’s possible that with the right guidance, ethics and emphasis on localized results, efforts like Disaster Maps will form a bridge between the private data which increasingly governs public life and the social good, which can be engaged through careful collaborative action.

Future social media users may be so fortunate one day to re-think these tools in their entirety from such a hopeful point of view.