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?
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.
“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.”
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!
Interesting post… let us know if anyone takes you up on your dissertation idea! We’re thinking of having a session around this topic for the Global Platform for DRR in Geneva May next year. Let us know if you would be interested in attending.
Thanks for reading, UNISDR. I’ll definitely let you know if anyone follows up on my dissertation proposal. Yes, I’d certainly be interested to know more about your session next May, thank you.
Two ideas to develop this further:
1. Rather than pairing on geography alone, match countries with similar risk profiles, average number of people affected by natural disasters, or types of disaster. Both Malaysia and Canada are significantly less disaster-prone than their matches. Indonesia and the Philippines could perhaps be a better match, and a better chance to see reciprocity at play in a disaster context.
2. If possible, compare reciprocity both before and after disaster events. Selecting cyclone/hurricane-prone countried could help with this because you know when it’s coming (the before), when it’s passed (after, and waiting a week or two would be good as this gives people time to start using Twitter as a tool of the response), and you have a well-established season when these things happen so you could get some data within a year! I think the after is important; take your example of The Dutch in NYC. How many of their neighbors followed (and did they reciprocate) before Sandy? Probably not a whole lot. How many after Sandy, once The Dutch built up some reputation and momentum as being a source of valuable information? Likely a lot more. This could be an interesting progression from a real-world loose acquaintance-level connection, to a Twitterverse-documented reciprocation, back to a real-world strengthening of the connection into more substantial social capital.
Many thanks for your input, Stefanie. Great to see other colleagues from Tufts interested in this area.
Great piece. Currently writing a book on the impact of natural disasters ON social capital. Would love to chat.
Thanks Kevin, happy to chat. My email: patrick at iRevolution dot net.
Every month there’s a meeting of the NE Electricity Restructuring Roundtable and the latest meeting was on Friday, December 21, 2012. The second panel of the meeting was on “Bracing for Storms in NE” with William Quinlan, Senior VP of Emergency Preparedness, Northeast Utilities, and Marcy Reed, President of National Grid (MA), among others. One of the things they talked about was getting quick information on downed lines and places which have lost power.
After the meeting, I asked Mr Quinlan if he knew about crisis mapping and tools like Ushahidi. He did not, wrote down the concepts, and was very interested in these ideas. Seems to me that there is a great opportunity here to link the crisis mapping community with electrical utilities so that they can improve their emergency procedures before the next disastrous event. You can see the Roundtable presentation at http://www.raabassociates.org/main/roundtable.asp?sel=117
Perhaps we can build social capital before disaster.
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Interesting as usual, Patrick. I have just added Aldrich’s book to my Kindle.
As one who comes from a psychology background originally, the general conclusions do not come as a shock to me. The fact that there might be people out there who would need a lot of persuading on the importance of social capital as an important factor in disaster resiliency is somewhat scary. Presence of strong social support networks have long been known to be associated with decrease risk of some mental illnesses, and a better prognosis for those who develop one. I would expect this finding at the micro-level to be repeated in some form at the macro-level. The city of Galveston recovered and rebuilt after 1900’s hurricane long before FEMA and other agencies. We see rural communities often handle disasters better than cities.
I think, however, expecting Twitter reciprocity to be “directly proportional” to disaster resilience might be to disregard your own caution about causal loops and their complexity. It also includes several assumptions that could be questioned, including whether Twitter reciprocity in fact a good proxy for measuring social capital. Social capital existed long before Twitter, so it is quite possible a community with little Twitter reciprocity might still be strong in capital. Also, the methodology of measuring Twitter reciprocity at the national level, operationally calling it social capital, then looking at disasters in specific cities might not be the best approach. Although social capital may exist within a country at the aggregate level, the methodology seems like it would only be appropriate if we are sure that capital is spread evenly throughout a country. In reality the capital is not evenly spread. Lots of social capital in Los Angeles might have limited, or no effect on Chicago’s resiliency.
It is also a distinct possibility that even in a specific city/town, differences in social capital exist between neighborhoods, so that even a city-level aggregate measure may not accurately represent the city’s “system” of social capital. This raises a question: what is the effective range at which social capital works?
Rather than jumping to matched nation-subjects, between-nation-city comparisons, and such…why not use a much smaller scale and start at the city level and community level comparisons within a single country? Even if you are going to stick with national level comparisons, rather than using historical data, it might be more interesting to wait until a disaster strikes a particular area, then gather the Twitter network data beginning a number of days before the disaster and monitor it throughout (does the event itself increase reciprocity?….).
I am sure such study will find relationships, but, as one who is becoming increasingly attracted to complexity theory, I am not sure you will find the relationships linear.
Hi Joseph, many thanks for your rich and informative commentary. I fully agree with your suggestion for a hyperlocal approach. The challenge will be availability of data at this resolution. Your follow up question, “What is the the effective range at which social capital works?” is fascinating. Thanks again for sharing.
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Very relevant article and comments for me, so thanks. I have recently submitted work I’ve done on this topic (almost exactly). The subject was ways to leverage social media for regional cooperation following an earthquake. Both Israel and Jordan reside on top and next to an active geologic fault with the potential to release a major earthquake. This shared risk as well as the inability of each to respond to it on its own was one of the triggers for this study. Furthermore, the population of both countries have high adoption rates of Facebook with more than 80% penetration of the online users. The study population was emergency responders from Israel and Jordan. The results are very encouraging and their are requests already to have a follow-up work to enhance it.
In regards to the Joseph’s comment- I am currently finalizing a comparative work between four cities in Israel during the last ‘Pillar of Defense’ conflict. The study compares the use of Facebook by these municipalities during an emergency by means of information, interaction, relevancy, engagement etc. but also the relationship between the municipality (local government) and ‘federal’ emergency authority in Israel.
One of my coming goals is two compare two cities from both sides of the border and their social media usages.
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