Tag Archives: Networks

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?

Twitter Heatmap Hurricane

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.


“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.”

Screen Shot 2012-11-30 at 6.19.45 AM

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.

Screen Shot 2012-11-30 at 6.03.23 AM

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.

On Synchrony, Technology and Revolutions: The Political Power of Synchronized Resistance

Synchronized action is a powerful form of resistance against repressive regimes. Even if the action itself is harmless, like walking, meditation or worship, the public synchrony of that action by a number of individuals can threaten an authoritarian state. To be sure, synchronized public action demonstrates independency which may undermine state propaganda, reverse information cascades and thus the shared perception that the regime is both in control and unchallenged.

This is especially true if the numbers participating in synchrony reaches a tipping point. As Karl Marx writes in Das Kapital, “Merely quantitative differences, beyond a certain point, pass into qualitative changes.” We call this “emergent behavior” or “phase transitions” in the field of complexity science. Take a simple example from the physical world: the heating of water. A one degree increase in temperature is a quantitative change. But keep adding one degree and you’ll soon reach the boiling point of water and surprise! A physical phase transition occurs: liquid turns into gas.

In social systems, information creates friction and heat. Moreover, today’s information and communication technologies (ICTs) are perhaps the most revolutionary synchronizing tools for “creating heat” because of their scalability. Indeed, ICTs today can synchronize communities in ways that were unimaginable just a few short years ago. As one Egyptian activist proclaimed shortly before the fall of Mubarak, “We use Facebook to scheduled our protests, Twitter to coordinate, and YouTube to tell the world.” The heat is already on.

Synchrony requires that individuals be connected in order to synchronize. Well guess what? ICTs are mass, real-time connection technologies. There is conse-quently little doubt in my mind that “the advent and power of connection technologies—tools that connect people to vast amounts of information and to one another—will make the twenty-first century all about surprises;” surprises that take the form of “social phase transitions” (Schmidt and Cohen 2011). Indeed, ICTs can  dramatically increase the number of synchronized participants while sharply reducing the time it takes to reach the social boiling point. Some refer to this as “punctuated equilibria” or “reversed information cascades” in various academic literatures. Moreover, this can all happen significantly faster than ever before, and as argued in this previous blog post on digital activism, faster is indeed different.

Clay Shirky argues that “this basic hypothesis is an updated version of that outlined by Jürgen Habermas in his 1962 publication, The Structural Transformation of the Public Sphere: an Inquiry into a Category of Bourgeois Society. A group of people, so Habermas’s theory goes, who take on the tools of open expression becomes a public, and the presence of a synchronized public increasingly constrains undemocratic rulers while expanding the rights of that public [...].” But to understand the inherent power of synchrony and then leverage it, we must first recognized that synchrony is a fundamental force of nature that goes well beyond social systems.

In his TED Talk from 2004, American mathematician Steven Strogatz argues that synchrony may be one of the most pervasive drivers in all of nature, extending from the subatomic scale to the farthest reaches of the cosmos. In many ways, this deep tendency towards spontaneous order is what pushes back against the second law of thermodynamics, otherwise known as entropy. 

Strogatz shares example from nature and shows a beautiful ballet of hundreds of birds flocking in unison. He explains that this display of synchrony has to do with defense. “When you’re small and vulnerable [...] it helps to swarm to avoid and/or confuse predators.” When a predator strikes, however, all bets are off, and everyone disperses—but only temporarily. “The law of attraction,” says Strogatz, brings them right back together in synchrony within seconds. “There’s this constant splitting and reforming,” grouping and dispersion—swarming—which has several advantages. If you’re in a swarm, the odds of getting caught are far lower. There are also many eyes to spot the danger.

What’s spectacular about these ballets is how quickly they phase from one shape to another, dispersing and regrouping almost instantaneously even across vast distances. Individual changes in altitude, speed and direction are communicated and acted on across half-a-kilometer within just seconds. The same is true of fireflies in Borneo that synchronize their blinking across large distances along the river banks. Thousands and thousands of fireflies somehow overcoming the communication delay between the one firefly at one end of the bank and the other firefly at the furthest opposite end. How is this possible? The answer to this question may perhaps provide insights for social synchrony in the context of resistance against repressive regimes.

Strogatz and Duncan Watts eventually discovered the answer, which they published in their seminal paper entitled “Collective dynamics of small-world networks.” Published in the prestigious journal Nature,  the paper became the most highly cited article about networks for 10 years and the sixth most cited paper in all of physics. A small-world network is a type of network in which even though most nodes are not neighbors of one another, most can still be reached from other nodes by a small number of hops or steps. In the context of social systems, this type of network results in the “small world phenomenon of strangers being linked by a mutual acquaintance.”

These types of networks often arise out of preferential attachment, an inherently social dynamic. Indeed, small world networks pervade social systems. So what does this mean for synchrony as applied to civil resistance? Are smart-mobs synonymous with synchronized mobs? Do ICTs increase the prevalence of small world networks in social systems—thus increasing robustness and co-synchrony between social networks. Will meshed-communication technologies and features like check-in’s alter the topology of small world networks?

Examples of synchrony from nature clearly show that real-time communication and action across large distances don’t require mobile phones. Does that mean the same is possible in social systems? Is it possible to disseminate information instantaneously within a large crowd without using communication technologies? Is strategic synchrony possible in this sense? Can social networks engage in instantaneous dispersion and cohesion tactics to confuse the repressive regime and remain safe?

I recently spoke with a colleague who is one of the world’s leading experts on civil resistance, and was astonished when she mentioned (without my prompting) that many of the tactics around civil resistance have to do with synchronizing cohesion and dispersion. On a different note, some physicists argue that small world networks are more robust to perturbations than other network structures. Indeed, the small work structure may represent an evolutionary advantage.

But how are authoritarian networks structured? Are they too of the small world variety? If not, how do they compare in terms of robustness, flexibility and speed? In many ways, state repression is a form of synchrony itself—so is genocide. Synchrony is clearly not always a good thing. How is synchrony best interrupted or sabotaged? What kind of interference strategies are effective in this context?

The Starfish and the Spider: 8 Principles of Decentralization

“The Starfish and the Spider: The Unstoppable Power of Leaderless Organizations” by Ori Brafman and Rod Beckstrom is still one of my favorite books on organizational theory and complex systems.

The starfish represents decentralized “organizations” while the spider describes hierarchical command-and-control structures. In reviewing the book, the Executive Chairman of the World Economic Forum wrote that “[it has] not only stimulated my thinking, but as a result of the reading, I proposed ten action points for my own organization.”

The Starfish and the Spider is about “what happens when there’s no one in charge. It’s about what happens when there’s no hierarchy. You’d think there would be disorder, even chaos. But in many arenas, a lack of traditional leadership is giving rise to powerful groups that are turning industry and society upside down.” The book draws on a series of case studies that illustrate 8 Principles of Decentralization. I include these below with short examples.

1. When attacked, a decentralized organization tends to become even more open and decentralized:

Not only did the Apaches survive the Spanish attacks, but amazingly, the attacks served to make them even stronger. When the Spanish attacked them, the Apaches became even more decentralized and even more difficult to conquer (21).

2. It’s easy to mistake starfish for spiders:

When we first encounter a collection of file-swapping teenagers, or a native tribe in the Arizona desert, their power is easy to overlook. We need an entirely different set of tools in order to understand them (36).

3. An open system doesn’t have central intelligence; the intelligence is spread throughout the system:

It’s not that open systems necessarily make better systems. It’s just that they’re able to respond more quickly because each member has access to knowledge and the ability to make direct use of it (39).

4. Open systems can easily mutate:

The Apaches did not—and could not—plan ahead about how to deal with the European invaders, but once the Spanish showed up, Apache society easily mutated. They went from living in villages to being nomads. The decision didn’t have to be approved by headquarters (40).

5. The decentralized organization sneaks up on you:

For a century, the recording industry was owned by a handful of corporations, and then a bunch of hackers altered the face of the industry. We’ll see this pattern repeat itself across different sectors and in different industries (41).

6. As industries become decentralized, overall profits decrease:

The combined revenues of the remaining four [music industry giants] were 25 percent less than they had been in 2001. Where did the revenues go? Not to P2P players [Napster]. The revenue disappeared (50).

7. Put people into an open system and they’ll automatically want to contribute:

People take great care in making the articles objective, accurate, and easy to understand [on Wikipedia] (74).

8. When attacked, centralized organizations tend to become even more centralized:

As we saw in the case of the Apaches and the P2P players, when attacked decentralized organizations become even more decentralized (139).

Patrick Phillipe Meier

Mapping the Persian Blogosphere (Updated)

Harvard’s Berkman Center has just released a fascinating study on the politics and culture of the Persian Blogosphere.

Berkman’s social network analysis reveals four major network clusters (with identifiable sub-clusters) in the Iranian blogosphere. The authors have labeled the four clusters as 1) Secular / Reformist, 2) Conservative / Religious, 3) Persian Poetry and Literature, and 4) Mixed Networks.

Surprisingly, a minority of bloggers in the secular/reformist pole appear to blog anonymously, even in the more politically-oriented part of it; instead, it is more common for bloggers in the religious/conservative pole to blog anonymously.

Blocking of blogs by the government is less pervasive than we had assumed. Most of the blogosphere network is visible inside Iran, although the most frequently blocked blogs are clearly those in the secular/reformist pole. Given the repressive media environment in Iran today, blogs may represent the most open public communications platform for political discourse. The peer-to-peer architecture of the blogosphere is more resistant to capture or control by the state than the older, hub and spoke architecture of the mass media model.

So are we likely to witness iRevolutions in Iran?

In authoritarian regimes, networked communications can allow participants to get around state control. As an example, Radio B92 in Serbia simply broadcast through the Internet after the government attempted to shut it down. In Iran, satellite TV, Internet based radio stations, cell phones, and other Internet based tools are difficult if not impossible for the regime to control. Costs are generally high for regimes that limit access and connectivity. The Internet will not lead automatically to liberal, open public spheres in authoritarian regimes, but it will make it harder to control and more costly for authoritarian states to do so. [...]

Early conventional wisdom held that bloggers were all young democrats critical of the regime, but we found conversations including politics, human rights, poetry, religion, and pop culture. Given the repressive media environment and high profile arrests and harassment of bloggers, one might not expect to find much political contestation taking place in the Iranian blogosphere. And yet oppositional discourse is robust. [...]

In conclusion, the authors essentially pose the same question that I am exploring for my dissertation:

The question at hand is not whether the Iranian blogosphere provides a Samizdat to the regime’s Politburo, but whether the new infrastructure of the social nervous system, which is changing politics in the US and around the world, will also change politics in Iran, and perhaps move its hybrid authoritarian/democratic system in a direction that is more liberal in the sense of modes of public discourse, if not necessarily in a direction that is more liberal in the sense of political ideology.

Berkman’s next step should be to move from static network analysis to dynamic analysis. The topology of the network itself over time should reveal other interesting insights. I would recommend they look up Mark Newman at the Santa Fe Institute. Another software program for networks analysis that I would suggest they use is one used to model foodweb dynamics in 3D. This clip demonstrates the program’s features.

Update: I just met with Josh Goldstein, a researcher at the Berkman Center who contributed to this study. Josh was interested in getting more of my thoughts on possible next steps regarding future research using social network analysis (SNA). I suggested they track network parameters (such as degree centrality) over time and find explanations for changes over time. In other words, plot the number of edges that each node (blogger) is connected to over time. For example, how does degree centrality change within the different clusters identified by Berkman after a terrorist events, i.e, events exogenous to the network? Recent research suggests that blogs display a power law relationship between frequency and magnitude, i.e., there are many nodes with few edges, and few nodes with many edges. Does the Persian blogosphere follow this distribution? Why or why not? Does the slope of the power law distribution become flatter or steeper following crises events? Again, why or why not? What social science explanations account for changes in network topologies over time?

Patrick Philippe Meier