Tag Archives: Capital

Why Digital Social Capital Matters for Disaster Resilience and Response

Recent empirical studies have clearly demonstrated the importance of offline social capital for disaster resilience and response. I’ve blogged about some of this analysis here and here. Social capital is typically described as those “features of social organizations, such as networks, norms, and trust, that facilitate action and cooperation for mutual benefit.” In other words, social capital increases a group’s capacity for collective action and thus self-organization, which is a key driver of disaster resilience. What if those social organizations were virtual and the networks digital? Would these online communities “generate digital social capital”? And would this digital social capital have any impact on offline social capital, collective action and resilience?

Social Capital

A data-driven study published recently, “Social Capital and Pro-Social Behavior Online and Offline” (PDF), presents some fascinating insights. The study, carried out by Constantin M. Bosancianu, Steve Powell and Esad Bratovi, draws on their survey of 1,912 Internet users in Bosnia & Herzegovina, Croatia and Serbia. The authors specifically consider two types of social capital: bonding social capital and bridging social capital. “

“Bridging social capital is described as inclusive, fostered in networks where membership is not restricted to a particular group defined by strict racial, class, linguistic or ethnic criteria.  Regular interactions inside these networks would gradually build norms of generalized trust and reciprocity at the individual level. These relationships [...] are able to offer the individual access to new information but are not very adept in providing emotional support in times of need.”

“Bonding social capital, on the other hand, is exclusive, fostered in tight-knit networks of family members and close friends. Although the degree of information redundancy in these networks is likely high (as most members occupy the same social space), they provide [...] the “sociological superglue” which gets members through tough emotional stages in their lives.”

The study’s findings reveal that online and offline social capital were correlated with each other. More specifically, online bridging social capital was closely correlated with offline bridging social capital, while online binding social capital was closely correlated with offline binding social capital. Perhaps of most interest with respect to disaster resilience, the authors discovered that “offline bridging social capital can benefit from online interactions.”

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Digital Humanitarians and The Theory of Crowd Capital

An iRevolution reader very kindly pointed me to this excellent conceptual study: “The Theory of Crowd Capital”. The authors’ observations and insights resonate with me deeply given my experience in crowdsourcing digital humanitarian response. Over two years ago, I published this blog post in which I wrote that, “The value of Crisis Mapping may at times have less to do with the actual map and more with the conversations and new collaborative networks catalyzed by launching a Crisis Mapping project. Indeed, this in part explains why the Standby Volunteer Task Force (SBTF) exists in the first place.” I was not very familiar with the concept of social capital at the time, but that’s precisely what I was describing. I’ve since written extensively about the very important role that social capital plays in disaster resilience and digital humanitarian response. But I hadn’t taken the obvious next step: “Crowd Capital.”

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John Prpić and Prashant Shukla, the authors of “The Theory of Crowd Capital,” find inspiration in F. A. Hayek, “who in 1945 wrote a seminal work titled: The Use of Knowledge in Society. In this work, Hayek describes dispersed knowledge as:

“The knowledge of the circumstances of which we must make use never exists in concentrated or integrated form but solely as the dispersed bits of incomplete and frequently contradictory knowledge which all the separate individuals possess. […] Every individual has some advantage over all others because he possesses unique information of which beneficial use might be made, but of which use can be made only if the decisions depending on it are left to him or are made with his active cooperation.”

“Crowd Capability,” according to John and Prashant, “is what enables an organization to tap this dispersed knowledge from individuals. More formally, they define Crowd Capability as an “organizational level capability that is defined by the structure, content, and process of an organizations engagement with the dispersed knowledge of individuals—the Crowd.” From their perspective, “it is this engagement of dispersed knowledge through Crowd Capability efforts that endows organizations with data, information, and knowledge previously unavailable to them; and the internal processing of this, in turn, results in the generation of Crowd Capital within the organization.”

In other words, “when an organization defines the structure, content, and processes of its engagement with the dispersed knowledge of individuals, it has created a Crowd Capability, which in turn, serves to generate Crowd Capital.” And so, the authors contend, a Crowd Capable organization “puts in place the structure, content, and processes to access Hayek’s dispersed knowledge from individuals, each of whom has some informational advantage over the other, and thus forming a Crowd for the organization.” Note that a crowd can “exist inside of an organization, exist external to the organization, or a combination of the latter and the former.”

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The “Structure” component of Crowd Capability connotes “the geographical divisions and functional units within an organization, and the technological means that they employ to engage a Crowd population for the organization.” The structure component of Crowd Capability is always an Information-Systems-mediated phenomenon. The “Content” of Crowd Capability constitutes “the knowledge, information or data goals that the organization seeks from the population,” while the “Processes” of Crowd Capability are defined as “the internal procedures that the organization will use to organize, filter, and integrate the incoming knowledge, information, and/or data.” The authors observe that in each Crowd Capital case they’ve analyzed , “an organization creates the structure, content, and/or process to engage the knowledge of dispersed individuals through Information Systems.”

Like the other forms of capital, “Crowd Capital requires investments (for example in Crowd Capability), and potentially pays literal or figurative dividends, and hence, is endowed with typical ‘capital-like’ qualities.” But the authors are meticulous when they distinguish Crowd Capital from Intellectual Capital, Human Capital, Social Capital, Political Capital, etc. The main distinguishing factor is that Crowd Capability is strictly an Information-Systems-mediated phenomenon. “This is not to say that Crowd Capability could not be leveraged to create Social Capital for an organization. It likely could, however, Crowd Capability does not require Social Capital to function.”

That said, I would opine that Crowd Capability can function better thanks to Social Capital. Indeed, Social Capital can influence the “structure”, “content” and “processes” integral to Crowd Capability. And so, while the authors argue that  “Crowd Capital can be accrued without such relationship and network concerns” that are typical to Social Capital, I would counter that the presence of Social Capital certainly does not take away Crowd Capability but quite on the contrary builds greater capability. Otherwise, Crowd Capability is little else than the cultivation of cognitive surplus in which crowd workers can never unite. The Matrix comes to mind. So this is where my experience in crowdsourcing digital humanitarian response makes me diverge from the authors’ conceptualization of “Crowd Capital.” Take the Blue Pill to stay in the disenfranchised version of Crowd Capital; or take the Red Pill if you want to build the social capital required to hack the system.

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To be sure, the authors of Crowd Capital Theory point to Google’s ReCaptcha system for book digitization to demonstrate that Crowd Capability does not require a network of relationships for the accrual of Crowd Capital.” While I understand the return on investment to society both in the form of less spam and more digitized books, this mediated information system is authoritarian. One does not have a choice but to comply, unless you’re a hacker, perhaps. This is why I share Jonathan Zittrain’s point about “The future of the Internet and How To Stop It.” Zittrain promotes the notion of a “Generative Technologies,” which he defines as having the ability “to produce unprompted, user-driven change.”

Krisztina Holly makes a related argument in her piece on crowdscaling. “Like crowdsourcing, crowdscaling taps into the energy of people around the world that want to contribute. But while crowdsourcing pulls in ideas and content from outside the organization, crowdscaling grows and scales its impact outward by empowering the success of others.” Crowdscaling is possible when Crowd Capa-bility generates Crowd Capital by the crowd, for the crowd. In contrast, said crowd cannot hack or change a ReCaptcha requirement if they wish to proceed to the page they’re looking for. In The Matrix, Crowd Capital accrues most directly to The Matrix rather than to the human cocoons being farmed for their metrics. In the same vein, Crowd Capital generated by ReCaptcha accrues most directly to Google Inc. In short, ReCaptcha doesn’t even ask the question: “Blue Pill or Red Pill?” So is it only a matter of time until the users that generate the Crowd Capital unite and revolt, as seems to be the case with the lawsuit against CrowdFlower?

I realize that the authors may have intended to take the conversation on Crowd Capital in a different direction. But they do conclude with a number of inter-esting, open-ended questions that suggest various “flavors” of Crowd Capital are possible, and not just the dark one I’ve just described. I for one will absolutely make use of the term Crowd Capital, but will flavor it based on my experience with digital humanitarias, which suggests a different formula: Social Capital + Social Media + Crowdsourcing = Crowd Capital. In short, I choose the Red Pill.

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Resilience = Anarchism = Resilience?

Resilience is often defined as the capacity for self-organization, which in essence is cooperation without hierarchy. In turn, such cooperation implies mutuality; reciprocation, mutual dependence. This is what the French politician, philo-sopher, economist and socialist “Pierre-Joseph Proudhon had in mind when he first used the term ‘anarchism,’ namely, mutuality, or cooperation without hierarchy or state rule” (1).

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As renowned Yale Professor James Scott explains in his latest bookTwo Cheers for Anarchism, “Forms of informal cooperation, coordination, and action that embody mutuality without hierarchy are the quotidian experience of most people.” To be sure, “most villages and neighborhoods function precisely be-cause of the informal, transient networks of coordination that do not require formal organization, let alone hierarchy. In other words, the experience of anar-chistic mutuality is ubiquitous. The existence, power and reach of the nation-state over the centuries may have undermined the self-organizing capacity (and hence resilience) of individuals and small communities.” Indeed, “so many functions that were once accomplished by mutuality among equals and informal coordination are now state organized or state supervised.” In other words, “the state, arguably, destroys the natural initiative and responsibility that arise from voluntary cooperation.”

This is goes to the heart what James Scott argues in his new book, and he does so  in a very compelling manner. Says Scott: “I am suggesting that two centuries of a strong state and liberal economies may have socialized us so that we have largely lost the habits of mutuality and are in danger now of becoming precisely the dangerous predators that Hobbes thought populated the state of nature. Leviathan may have given birth to its own justification.” And yet, we also see a very different picture of reality, one in which solidarity thrives and mutual-aid remains the norm: we see this reality surface over & over during major disasters—a reality facilitated by mobile technology and social media networks.

Recall Jürgen Habermas’s treatise that “those who take on the tools of open expression become a public, and the presence of a synchronized public increas-ingly constrains undemocratic rulers while expanding the right of that public.” One of the main instruments for synchronization is what the military refers to as “shared awareness.” As my colleague Clay Shirky notes in his excellent piece on The Political Power of Social Media, “shared awareness is the ability of each member of a group to not only understand the situation at hand but also under-stand that everyone else does, too. Social media increase shared awareness by propagating messages through social networks.” Moreover, while “Opinions are first transmitted by the media,” they are then “echoed by friends, family mem-bers, and colleagues. It is in this second, social step that political opinions are formed. This is the step in which the Internet in general, and social media in particular, can make a difference.”

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In 1990, James Scott published Domination and the Arts of Resistance: Hidden Transcripts, in which he distinguishes between public and hidden transcripts. The former describes the open, public interactions that take place between dominators and oppressed while hidden transcripts relate to the critique of power that “goes on offstage” and which the power elites cannot decode. This hidden transcript is comprised of the second step described above, i.e., the social conversations that ultimately change political behavior. Scott writes that when the oppressed classes publicize this “hidden transcript”, they become conscious of its common status. Borrowing from Habermas, the oppressed thereby become a public and more importantly a synchronized public. Social media is the metronome that can synchronize the collective publication of the hidden trans-cript, yielding greater shared awareness that feeds on itself, thereby threatening the balance of power between Leviathan and now-empowered and self-organized mutual-aid communities.

I have previously argued that social media and online social networks also can and do foster social capital, which increases capacity for self-organization and renders local communities more resilient & independent, thus sowing the seeds for future social movements. In other words, habits of mutuality are not all lost and the Leviathan may still face some surprisesAs Peter Kropotkin observed well over 100 years ago in his exhaustive study, Mutual Aid: A Factor of Evolution, cooperation and mutual aid are the most important factors in the evolution of species and their ability to survive. “There is an immense amount of warfare and extermination going on amidst various species; there is, at the same time, as much, or perhaps even more, of mutual support, mutual aid, and mutual defense… Sociability is as much a law of nature as mutual struggle.” 

Sociability is the tendency or property of being social, of interacting with others. Social media, meanwhile, has become the media for mass social interaction; enabling greater volumes of interactions than at any other time in human history. By definition, these mass social interactions radically increase the probability of mutuality and self-organization. And so, as James Scott puts it best, Two Cheers for Anarchism

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Social Media = Social Capital = Disaster Resilience?

Do online social networks generate social capital, which, in turn, increases resilience to disasters? How might one answer this question? For example, could we analyze Twitter data to capture levels of social capital in a given country? If so, do countries with higher levels of social capital (as measured using Twitter) demonstrate greater resiliences to disasters?

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These causal loops are fraught with all kinds of intervening variables, daring assumptions and econometric nightmares. But the link between social capital and disaster resilience is increasingly accepted. In “Building Resilience: Social Capital in Post-Disaster Recover,” Daniel Aldrich draws on both qualitative and quantita-tive evidence to demonstrate that “social resources, at least as much as material ones, prove to be the foundation for resilience and recovery.” A concise summary of his book is available in my previous blog post.

So the question that follows is whether the link between social media, i.e., online social networks and social capital can be established. “Although real-world organizations […] have demonstrated their effectiveness at building bonds, virtual communities are the next frontier for social capital-based policies,” writes Aldrich. Before we jump into the role of online social networks, however, it is important to recognize the function of “offline” communities in disaster response and resilience.

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“During the disaster and right after the crisis, neighbors and friends—not private firms, government agencies, or NGOs—provide the necessary resources for resilience.” To be sure, “the lack of systematic assistance from government and NGOs [means that] neighbors and community groups are best positioned to undertake efficient initial emergency aid after a disaster. Since ‘friends, family, or coworkers of victims and also passersby are always the first and most effective responders, “we should recognize their role on the front line of disasters.”

In sum, “social ties can serve as informal insurance, providing victims with information, financial help and physical assistance.” This informal insurance, “or mutual assistance involves friends and neighbors providing each other with information, tools, living space, and other help.” Data driven research on tweets posted during disasters reveal that many provide victims with information, help, tools, living space, assistance and other help. But this support is also provided to complete strangers since it is shared openly and publicly on Twitter. “[…] Despite—or perhaps because of—horrendous conditions after a crisis, survivors work together to solve their problems; […] the amount of (bounding) social capital seems to increase under difficult conditions.” Again, this bonding is not limited to offline dynamics but occurs also within and across online social networks. The tweet below was posted in the aftermath of Hurricane Sandy.

Sandy Tweets Mutual Aid

“By providing norms, information, and trust, denser social networks can implement a faster recovery.” Such norms also evolve on Twitter, as does information sharing and trust building. So is the degree of activity on Twitter directly proportional to the level of community resilience?

This data-driven study, “Do All Birds Tweet the Same? Characterizing Twitter Around the World,” may shed some light in this respect. The authors, Barbara Poblete, Ruth Garcia, Marcelo Mendoza and Alejandro Jaimes, analyze various aspects of social media–such as network structure–for the ten most active countries on Twitter. In total, the working dataset consisted close to 5 million users and over 5 billion tweets. The study is the largest one carried out to date on Twitter data, “and the first one that specifically examines differences across different countries.”

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The network statistics per country above reveals that Japan, Canada, Indonesia and South Korea have highest percentage of reciprocity on Twitter. This is important because according to Poblet et al., “Network reciprocity tells us about the degree of cohesion, trust and social capital in sociology.” In terms of network density, “the highest values correspond to South Korea, Netherlands and Australia.” Incidentally, the authors find that “communities which tend to be less hierarchical and more reciprocal, also displays happier language in their content updates. In this sense countries with high conversation levels (@) … display higher levels of happiness too.”

If someone is looking for a possible dissertation topic, I would recommend the following comparative case study analysis. Select two of the four countries with highest percentage of reciprocity on Twitter: Japan, Canada, Indonesia and South Korea. The two you select should have a close “twin” country. By that I mean a country that has many social, economic and political factors in common. The twin countries should also be in geographic proximity to each other since we ultimately want to assess how they weather similar disasters. The paired can-didates that come to mind are thus: Canada & US and Indonesia & Malaysia.

Next, compare the countries’ Twitter networks, particularly degrees of  recipro-city since this metric appears to be a suitable proxy for social capital. For example, Canada’s reciprocity score is 26% compared to 19% for the US. In other words, quite a difference. Next, identify recent  disasters that both countries have experienced. Do the affected cities in the respective countries weather the disasters differently? Is one community more resilient than the other? If so, do you find a notable quantitative difference in their Twitter networks and degrees of reciprocity? If so, does a subsequent comparative qualitative analysis support these findings?

As cautioned earlier, these causal loops are fraught with all kinds of intervening variables, daring assumptions and econometric nightmares. But if anyone wants to brave the perils of applied social science research, and finds the above re-search questions of interest, then please do get in touch!

Does Social Capital Drive Disaster Resilience?

The link between social capital and disaster resilience is increasingly accepted. In “Building Resilience: Social Capital in Post-Disaster Recover,” Daniel Aldrich draws on both qualitative and quantitative evidence to demonstrate that “social resources, at least as much as material ones, prove to be the foundation for re-silience and recovery.” His case studies suggest that social capital is more important for disaster resilience than physical and financial capital, and more im-portant than conventional explanations.

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Aldrich argues that social capital catalyzes increased “participation among networked members; providing information and knowledge to individuals in the group; and creating trustworthiness.” The author goes so far as using “the phrases social capital and social networks nearly interchangeably.” He finds that “higher levels of social capital work together more effectively to guide resources to where they are needed.” Surveys confirm that “after disasters, most survivors see social connections and community as critical for their recovery.” To this end, “deeper reservoirs of social capital serve as informal insurance and mutual assistance for survivors,” helping them “overcome collective action constraints.”

Capacity for self-organization is thus intimately related to resilience since “social capital can overcome obstacles to collective action that often prevent groups from accomplishing their goals.” In other words, “higher levels of social capital reduce transaction costs, increase the probability of collective action, and make cooperation among individuals more likely.” Social capital is therefore “an asset, a functioning propensity for mutually beneficial collective action […].”

In contrast, communities exhibiting “less resilience fail to mobilize collectively and often must wait for recover guidance and assistance […].”  This implies that vulnerable populations are not solely characterized in terms of age, income, etc., but in terms of “their lack of connections and embeddedness in social networks.” Put differently, “the most effective—and perhaps least expensive—way to mitigate disasters is to create stronger bonds between individuals in vulnerable populations.”

Social Capital

The author brings conceptual clarity to the notion of social capital when he unpacks the term into Bonding Capital, Bridging Capital and Linking Capital. The figure above explains how these differ but relate to each other. The way this relates and applies to digital humanitarian response is explored in this blog post.