mass collaboration in earthquake risk management

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Mass Collaboration in Earthquake RiskManagementLi Qiu a d , Desheng Dash Wu b c , Rong Fu d , Xiaochun Chen d & ShaWu da School of Business and Management , Hunan University , Changsha,Chinab Reykjavik University , Reykjavík, Icelandc RiskLab , University of Toronto , Toronto, ON, Canadad School of Policy and Public Management , Hunan University ,Changsha, ChinaPublished online: 07 Jun 2010.

To cite this article: Li Qiu , Desheng Dash Wu , Rong Fu , Xiaochun Chen & Sha Wu (2010) MassCollaboration in Earthquake Risk Management, Human and Ecological Risk Assessment: AnInternational Journal, 16:3, 494-509, DOI: 10.1080/10807031003779971

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Human and Ecological Risk Assessment, 16: 494–509, 2010Copyright C© Taylor & Francis Group, LLCISSN: 1080-7039 print / 1549-7860 onlineDOI: 10.1080/10807031003779971

Mass Collaboration in Earthquake Risk Management

Li Qiu,1,3 Desheng Dash Wu,2 Rong Fu,3 Xiaochun Chen,3 and Sha Wu3

1School of Business and Management, Hunan University, Changsha, China;2Reykjavik University, Reykjavık, Iceland and RiskLab, University of Toronto,Toronto, ON, Canada; 3School of Policy and Public Management,Hunan University, Changsha, China

ABSTRACTThe mechanism of mass collaboration in risk management was studied during the

Sichuan earthquake under a Web-based “PeopleFinder” project, where informationis contributed and shared among mass contributors. The case study is providedby a great earthquake that happened in Wenchuan County, Sichuan Province, ofsouthwestern China at 2:28 p.m. on May 12, 2008. We witnessed and experienced therescue and relief efforts for the great earthquake. In this article, two fundamentalframeworks are developed to study the mechanism of mass collaboration. Masscollaboration is proven to be effective in a big public crisis such as the Sichuanearthquake.

Key Words: mass collaboration, Sichuan earthquake, public crisis management,risk management.

INTRODUCTION

Mass collaboration refers to collective actions that occur when many people workindependently on a single project, which typically takes place on the Internet usingSocial-Software and collaborative tools such as technologies. In modern economiclife, cooperation among organizations or individuals becomes increasingly impor-tant to produce complex products and services that satisfy customer demands in thisInformation Explosion Era. Companies can benefit from collaborative innovationand so that they can grow rapidly. For example, Wikipedia.com—an on-line encyclo-pedia complied through mass collaboration—can accumulate information quicklyand effectively by various users’ active participation. Other examples that includeYouTube, Second Life, BMW, and Procter, have also attracted lots of attention dueto the adoption of mass collaboration in recent years.

Address correspondence to both Li Qiu, School of Business and Management, School of Policyand Public Management, Hunan University, Changsha, China. E-mail: [email protected] Desheng Dash Wu, School of Science and Engineering, Reykjavik University, Kringlunnil, IS-103, Reykjavik, Iceland. E-mail: [email protected]

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Wikinomics: How Mass Collaboration Changes Everything (Tapscott and Williams2006) is the first to directly discuss mass collaboration, and advocate that the wholeeconomy might be organized in the way of mass collaboration. From then on, masscollaboration has been investigated by many researchers, as a new model to pro-vide a potentially infinite hypertextual substrate within which the collaboration mayoccur on the Internet. Mass collaboration is especially useful in some complicatedand urgent events that require creativity from a great number of people, for ex-ample, providing solutions to public crises, climate change, alternative energy andsustainability, monitoring and managing possible pandemic disease outbreaks, of-fering microfinance services to help fight poverty, initiating large-scale cultural shiftsthrough the creation and provision of free information and software resources, andso on (Sawhney 2005; Shrader 2006; Bernardo 2007).

Our case study, a PeopleFinder project, described in this article is also basedon the application of mass collaboration. We explored the mechanism of masscollaboration through the PeopleFinder project launched as an risk managementeffort for the Sichuan earthquake.

On May 12, 2008, an earthquake measuring 8.0 on the Richter scale struck inWenchuan County, Sichuan Province, China. This article will mainly describe thePeopleFinder project for the year’s biggest natural disaster in China as a practice ofmass collaboration.

LITERATURE REVIEW

Due to the complexity of mass collaboration, there are limited rigorous researchresults for mass collaboration. However, many comments can still be obtained fromthe Internet.

Definition and Characteristics

Cooperation has been regarded as an “exceptional event” in history and wasalways explained through various theories, such as Utilitarian theories, based onmethodological individualism. In these days, however, cooperation on the Webbecame ubiquitous: a large number of people would be involved in an on-line activityfor a social value, when the need for large-scale collaboration arose. That means thatnot only the frequency of participation has surged, but also the spatial and temporalrange of participation has been incomparably extended. For this, “Wikinomics”(Tapscott and Williams 2006) used the expression of “mass collaboration.”

Tapscott and Williams (2006) started the pioneer work to directly address masscollaboration, where they claimed that mass collaboration was associated with deepchanges in the structure and modus operandi of the corporation and our economy,based on new competitive principles such as openness, peering, sharing, and actingglobally. They proposed four principles from actual cases of mass cooperation, butfailed to provide an adequate definition or criteria for discerning collaboration fromother collective activities.

Elliott (2007) described mass collaboration as the emergence of coordinatedstructures across distributed and often disconnected collaborative participants. He

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also considered that mass collaboration was the best developed and extended collec-tive creative process currently available to humanity for the intersection of stigmergy1

and collaboration.In the Wikipedia webpage, mass collaboration was defined as “a form of collective

action that occurs when large numbers of people work independently on a singleproject, often modular in its nature” (www.wikipedia.org; www.mass-collaboration.net).

Based on the aforementioned definitions, mass collaboration is a collaborationmodel based on collective actions with large numbers of contributors and partici-pants working independently but collaboratively in a single project that is modularin its nature (Tapscott and Williams 2006; Libert and Specter 2008). It has thefollowing attributes:

• It is a content-oriented process, not a directly social interaction–oriented pro-cess. Individuals and groups involved in “mass collaboration” activities and will-ing to take place in creative acts do require the joint development of sharedunderstanding (the essence of collaboration).

• It is a kind of collective action. The outcome not only existed in textualmedium, but also in open source software, music (most “anonymous” folksongs and “traditional” tunes are also arguably sites of long-term mass collab-oration).

• There are four principles: being opened, peering, sharing, and acting globally.

Projects with mass collaboration were typically described to have the followingcharacteristics:

• Based on community,• Self-organized,• Derived by the technological,• Internet revolution.

Web 2.0 technologies and services (such as blogs, wikis, social networks, VoIP,chartrooms, etc.) have created a new sense of innovation, creativity, and ingenu-ity (Tapscott and Williams 2006).

Mechanism

Most of the studies were tackling and discussing the opportunities and effectsof mass collaboration (Tapscott and Williams 2006; Libert and Specter 2008; Howe2008). Bernardo (2007) introduced the role that mass collaboration played in pro-tecting human lives and reducing mass destruction of animals. He pointed out thatmass collaboration would provide early detection, rapid response, and facilitatedisease prevention.

1The term stigmergy was created by Pierre-Paul Grasse (1959), who studied ants and termitessociety, is used to describe a self-organizing system arising from individuals interacting withtheir fellows and the environment.

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Some researchers focused on the management of mass collaboration and triedto improve its efficiency, as management is critical for the success of mass collabo-ration (Libert and Specter 2008). Ahmad Ghazawneh (2008) developed a processframework of how mass collaboration projects could be managed. This frameworkconsisted of three inter-related modules that dealt with the adoption lifecycle ofmass collaboration.

As for the factors that promote mass collaboration and how mass collabora-tion works, it can be attributed to the motivation of collaboration. Kollock (1999)claimed that anticipated reciprocity, reputation, and efficacy comprises the moti-vation for on-line cooperation. Ghosh (1998) also emphasized reputation as theutmost motivation for on-line collaboration, describing it as an implicit barter econ-omy with asymmetric transaction. Benkler (2002) explained motivation for on-linecooperation (collaboration) in the framework of monetary rewards, intrinsic he-donic rewards, and social psychological rewards. On the other hand, Lerner andTirole (2002) categorized such motivation as immediate payoff and delayed payoff.Immediate payoff is calculated by spontaneous use-value and opportunity cost fortime, while delayed payoff is calculated by reputation and job offer one might ac-quire from on-line activity. Ha and Kim (2008) tried to summarize the motivationof on-line collaboration and explore possible dominant participating motivation ofmass collaboration based on Benkler’s framework.

Elliott (2007) found that stigmergy was a deeply rooted mechanism inherent innot only traditional material collaboration, but also a range of emerging on-linepractices, including mass collaboration. He explored the mass collaboration fromthe perspective of stigmergy combined with collaboration activity and the Internet.

It can be seen that these researchers had difficulty in clearly describing themechanism and other aspects of mass collaboration. Further research supportedby empirical evidence is required. This article probes into the mechanism througha case study. Some framework, such as how mass collaboration evolves and whichelements drive the evolution, and so on is discussed in the case study.

Application

Before the term of “mass collaboration” was created, mass collaboration actuallyexisted in many areas, such as art, science, industry, business, education, technology,software design, and medical science. Web-based companies and projects such asWikipedia, YouTube, Second Life, and Linux gained unique and final success be-cause of the adoption of mass collaboration. In addition, most recently “58” complexchemistry, biology, and other problems and “challenges” were solved by more than120,000 “solvers” mostly from the United States, Europe, China, Russia, and othercountries (Sawhney 2005). Mass collaboration was quickly applied in business, suchas BMW, Boeing, and Procter and Gamble, driven by the direct financial benefits.The publication of Tapscott and William’s Wikinomics: How Mass Collaboration ChangesEverything (2006), presented many commercial applications of mass collaboration.

The power of mass collaboration also attracted government agencies; these agen-cies noticed that mass collaboration could make their work more effective. Forexample, after the September 11, 2001 terrorist attack, U.S. government agenciesfound that they had not shared information and could not “connect the dots.”


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Therefore, they developed their own encyclopedia, which was called “IntelliPedia,”where ideas and subjects about the most difficult issues faced by U.S. intelligenceagents were tackled there by more than 3600 intelligence professionals. IntelliPediais not open to the public and is restricted to authorized users via specific local areanetworks (LANs) or from remote terminals via VPNs (Shrader 2006).

Mass collaboration was adopted in public crisis and big disasters in the form ofPeopleFinder, for example, Hurricane Kartrina on Monday, August 29, 2005. Fourdays after the disaster took place, some volunteers with good information technology(IT) experience collaborated and developed an automated process to scour variouswebsites and handle a large amount of data. They created a standard format so thatall entries could be collected in a central database, where 650,000 entries couldbe processed simultaneously. This is a famous people finder project with a goodapplication of mass collaboration in a massive disaster.

In China, the Sichuan earthquake attacked a huge area, caused great loss of livesand dislocated many people. People finder was employed as an effective earthquakerisk management tool using mass collaboration. We followed the ideas from Katrina’sPeopleFinder and applied mass collaboration in this disaster. In this article, weexplore the in-depth mechanism of mass collaboration using the PeopleFinderproject in the Sichuan earthquake as a case study.

PEOPLE FINDER PROJECT IN THE SICHUAN EARTHQUAKE

General Description

A major earthquake measuring 8.0 on the Richter scale jolted Sichuan County ofsouthwest China’s Sichuan Province at 2:28 p.m., May 12, 2008. Thousands of peoplewere in disorder due to the separation from their families or friends. From the verybeginning of the earthquake, people-searching information appeared quickly on theInternet, and was distributed in all kinds of forums and electronic bulletin boardsystems. However, this information was not systematically organized; people had tolook for the relevant information, going from one website to another.

A simple framework was constructed in Dushuren and Qidian (website name) toorganize the distributed people-searching information into an information system. Afew hours later, these sites received overwhelming response, and the information wasdisseminated extensively through Internet communities, forums, blogs, and manyother Web-based places. Then volunteers were attracted by a special communica-tion community named the QQ group (a real-time communication tool producedby QQ.COM) with advanced functions such as information sharing, real-time com-munication, bulletins, and so on (see Figure 1).

In the QQ group a more complicated plan was discussed and work tasks were soonbroken down into more specific and smaller tasks. Under the collaboration amongdifferent people who continually joined the QQ group, the website (www.xunren110.org) was built for the PeopleFinder project 17 hours after the earthquake. Afteranother 19 hours the website was developed as an enquiry site for people to recordand wait for their matching information. That is to say, it took 36 hours since theearthquake occurred to build up the information system in www.xunren110.org.The information source was gathered quickly through collaboration of thousands


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Figure 1. The view of QQ group.

of people (the collaboration was realized through QQ groups, see Figures 2 and 3).The database was expanded rapidly at the rate of about thousands of items per dayin the first 7 days. On May 20, 2008, 8 days after the earthquake, it had accumulatedtwo hundred thousand of clicks with ten thousand clues remaining to be matched.

Figure 2. The expanding process of QQ groups.


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Figure 3. The structure of the QQ group.

Collaborative Process of QQ Groups

A very important, exciting and amazing process as the main communication toolfor mass collaboration related to the QQ group is shown in Figure 2. The processcan be described as a series of collaborations among the various groups. Group 1 wasestablished first with initial collaboration, when two netizens2 formulated the idea ofmaking use of mass collaboration to deal with the people finding problems in a QQgroup after the earthquake happened and the request to find people was increasedgreatly. People with great attention to this event were attracted into Group 1, wherethey just wished to contribute their effort to the earthquake response. It was afterseveral hours that the website was constructed to be ready for discussion in this QQgroup with donations of funds for office space and technology. Some volunteerswith website development expertise proposed that they should build another QQgroup to attract other volunteers with technical expertise and thus could managethe collaboration more efficiently. Consequently, Group 2, named the technicalsupport group, was built up immediately and at the same time, Group 1 became acoordinator and was responsible for the organizing of mass collaboration.

Building the website was the starting point of mass collaboration, with paralleldevelopment of more subsequent work that was discussed and assigned to relevantgroups, such as Groups 3, 4, and 5. Group 3 was an advertising group who propagatedthe project and made it appealing to netizens. Groups 4 and 5 were responsible forthe management of the information that included information on survivors andsearchers. It was burdensome for the volunteers in Groups 4 and 5 to handle suchhuge amounts of information that came from all kinds of channels. It was a big loadof work and seemed to be an impossible task, but some volunteers split the taskof inputting data into some fine-grained tasks. Therefore, the volunteers involvedin the project did not need to handle the whole task, but to handle, for example,

2Editor’s Note: A netizen (or cybercitizen) is a person actively involved in on-line communities(Wikipedia 2009).


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Table 1. The introduction of cooperative groups.

Num ofparticipants

Group2 Name (Max.)1 Content

Group 1 Generalization 200 Macro-coordinationGroup 2 Technical support 152 Website construction and

managementGroup 3 Advertising 200 Propagandize websiteGroup 4 and 5 Information cooperation 360 Collect information; Sort out the

data; Input data into websiteGroup 6 Notice 115 Cooperate with media and release

the outcomesGroup 7 Reception 176 Receive visitors; Question–answerGroup 8 Media 90 Release the outcomes of websites

cooperated to media and sentthem to the disaster area

Group 9 Forum management 25 Forum management

1Num of participants (Max.) refers to the max number that had existed. In fact, it was adynamic number in terms of content of collaborative groups.2Group: the past groups in existence along the project. Some of them disappeared as thedecrease of people finding; some are still developing in terms of new requirements.

20 items of information for one unit, which only required only a few minutes for onevolunteer to accomplish. The experience of Groups 4 and 5 showed the importanceof fine-grained tasks with solid objectives and easy to be operated. Thus, there wereseveral necessary elements for a group to fulfill a special superordinate goal, asdescribed in Figure 3.

With the rapid development of the website, the team was further expanded. Thenumber of volunteers continued to increase, and all kinds of work were required.Therefore, the notice group (Group 6), the reception group (Group 7), the mediagroup (Group 8), and the forum management group (Group 9) were established tomeet these requirements. The specific tasks of all groups are given in Table 1. Thecollaboration among these groups became more complicated as it was increasedfrom two groups’ collaboration to the collaboration among nine groups. Thus, thescale of the collaboration organization reached a peak. The communication andcooperation among the groups still kept lively and smooth.

The Structure of the Website and Relevant Data

The website was designed to facilitate mass collaboration under the principles ofopenness, peering, sharing, and global collaboration. The structure (see Figure 4)was composed by two open accesses to record the information of the victim andthe information of missing people (if it was supposed that the information of themissing people could not be found on-line immediately), so people could use twoways to find people: one was the immediate querying, the other was subsequentinformation matching. The designed structure is shown in Figure 5.


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Figure 4. The home page of the website.

The data from the website outcomes can be devolved into three parts:

• The data obtained through the search engine of the website itself. Users visitedthe website to search for a specific person whose information may have beenposted in the survivor information. Then they might get the satisfactory result.How many users found by searching our website the people they were lookingfor defies statistics, however, third-party statistics may give us a clue: the numberof the accumulated visits reached more than 218,000 according to the datashown in a statistics website, and there were more than 652,000 accumulatedpage views. It was believed that this access helped many people who successfullyfound their friends and relatives through our website.

• The data to be matched with the corresponding information. If users couldnot find the person they were looking for from the survivor information in ourwebsite, they could put the information of the missing people they would liketo search into the database to wait for a reply. So far, there were 31,811 entries

Figure 5. The structure of the website.


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Figure 6. The daily reach index of Alexa.

of people searching information and 146,715 entries of survivor informationin the database pending to be matched.

• The data matched automatically by database. There were two accesses to enterdata into the database. One was for the information of the survivors, andthe other was for the information of the possible missing people. When thetwo databases accumulated a certain amount of information, the databasewould match the information of the survivors and the information of thepossible missing people automatically according to certain criteria, such asname, gender, or address. There have been 140,000 success matching cases sofar.

It could also be shown in Alexa’s indexes (www.alexa.com, a famous statistics web-site), Daily reach; Daily page views; and Daily traffic rank trend (Figures 6–8).

Figure 7. The daily pageviews index of Alexa.


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Figure 8. The daily traffic rank trend index of Alexa.

Compared to other websites, our website (www.xunren110.org) ranked the top,which could be seen from the ranking website of www.baidu.com.

ANALYSIS OF THE CASE

The PeopleFinder project of the Sichuan earthquake was a practical implemen-tation of mass collaboration. To analyze the mechanism of the mass collaboration,we focus on the process first. From the practice, we found that there are three stagesin the process of mass collaboration (see Figure 9).

As described previously, mass collaboration is a content-oriented process, and thecollective activity was guided by what might be described as “superordinate goals”

Figure 9. Mechanism of mass collaboration based on process.


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based on shared understandings. Muzafer Sherif (1958) showed in his seminal ar-ticle, Superordinate Goals in the Reduction of Intergroup Conflict, that conflict could besignificantly reduced in group interactions by the introduction of goals compellinglyshared by group members and that require the collaborative efforts of all. Super-ordinate goals often appeared in the form of mission statements, taglines, projectdescriptions, instructions, or guidelines that attempted to communicate the objec-tives and/or primary concerns of the group. In this context, superordinate goalsalso tend to communicate something of the core values, beliefs, and norms associ-ated with the project, which has the effect of attracting and unifying like-mindedparticipants and even marshalling their contributions.

Many projects of mass collaboration are often associated with the superordi-nate goals, providing stigmergic cues for participants in their collaborative ac-tivities and their community interactions, for example, superordinate goals ofWikipedia.org could be summarized as the free encyclopedia that anyone couldedit (Wikipedia.org’s tagline) and encyclopedic content must be written from aneutral point of view, representing views fairly, proportionate, and without bias. Inthis case, the belief of contributing one’s share to people finding disaster victimsas the highest superordinate goal guides the groups of volunteers. And this goalwas combined tightly with the emergency that could be seen from Figures 6–8. Thecurves in the three figures had the same shape of sharp spikes and the range ofperiod was short with around 1 or 3 weeks. It meant that it attracted most of thepeople focusing on a common purpose in a short time and in one common time pe-riod. When the rescue work was progressed and the concern was dispersed, the masscollaboration in this people-finding project reached its epilogue. This is because thesuperordinate goal has changed then.

In the collaboration based on the communication of QQ groups, the superordi-nate goals dominated the whole process, coordinated and centralized the collabora-tive efforts of the participants, and mediated conflicts during the mass collaborationprocess.

Driven by the superordinate goal, the following stages represented the evolutionprocess of our mass collaboration.

Stage 1: Infrastructure Construction

Being operated based on the Internet and openness was the first and most im-portant principle in mass collaboration. Therefore, building a working platformfor open access is a necessity. There are some dominant agents (main volunteers)to sponsor the mass collaboration project in the beginning (see Figure 5). Theyinvited ideal agents to join in and attract the masses to take action. Then the roughframework of this platform and the whole project was formulated as the result ofthe collaboration among these dominant agents. The framework became maturethrough participation and contribution of more agents. The next stage was the coop-eration and coordination among these multi-agents to set up the working platform.

Stage 2: Stigmergic Collaboration

Recently, researchers suggested that stigmergy is inherent in the workings of theOpen Source software movement (Heylighen et al . 2007; Robles et al . 2005), the


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Figure 10. The processes of Stage 2 (Stigmergic Collaboration).

Internet (Gregorio 2002; Parunak 2006), and even the emergence of a global brain(Heylighen et al . 2007). We named this stage as stigmergic collaboration as theprocesses are similar to the stigmergic processes that are the result of idiosyncraticcharacteristics of individualistic behavior reliant on stimulus–response sequenceswhere the stimulus is an action of one individual and the response is an actiontriggered by another, which may trigger yet another stimulus.

This stage was complex and involved some stigmergic processes. The details of theprocesses are displayed in Figure 10. One step prompted another that may triggeryet another until the mass collaboration is stabilized.

After the completion of the construction of the open platform, the superordinategoals directed the task to the agents. Some dominate agents split the strenuoustask into fine-grained tasks to let the mass focus. Since the task was fine-grained,volunteers could be involved easily under the guidance of the working rules nomatter whether they knew the project as a whole or they only understood andaccepted the superordinate goals. Thus, more participants were encouraged to beinvolved to finish the fine-grained tasks (see Collaboration I of Figure 10).

Then, the other step—Collaboration II was triggered by the previous step after theaccomplishment of the previous task or during the executing of the superordinategoals that provided participants with stigmergic cues in their collaborative activities.The processes of this step were similar to the previous step (see Collaboration IIof Figure 10). Thereafter, this step would trigger another, and the process went onuntil all aspects became stable. The QQ groups’ expanding as introduced earlier isthe correct result of the process too as we designate stigmergy here.

Stage 3: Stability Collaboration

After the second stage, the superordinate goals draw off the new steps no longer,and the state became dynamically stable. This stability was a corresponding stationarydistribution. For a network evolution, there is a stable state or a maximal cycle(Matthew and Alison 1998). The mass collaboration network will ultimately reachits dynamical equilibrium.


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While the superordinate goals mediated conflict surrounding confusion duringthe process, work teams accommodate dynamically according to agents’ time tables.Otherwise, the non-stop outcomes would stimulate the agents’ passion and keep thenetwork active.

Every part of the network was operated rather smoothly, with some problemsappearing occasionally. However, the system could solve and adjust itself with itsself-organizing capability.

Based on the PeopleFinding project, there is another issue we can explore regard-ing to how the mass collaboration came into being. Openness, peering, sharing, andacting globally are the four principles of mass collaboration (Tapscott and Williams2006). Some important practices of accomplishing our project have verified the prin-ciples very well. The principle of peering was shown in fine-grained tasks, becausethe specific and fine tasks have made people easier to accept, understand and actwithout the whole information. The open access of the interface and the group workplatform can bring openness for environment, rules, and participants, which easilykept the network active. The common purpose based on emergency and altruismis the basis for sharing that attracted participants. The last principle, acting glob-ally, meant that the collaboration was not restricted by location or occupation, forexample, nongovernmental organizations (NGOs), media, victims, citizens, and soon. There is a necessary condition as well as a vital element, that is, rules, dominatedby majority of volunteers in this case, which have driven all elements. And in fact, ifthese elements and principles are not separated, they interact among themselves.

We concluded that these three stages of mass ensured the success of this project(see Figure 11). In fact, there is another important experience we can learn fromthis project, which is the importance of a communication platform based on QQgroups’ collaboration. This is necessary to improve the understanding and dissipateconflict between different participations, media, government, common people, vic-tims, volunteers, and relief workers.

Figure 11. Mechanism of mass collaboration based on elements and principles.


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CONCLUSIONS

In this article we have analyzed the case of a PeopleFinder project with apanoramic exhibition and explored the mechanism of mass collaboration. We con-cluded that in big disasters such as the Sichuan earthquake, mass collaborationcan be used as an alternative risk management tool and rapidly respond to emer-gencies, generating delightful outcomes that satisfy different participants. In theprocess of mass collaboration, we probed into the mechanism based on the evolu-tion process with three stages: infrastructure construction, stigmergic collaboration,and mass collaboration. Each stage represents a state, provoking relevant activitiesinto mass collaboration with necessary characteristics as shown in Figures 9 and 10.In terms of four well-known principles (i.e., openness, peering, sharing, and actingglobally), we have analyzed these structure elements that drive the content-orientedcollective activity in mass collaboration.

While some questions should be noted, that in China (likewise in developingcountries), the Internet is not popular in poverty areas. After the onset of a disaster,the information matching road is made broader by practical difficulties. First, theinformation on survivors is very difficult to collect. There needs to be more aidto gather survival data, such as the aid of hospitals and refugees’ camps. Second,after matching the information, the right cue should be sent to the right people,especially the victims, and that needs special volunteers to do so. Therefore, besidesthe collaboration in Internet, there also needs to be off-Internet collaboration, sothat affected people can be involved in the project of mass communication. Sofrom the aspect of managing mass collaboration, there will be more complicatedsituations, which is also a challenge. We hope to research it in future work.

Overall, mass collaboration is changing the world; some former impossibilities cannow happen. The case of the PeopleFinder project described in this article is not anexception. So many people cooperated to solve the people-finding problem after theSichuan earthquake, and the goal was attained, at least partially. Emergencies will stilloccur, whether they are from natural or artificial causes. If we can learn somethingfrom this case study, we hope this kind of experience can improve the responseand management of big disasters in the future. Mass collaboration has been provento be effective in public crisis management. In addition, in a global perspective,collaboration between enterprises shows a new view to resolve problems. We believeit will, especially in combination with information technologies, play an importantrole in facing economy crises and other needs such as sustainable development.

ACKNOWLEDGMENTS

The research was supported by National Social Science Funds of China (No.09CZZ036). All volunteers who attended the PeopleFinder project are acknowl-edged.

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