A Network Theory of Power

Manuel Castells

Reported by: Li Lu, Peter Knaack, & Lauren Frank

Manuel Castells is  University Professor and the Wallis Annenberg Chair of Communication Technology and Society at the University of Southern California, Los Angeles, and Professor of Sociology and director of the Internet Interdisciplinary Institute at the Open University of Catalonia in Barcelona. He is also Professor Emeritus of Sociology and of City & Regional Planning at the University of California, Berkeley, where he taught for 24 years.

Professor Castells started his talk with his view of how theory serves his work. He suggested that theory should be used to produce knowledge through research, so it is instrumental, not the value itself.  Therefore, theory should always be specific to context. Viewing the networked society as the background of the talk, Manuel proposed that power relationships are fundamental. In any society, those with power determine the rules. Fortunately, power is always balanced by counter-power. In this way, the society is going through constant challenges and evolving. Echoing Bruno Latour’s keynote speech, Castells pointed out that systems move through the actions of individuals.  In the current global network society context, specific social structures are produced, characterized by key organizational forms organized in interwoven networks, in which micro-electronic based technologies function as the key elements underlying these networks.

In suggesting that all this supports a theory of power and counter-power in the network society, Castells identified four different forms of power:

1)      Networking power refers to the power of the actors and organizations included in the networks that constitute the core of the global network society over human collectives or individuals who are not included in these global networks.

2)      Network power (as Grewall defined in the previous session) means the power resulting from the standards required to coordinate social interaction in the networks. In this case power is exercised not by exclusion from the networks but by the imposition of the rules of inclusion. Any social or network action requires social coordination, so it requires standards. These standards display network power. For example, once one protocol of communication gets accepted in the network, it becomes a form of power through imposing the rules of inclusion.

3)      Networked power indicates the power of social actors over other social actors in the network. The forms and processes of networked power are specific to each network. This type of power is the most complicated form. Throughout human history, there are two basic forms of power. The first one is coercive power. In this manner, actors can impose their will over others. The second form is persuasive power, which functions in the minds of people through constructing the meaning of actions. These two forms of power can combine in different proportions. But having the capacity to construct meaning through discourses (persuasive power) is fundamental. In other words, shaping the minds is the more effective way than torturing the bodies.

A worthy following question would be who has the networked power in a global network society. According to Castells, the answer is totally undetermined. However, that does not mean that dominance does not exist. Essentially, different forms of power organized in different networks of power are not unified. There is a distinction between the differentiation of power elite and the formation of ad-hoc elites in particular contexts. The traditional definition of power is not useful here; how these different networked powers connect to each other requires specific analysis.

4)      Finally, network-making power refers to the power to program specific networks according to the interests and values of the programmers, and the power to switch different networks by forming strategic alliances with different networks.  Programmers and switchers are not abstract concepts; they are simply people or actors in the networks. For instance, MIT establishes networks between scientific and military networks, which ensures the domination of MIT in scientific networks and of the US in military technology. Ultimately, these ideas materialize in the brains of social actors. Therefore, the key becomes connecting human networks via communication networks. Here, Castells emphasized that the shaping of communication networks has a decisive effect on other networks (e.g., agenda setting, gatekeeping effect of traditional media).

Of course, there are also mechanisms of counter-power in any society. People are not passive; they receive, challenge, and produce their own products. Thus, counter-power is exercised in a manner symmetrical to power. For instance, in the financial markets, a number of new criteria such as environmental standards have been introduced. Counter-power also works through disrupting network switches. For example, protests against the FCC remind the FCC to take the citizen rights into consideration.

Discussion

• Barzilai-Nahon: In terms of the identity of switchers and programmers, do these labels primarily refer to individuals, or can collectives have the same function? Is it possible that collectives create patterns of interaction which in turn provide the basis for the emergence of new switchers?

Castells: Actors in a network are not always individuals. However, when looking at the formation of an actor, individuals are at the root of collectives, and individuals are the ones that change the collective. However, not all individuals in a collective are equal. Spontaneous networks of protest emerge when individuals, by responding to some event, suddenly form a collective. A second example of collective action is the movement to control the FCC. Some individuals created a loose activist structure, and the identity of those who joined the movement and their reasons for joining have a decisive impact on the identity of the collective. This also has implications for movement evolution, something that is understudied in social movement research: the motivations and background of the first individuals that created a collective before it grew big are important but usually not observed.

• Capra: Networked power has existed throughout history, and might be even more representative of the Renaissance and other historical periods than of the network society.

Castells: Networked power is not unique to the network society. All of the four types of power presented above are present in the contemporary period. The important question in that respect is who is included in these networks, and who holds power positions within them. The answer to this question depends on the nature of the particular network, its goals, components, and technology.

• Latour: In the term network power, neither “network” nor “power” is enlightening.  First, he suggested abandoning the concept of power, asking if there is anything that is not power. Second, he pointed to the inflationary, even hegemonic use of the term network today. Latour asserted that because of the traceability of human action today we tend to call every phenomenon network, rather than using traditional categories such as territory, society, macro. In addition, Latour disagreed with Castells about the importance of theory – only theory can give precision to a confused concept of networks.

Castells agreed to disagree completely with Latour. For him, power is not everywhere. It is a fundamental, but particular type of relationship. He also distinguished between power as relational and domination as an institutional concept. In contrast to earlier societies, the core activities of the network society are organized in networks, based on information and communication technology. Therefore, there are quantitative and qualitative differences between contemporary networks and those of other societies and historical periods.

• Fulk: A them of the conference has been that those excluded from networks are less powerful.  Instead, depending on the network, the excluded can have more power than the included, using the examples of small-business and police coordination networks.

Castells acknowledged this as a very relevant point. He stated that the included are more powerful in terms of the program of the network itself. Therefore, criminal networks have no problem in being excluded. A second order analysis of the relationship between networks is important; power resides in those networks that succeed in competition and are able to impose their will onto other networks.

• Grewall: Does it make sense to distinguish between different kinds of programmers and switchers?

Castells agrees that programmers can be switchers and vice versa. Networks operate efficiently once they have a clear goal and program. He pointed to the connections between business and academic networks and how the former influence the latter’s research agenda. Therefore, switchers are important actors in all networks.

• Tongia: What is your opinion regarding the recent Supreme Court ruling on corporations as individuals?

Castells returned to his point that corporations are ultimately run by individuals. He emphasized the connection between collective actors and the individual, which he hopes to connect ultimately to the individual brain.

• Powell: Social scientists until now have been unable to measure power. He expressed his doubts about mashing up network theory and the phenomenon of power. Powell suggested that Castells’ presentation could as well be titled the “technology of power”, and Powell is not sure whether the concept of networks is useful for an analysis of power.

Castells pointed to the transformative role of technology. He proposed a network theory of power in which power ultimately flows through communication networks. The construction of meaning is the most important form of power. For the first time in history, the system of communication networks provides the basis of this construction of meaning in immersive, interactive discourses that shape people’s minds.

Additional reading:

Castells, M. (2009). Communication Power. New York: Oxford University Press, Inc.

Varieties of Networks, Varieties of Power: Network Multidimensionality in Historical Perspective

David Singh Grewal

Reported by: Sandi Evans & Anna Li

David Singh Grewal, a Junior Fellow at the Harvard Society of Fellows and a Director of the Biobricks Foundation, is a graduate student at the Harvard University’s Government Department. He studies network power in the context of globalization and is the author of Network Power: The Social Dynamics of Globalization (2008).

Grewal began his talk on a tangent discussing how the Biobricks Foundation related to the previous talk on the semantic web. The Biobricks Foundation is a site for the emerging field of synthetic biology, and serves as an online registry for the standardization of biological parts. He described this integration of biological data and metadata as “Web 3.1″ – meaning biopower plus network power. Here, as in the earlier semantic web talks, the issue of privacy loomed large over this potential informational boon, though this topic was not the focus of the rest of this presentation.

Multidimensionality and a historical perspective
Grewal’s starting point consisted of three research questions: 1) what kind of power is at work in the network society? 2) how do networks structure power? 3) do different kinds of networks structure power differently? He then went on to provide a review of literature on network and anthropological theory. Because his presentation was exploratory he elicited and received a great deal of interesting feedback from the audience.

Grewal addressed the methodological argument that a synchronic approach to studying networks provides a single snapshot, and does not measure change over time, which can be considered problematic. By taking a historical perspective he suggests one can analyze networks as processes. Grewal provided a review of literature to support his ideas. First, Grewal discussed various theories of network power. Grewal included his own definition from his book “Network Power” (2008), and emphasized Castells’ (2009) typology: networking power, network power, networked power, and network-making power. Secondly, Grewal addressed a network typology of structures, which included references to Ouchi’s framework on organizational failure (1980), Powell’s (1990) research on network forms of organization, Lipnack and Stamps’ (2000) research on virtual teams, and Ronfeld’s (2006) research on organizational forms. Thirdly, Grewal addressed some anthropological views on networks and related topics such as tribes. He covered the development of tribes, transitions, and concepts of exchanges (reciprocity, redistributive) and related these concepts to communication networks. He also addressed historical models including the ancient, feudal and modern. This broad review of literature was rich in its coverage of conceptualizations about power such as the role of switchers and programmers and their function as the “new citizens” of the network society. He also provided a picture of the modern model where the state has removed the need for hierarchical reciprocity; instead, everybody can be connected through digital technology.

Questions from the audience
Because Grewal’s work was exploratory, the questions and comments from the audience were integral to this talk. Woody Powell suggested that he consider the political, economic and social networks as separate levels, each with its own network structure and then compare them in order to assess issues of power.

Another theoretical question that emerged from the audience was: under what conditions could you predict a major transition in networks? Members of the audience agreed that the focus on networks in transition rather than stages or periodicity was central, though there were many questions about how this question could be studied effectively. One audience member suggested that Grewal consider using cities as a level of analysis because cities, defined as large concentrations of work, could be considered as singular large networks or as a population.

Manuel Castells noted that trying to map out an evolutionary theory of networks was akin to “stepping into a minefield,” but that it was a worthwhile endeavor. He noted that networks need to be put in context in order to observe how they operate, and that the role of technology is integral to the study of networks, particularly in relation to the concept of a Network Society.

Overall, Grewal’s talk brought up several intriguing questions about the role of time and history in network analysis, and he provided a review on both network and anthropological theory.

Additional Readings

Grewal, D. S. (2008). Network Power: The Social Dynamics of Globalization. Yale University Press, 2008.

Linked Data Networks: the Pragmatic Semantic Web

Nigel Shadbolt

Reported by: Sandi Evans & Jaclyn Selby

Nigel Shadbolt is Professor of Artificial Intelligence (AI) and Deputy Head (Research) of the School of Electronics and Computer Science at the University of Southampton. He was a Founding Director of the Web Science Research Initiative, a joint endeavour between the University of Southampton and MIT, and is a Founding Director and Trustee of the Web Science Trust. He is also a Director of the World Wide Web Foundation. His current research focuses on developing Web-Based Semantic Technologies.

Nigel Shadbolt spoke about the Semantic Web and the potential for research. The Semantic Web refers to emerging syntax-based architecture that enables the sharing of data on the Web. The Semantic Web is also referred as Linked Data and Web 3.0. The Semantic Web reflects a rich opportunity for researchers because of the potential for access to large amounts of data. Shadbolt also discussed Uniform Resource Identifiers (URI), a language used to represent information on the World Wide Web, and Resource Description Framework (RDF), a language connected with W3C.

In his lecture, Shadbolt noted that people developed a ‘romantic’ idea that the Semantic Web would be artificial intelligence (AI) ‘magic.’ It would create “proof and trust” but AI never “had a hope of that.” He felt that people had gotten sidetracked from the point, which is its great potential for information sharing. The Semantic Web, according to Shadbolt, is about moving from a web of documents to “a web of data.” He noted that all HTTP (hyper text transfer protocol) does is put “a thin layer of abstraction onto a hideous web of documents.” It creates physical connections between abstract machines. He cited Web addresses, domain name services, rooting systems and HTML (hyper text markup language) as examples of abstract protocols designed to “sit on top” of a variety of operating systems. What the Semantic Web does is to create a method for abstracting and linking the internal components of this “web of data.” The essential idea, says Shadbolt, is to “give Web addresses to atomic facts.” What we have then is a set of principles for the Semantic Web that developers can then attempt to scale.

Shadbolt brings up a few conceptual problems with the Semantic Web, comparing it to dark matter; it is ‘there’ but we can’t ‘feel’ it. A major difficulty lies in the problem of co-referencing. He notes that although he and Wendy Hall often work together they do not often publish together and thus the Semantic Web as such does not recognize that they are linked. It is thus necessary, argues Shadbolt, to take a closer look at how the Semantic Web is constituted.

Shadbolt discussed the significance of URIs, which are Web-based identifiers providing information about properties, values, objects, and relations (Uniform Resource Identifier, n.d.). Shadbolt defined RDFs as a “knowledge representation language for the Web” that “represents information as sets of triples.” RDF is affiliated with W3C and has become a widely used method for modeling information through syntax formats (Resource Description Framework, n.d.)

Examples of RDF Sites
Shadbolt illustrated his discussion of Linked Data with several examples of current RDF sites. These include DBpedia, SPARQL, SameAs.org, and data.gov.uk. DBpedia is a site that extracts structured information from Wikipedia. It is unique in that it enables new mechanism for navigating, linking to and building upon Wikipedia. According to Shadbolt, DBpedia describes about 3 million pieces of data. It also is an example of triple store technology that enables browsing, navigating and semantic queries.
The UK site, data.gov.uk, is a second example of Linked Data. This site stems from a public service mandate by the UK government to provide open access to much government data, including health, education, crime, transportation and fiscal data. Shadbolt states that this site reflects themes of transparency and citizen engagement.

Opportunities and potential threats
This discussion brought up several opportunities and some potential challenges. Shadbolt stated that there is a need for further research into the “shape and structure” of networks. Nosher Contractor noted that these new forms of large, global data sets are huge opportunities for researchers. Though it may be a challenge to get access to some forms of data, publicly available data from sources like government agencies may be useful. Additionally, as the data.gov.uk site exemplifies, this form of data can act as both a public service and as a means to keep governments accountable by making data accessible and understandable. Arguing that data empowers, Shadbolt used the example of the UK government’s decision to make bike accident data available and the resulting production of accident-avoidance Web applications in under 24 hours. He proposed that similar linked data efforts in Haiti could aid in the coordination of relief efforts. URI, according to Shadbolt, frees data in a way that being “locked up inside spreadsheets or large databases” does not. It is Shadbolt’s conviction that governments “should establish the principle that all public services should publish in reusable form all objective data.”

However, the Semantic Web also brings up issues including privacy and data literacy. Shadbolt noted that although some people may feel comfortable with private firms, for example,  Google managing health records, governments have “a rule and responsibility to the people.” He argues, it is time for the invocation of data portability and transparency. Shadbolt pointed out that the Obama administration has not adopted full data portability, and that if a person visits data.gov.uk they are faced with large downloadable files that may or may not be useful. He is anticipating the creation of semantic.data.gov.

Shadbolt noted also that some governments think that raw data can be too dangerous, and that some data should not be authorized for circulation because people are not data literate and cannot interpret it correctly. He then asked how this is different from the data literacy problems we witness in print media. In terms of data literacy, a seminar participant argued that this form of literacy was necessary to enable people to understand these newly accessible forms of data and metadata. In terms of privacy, one seminar participant asked, what mechanisms exist to balance audience rights with the availability of information? She gave the example of the sex offender database in the U.S., which names offenders and has been controversial for taking away individuals’ privacy without providing enough context about the seriousness of past crimes. Hall responded that the Semantic Web is akin to the World Wide Web of 1994 — it is new, and the rules are still being established. So far, there is no such privacy mechanism yet. Shadbolt also touched upon the issue of granularity in relation to privacy. If Semantic Web networks scale down to the level of the individual level, this further touches upon the issue of privacy.

Additional References

• Freebase.com. http://www.freebase.com/
• HM Government. http://data.gov.uk/
• DBpedia  http://dbpedia.org/About
• Open Street Map. http://www.openstreetmap.org/
• Many Eyes. http://manyeyes.alphaworks.ibm.com/manyeyes/
• Resource Description Framework. Wikipedia.org.     http://en.wikipedia.org/wiki/Resource_Description_Framework
• SameAs.org. http://sameas.org/
• Sig Ma. http://sig.ma/
• SPARQL. http://www.w3.org/TR/rdf-sparql-query/
• WC3. http://www.w3.org/
• Web Science Trust. http://webscience.org/trust.html
• Uniform Resource Identifiers. (n.d.). Wikipedia.org.             http://en.wikipedia.org/wiki/Uniform_Resource_Identifier

The Ever Evolving Web: The Power of Networks

Wendy Hall, University of Southampton

Reported by: Jaclyn Selby, Youngji Kim & Amanda Beacom

Dame Wendy Hall is Professor of Computer Science at the University of Southampton School of Electronics and Computer Science and a founding director of the Web Science Research Initiative, now the Web Science Trust (http://webscience.org). Her current research focuses on the Semantic Web and Web science. In her seminar presentation, Professor Hall provided a historical context for online networks, tracing the emergence and growth of the World Wide Web to the current development of the Semantic Web.

Hall began her presentation by discussing how throughout history, people have been writing about linking information and how difficult it is to do. She noted that the brain does this very well and so scholars have sought to develop tools that use the human brain as a model for the organization and management of information. With the creation of increasingly sophisticated machines, people began to think about how machines could be used to create cross-references, links, and associations between related units of information. In 1945, for example, Vannevar Bush, scientific advisor to U.S. President Franklin Roosevelt during World War II, wrote an Atlantic Monthly article titled “As We May Think” which advocated the need for new technologies that use the brain as a model for storing and finding information. This article, which Hall highlighted in her lecture as one of the inspirations for her own work, discusses how a machine could create a system of automatic, “associative indexing,” and uses terms such as “trails” and “web” to describe this system.

Hall described how innovations in computers beginning in the 1960s continued to reference or attempt extensions or augmentations of the human brain. She mentioned her colleague, Ted Nelson, who coined the phrase “everything is deeply intertwingled” to express the complexity of interrelations in human knowledge. In the 1960s, Ted Nelson first used the terms hypertext and hypermedia and created Xanadu, a hypermedia system; and Douglas Engelbart developed Augment, a project with hypertext features that envisioned the use of computers to enhance intellect. In the 1970s and ‘80s, hypertext systems were further developed in research labs and commercially with the introduction of personal computers. Hall and her colleagues created Microcosm (the Mountbatten Archive Application) in the late 1980s to store information links in databases. These ‘linkbases,’ as she referred to them, were to capture all the relationships between different pieces of information. All the links were triples. Source, destination, scripts. Hall noted that although the Internet existed, there was no real web.  Her hypothesis was that hierarchical indexing is what is necessary to store information.

Apple’s HyperCard became available on Macintosh computers in 1987. In 1989, Tim Berners-Lee began development of the World Wide Web to facilitate information sharing among scientists, creating a system of open protocols and universal standards involving Hypertext Transfer Protocol (HTTP) and Hypertext Mark-up Language (HTML). He wrote a paper called “Information Management: A Proposal” and then went on to work on a demo of the ‘World Wide Web’ which he debuted in 1991 to much skepticism. The ACM hypertext conference famously rejected Tim’s paper but by 1993 the idea was widely accepted.  In just a few years, the system became user-friendly with the introduction of the Mosaic, and later the Netscape and Explorer browsers.

After outlining these key historical events, Hall offered some lessons learned in the development of the Web. First, she said, “big is beautiful,” meaning that as Berners-Lee argued, the network is the most important feature of the Web as a hypertext information system. She emphasized that we had lost (for a time) conceptual and contextual linking and that the Web had been “a strangely linkless world” with search engines filling the gap where the missing links were. Other such systems that were developed around the same time as the Web operated on stand-alone workstations, and could be accessed only at those workstations. The Web, in contrast, may be accessed anywhere. Second, “scruffy works,” meaning that the system did not need to be perfect in order to be effective. Links could fail. The third lesson, Hall said, is that “democracy rules.” The Web is based on non-proprietary protocols and universal standards, and demonstrates how everyone has to use such a system, or no one will. Hall points out that ironically, Web search engines such as Google, which are so integral to Web use today, operate in a spirit opposite that of this third lesson. Whereas the Web is an open and transparent system, Google is a closed system with proprietary search algorithms and little transparency. The irony is that when Brinn and Page published their paper on their page ranking algorithm in 1997, they were told it wouldn’t scale.  They had to get financial support and do the math to prove that it would, which they did in 1999. But then they couldn’t make any money so they came up with this idea of auctioning words which turned out to be very successful. One of Hall’s key lessons regarding the rise of Google, which depends on the links we make to make its results more accurate, is that Links equal Power. Ie. if more people point to you than you are rewarded with status you don’t have to pay for.

Hall then described a situation where she asked her students if the Web was truly a hypertext system? Links are unidirectional and don’t point back to where they came from.  However, the World Wide Web was so much better than what came before it that researchers didn’t care and busied themselves exploring “the new universe.”  However, the web did not become a truly ‘social web’ until it completed the transformation from Read Only Web to Read/Write Web.  Hall cites a number of revolutionary social sites (Wikipedia, Galaxy Zoo, Twitter) that are a product of our growing ability to ‘write’ to the web.

The lessons from the development of the Web, of course, also inform the development of the Semantic Web. Hall explained that whereas the Web is built on links between documents, the Semantic Web is built on links between data. This shift from documents to data allows for data re-use, reduces the requirements for human information processing, and releases the large quantity of currently inaccessible data stored in relational databases and Excel spreadsheets by allowing these data to be directly processed by machine. The building blocks of the semantic web are Universal Resource Identifiers (URIs) and the Resource Description Framework (RDF), which describes and links the data, and which Hall equated to HTML. (Nigel Shadbolt’s seminar lecture, which followed Professor Hall’s, provided additional detail on these concepts.). Hall suggested that the aggregation of all this information in a standard manner might make it possible for people to pose queries to the system such as “where is the best place to study journalism?” and receive structured and useful answers.

Hall posed the question of what will be the tipping points for widespread adoption and use of the Semantic Web. One possible tipping point, she said, is the use of the Semantic Web by governments. Both the administration of U.K. Prime Minister Gordon Brown and the administration of U.S. President Barack Obama have announced initiatives for using the Semantic Web. (See the following sites for more information: http://data.gov.uk/ and http://www.sitepoint.com/blogs/2009/03/19/obama-groundbreaking-use-semantic-web/.)

Hall concluded her talk by introducing the emerging interdisciplinary field of Web science, which she refers to also as part of Web 3.0. She envisions Web science as “a process of creative innovation, design and engineering, the social and the technical, and interpretation and analysis,” and “inter-/multi-/trans-disciplinary”—not the union of disciplines, but their intersection. Understanding the web, according to Hall, is a major challenge as large as any other global cause because nobody (as of yet) owns the web and there are possible scenarios which could end in its demise.  She argued that the field—and the questions it will investigate—matter because the Web has become our cultural legacy and social heritage, and because we cannot afford to take the freedom to exchange information online for granted.

Discussion

Q: What are the limits of the knowledge available online?

A: Aside from some archival data, most information is accessible on the Web.

Q: Is a limitation of the Semantic web its objective view of associations, given that the association one person makes between two pieces of information may differ from the association another person makes, depending on different ontologies?

A: Given that the World Wide Web functions without every link to every document, the Semantic Web should be able to function without all possible associations.

The Fuzziness of Inclusion/Exclusion: Network Gatekeeping Theory

Karine Barzilai-Nahon

Reported by: Amanda Beacom & Cuihua (Cindy) Shen

Karine Barzilai-Nahon is an assistant professor at the University of Washington Information School. She studies information policy and politics, particularly information control and gatekeeping, the digital divide, and e-government and e-business in comparative analysis. Recent work has focused on network gatekeeping theory, digital divide metrics, the organizational impact of digital natives, and the development of the concept of “cultured technology” to understand information control in secluded communities.

In her seminar presentation, Professor Barzilai-Nahon used network gatekeeping theory to examine inclusion, exclusion, and power in networks. Network gatekeeping theory, which Barzilai-Nahon has proposed and developed in a series of recent publications, departs from other approaches to information control and gatekeeping in several ways. First, it recognizes three means of exercising power in social networks: (1) decisions; (2) non-decisions; and (3) inactions that shape preferences and awareness. Previous research has emphasized decision-making by elites as a means of exerting power in social interactions. Barzilai-Nahon argues that while decision-making may be an easier mechanism for researchers to observe, non-decisions and the shaping of preferences and awareness are also significant tools for controlling information in networks.

Second, network gatekeeping theory gives equal weight to gatekeepers and the “gated,” which Barzilai-Nahon defines as “the entity subjected to gatekeeping.” In a comprehensive review of gatekeeping theories across a range of scholarly disciplines, Barzilai-Nahon found that most research has focused on the gatekeeper, and little attention has been paid to the concept of the gated. Network gatekeeping theory identifies four attributes of the gated that affect information control in networks: (1) their political power relative to the gatekeeper, an attribute commonly studied in political science; (2) their information production ability, an attribute of traditional interest to economists; (3) their relationships with the gatekeeper, a major focus of social network analysts; and (4) their alternatives in the context of gatekeeping, which is of particular interest to Barzilai-Nahon.

To consider the gated’s alternatives is to acknowledge potential fluidity in the boundaries between gatekeeper and gated in social networks. These fuzzy boundaries are a third distinct feature of network gatekeeping theory. In her seminar presentation, Barzilai-Nahon argued that there is a dynamic flow of power between the identities of the gatekeeper and the gated, and that elite status is transient. According to network gatekeeping theory, a gated actor may become a gatekeeper when the gated possesses the capability to control information and the appropriate social context exists. Gatekeeping is a dynamic status dependent upon social context. Barzilai-Nahon used the example of the Huffington Post to illustrate gatekeeper-gated dynamics. In the social context of its readers, the Huffington Post may be viewed as a gatekeeper of information, but in other contexts, such as that of news sources or of all non-readers, the Huffington Post may be viewed as a gated actor. New information and communication technologies offer novel contexts for gatekeeper-gated dynamics.

Finally, Barzilai-Nahon pointed out that fluidity or fuzziness exists not only in gatekeeper-gated status but also in the broader question of whom or what is included or excluded in social networks. Barzilai-Nahon argued that inclusion/exclusion often reflects self regulation and the social norms of specific contexts. As a member of one network, we may highlight only certain characteristics of ourselves and exclude others. For example, in a professional network, an actor may not discuss a family vacation, whereas in a friend network, an actor may share vacation photos but not work projects. Information control occurs across multiple social dimensions and spheres, and therefore an actor may be included in one social network, and excluded in another, or be a gatekeeper in one network, and the gated in another.

Discussion

• Macy: When it is fuzzy, you throw someone out. So you identify the deviant and exclude them (e.g., trolls in a forum), which help identify the inclusion criteria.
• Capra: Huffington Post only serves as gatekeeper for those who read huffpost. Arianna Huffington already adopted the political culture (selected by the culture as the gatekeeper). She appeals to a certain group and the group selects her. Now she is influencing the group. The gatekeeper emerged. It is not the mob, it is the elite.
• If elites exist ,why would there be the fuzziness of inclusion/exclusion? Because elites would like to dominate, and a lot of self-regulation processes take them to different paths. Unintended outcomes.
• Taplin: There used to be gatekeepers and no alternatives (if movie is made but without a distributor, then the movie doesn’t exist) . Now there are gatekeepers and alternatives. You can put the movie on Youtube. The role of gatekeepers has changed – there are multiple dimensions of power.
• Macy: “never having to say sorry” (love story) is not love, but power. the structure guarantees that it will happen – power.
• Borner: this is an active view of gatekeeping. But there are also passive ways of gatekeeping.
  • Barzilai-Nahon: It’s difficult to operationalize passive gatekeeping. Passive gatekeeping gets to the second dimension of power.
• Tongia – it is interesting to see what is excluded – what is taken out.
• Barzilai-Nahon: Google is a gatekeeper when it exercises info control, but it can be gated in other circumstances (such as in China)
• Butts:  In social network theory, brokerage (Burt’s argument) and exchange theory is very similar to your argument. What you have is equilibrium of gatekeepers in different contexts.  Gatekeeping is a global property, not local property. It also depends on the structure of the network (context) where people are embedded.
• Castells: you are talking about press and internet, this is just one type of gatekeeping. But there are other forms of gatekeeping, like in a club.  Journalists are previously the powerful gatekeepers, but now journlaism crumbles. What is happening is a transformation of gatekeeping, and the gatekeepers. It is still unfolding. We don’t know for sure yet.
• Macy – Nature open review experiment in 2006 is a good example.
• Tongia – am I not the biggest gatekeeper for myself? We tend to look at gatekeepers from the supply side perspective.

Additional readings:

Barzilai-Nahon K. (2009). Gatekeeping: A critical review. Annual Review of Information Science and Technology, 43, 433-478.

Barzilai-Nahon K. (2008). Towards a theory of network gatekeeping: A framework for exploring
information control. Journal of the American Society for Information Science and Technology, 59(9),1493-1512.

Challenges Posed by Network Multidimensionality in the Digital Age

Yochai Benkler

Reported by: Nina O’Brien, Allie Noyes & Lauren Frank

Yochai Benkler is the Berkman Professor of Entrepreneurial Legal Studies at Harvard, and faculty co-director of the Berkman Center for Internet and Society. Before joining the faculty at Harvard Law School, he was Joseph M. Field ‘55 Professor of Law at Yale. He writes about the Internet and the emergence of networked economy and society, the economic, social, and political roles of commons-based practices in the networked environment, and the emergence of large scale cooperation as a major dimension of social production.

In the second session of the Annenberg Networks Network (ANN) conference, Benkler presented his ideas about networks, power and freedom in the digital age.  He began by reviewing different dimensions of power–including political, industrial organization, cultural, institutional design, technical platform design, and social practices and norms.  He posed a series of questions about how power flows differently in the digital age and then framed his focus as exploring how we use the computer-mediated nature of the networked society to make machine observations more complete and refined as a method of studying social relations.

Benkler addressed the changes in legal and organizational power by providing an example of how the network can be used to emphasize counter power (e.g., free music downloads with request for donations).  He suggested that emerging ecosystems based on things like voluntary sites and fan culture may be able to challenge traditional capitalist power structures and destabilize existing categories of power (e.g., consumers vs. producers).  However, as he builds a possible case for the idea that the internet “democratizes,” he also interjects the major waves of criticism of this idea.

The argument for the idea that the internet democratizes is based on the fact that suddenly anyone and everyone has the power to be a “pamphleteer” and to disseminate information widely.  The first generation critique of this argument is based on the issue of fragmentation.  Although anyone can disseminate information, people are consuming information based on personal beliefs and preferences and are no longer confronted with ideas that challenge their point of view.  The second generation critique of the “internet democratizes” idea is related to the power law distribution of links.  It may be possible for anyone to present information to the world vis a vis the internet; however, the vast majority of the information on the internet is never viewed by a substantial audience.

Finally, Benkler reviewed a number of challenges to studying networks, power and freedom in the digital age.  What is the entity of interest?  Is it the blog or perhaps the individual author?  What is the network of interest?  Do blogs and newspapers get combined into one network?  How is it possible to account for diverse structures within a network (e.g., political networks that differ substantially between the left and right)?  What are the limits of network analysis on these questions?  Is is possible to integrate many different kinds of research into network approaches–like qualitative research, text analysis, offline networked power, money and other power systems, and behavioral/brain sciences?

Discussion

• Capra: Multi-dimensional webs are reminiscent of chaos theory which has succeeded in solving equations with variables and producing compact representations of a system.  Have network theorists thought of defining the space of variables?

Benkler: All of this is at an early stage.  Other people can improve upon it with different skill sets.

• Barzilai-Nahon: With bloggers, do we have replication?  Maybe they are not a mob, but instead merging elites in real time.  What do you think?

Benkler: I have had my share of being overly optimistic about the democratizing effect of the web.  By definition, someone who has time online may be elite.  Does it change from a few hundred or thousand people being able to influence the political system to 2-3 million being able to directly affect and a total of 30 million able to indirectly affect? Maybe now being part of the elite makes you part of 20-30% of population, rather than a fraction of a percent.

Barzilai-Nahon: The real question may not be about the numbers but about what it means.  Maybe the number is not important.

• Latour:  There is a vast amount of information available.  Are we talking about scaling up or compounding so many profiles?  Can we go back and forth?  It seems the advantage should be that we can simultaneously look at the whole and zoom in on specific parts.

Benkler:  We may just be using the term “scaling up” differently.  We are scaling up our ability to make subtle judgments that humans can make without the benefit of a machine.  When we zoom back in, we still get a high-resolution image.

Additional Readings:

Benkler, Y. (2006) The Wealth of Networks: How social production transforms markets and freedom. New Haven: Yale UP.

Moving Technology Inside the Network: Multidimensional Networks in a Pervasive Technology Use

Noshir Contractor, Peter Monge and Paul Leonardi

Reported by: Nina O’Brien, Allie Noyes & Courtney Schultz

Noshir Contractor is the Jane S. & William J. White Professor of Behavioral Sciences in the McCormick School of Engineering & Applied Science, the School of Communication and the Kellogg School of Management at Northwestern University, USA. He is the Director of the Science of Networks in Communities (SONIC) Research Group at Northwestern University. He is investigating factors that lead to the formation, maintenance, and dissolution of dynamically linked social and knowledge networks in a wide variety of contexts including communities of practice in business, translational science and engineering communities, public health networks and virtual worlds.

Peter Monge is Professor of Communication at the Annenberg School for Communication and Professor of Management and Organization at the Marshall School of Business, University of Southern California. His most recent book (with Noshir Contractor) is Theories of Communication Networks. He has published theoretical and research articles on organizational communication networks, evolutionary and ecological theory, collaborative information systems, globalization, and research methods.

Paul Leonardi (Ph.D. Stanford University) is Assistant Professor of Communication Studies, Industrial Engineering and Management Sciences, and (by courtesy) Management and Organizations at Northwestern University where he holds the Breed Junior Chair in Design. Paul’s research explores how information technologies and organizations can be simultaneously designed to enhance one another. His work on these topics cuts across the fields of Organization Studies, Communication Studies, and Information Systems and has been published in leading journals in these fields.

In the first session of the Annenberg Networks Network (ANN) conference, Noshir Contractor began by presenting two opposing points of view.  The first view is that technology is an exogenous variable that can shape networks. The second view is that networks shape technology so that networks, instead, become the exogenous variable. Contractor explains that even though there are two opposing views, they share something in common – they both see technology and networks as distinct entities. It is important that we, as network scholars, attempt to transcend that view so that technology and networks can be brought together. Two theories where briefly discussed which attempt to accomplish this: actor network theory and the sociomaterial approach.

According to Contractor, including technology in networks is a useful step to address many of the challenges researchers currently face. First, in addition to people, nodes could also include things such as documents or computer programs. When the types of nodes change, so do the relationships between these nodes.  People can be friends with each other, but in all likelihood they would not consider themselves friends with their database.  Taken together, this shift would create networks with many different types of nodes and many different types of relationships between those nodes. The question he asks is: Can existing network approaches represent this conceptual shift?

Paul Leonardi then presented a case study that serves as an example of a multidimensional network.  The case focused on engineers who do computer models of crash tests for a car manufacturer.  One engineer developed a computer program to assist with the analysis of the crash test models.  Leonardi described the diverse range of network ties that initially led to the dissemination of the computer program.  Initially when people began to use this new program, they continued to seek advice from other people (i.e., experts) about how to analyze crash test models, but eventually as people became familiar with the program, they started using the program itself as an “expert” in the process of figuring out how to analyze crash test models.  The technology actually became a node in the network.  If it was analyzed only as an influence on the network of human relationships, the nature of the network would be distorted.  The multidimensional perspective allows quantitative network methods to more accurately explore the kinds of complex relationships that are typically left to qualitative ethnographic research.

Discussion:

• Wendy Hall: Consider Implications, for example Google Buzz automatically generated networks for individuals based on their  frequency of email with contacts. This has had some terrible consequences and has been a real privacy problem — they have had to scale it back.
  • The Google Buss issue raises a bigger question: who gets to set the rules? Is the policy an opt-out or an opt-in?
• John Taplin: Question for Paul: before JWIN was introduced there were people identified as experts who were called upon, and they slowly become replaced with technology and the network. What happens to the social relations of those people who used to be the go-to experts
  • Paul Leonardi: Response to JT: expertise isn’t always singular — people may have multiple expertise. As well engineers were often getting dumb questions or practical questions (i.e. how do I use this tool in this context) rather than substantive questions about the “why.”
• Ernie Wilson: How would the model respond if instead of losing connections in one sphere and picking it up in others, we consider the ways in which power changes over time, eg, does individual status change over time?
• Karine Barzilai-Nahon: Not sure this model does account for power relations — it illuminates different relationships, but doesn’t really get at power, per se
• Woody Powell: This case study is lovely because it clearly demonstrates the logic, but scaling up may be premature — we want the specific case to illuminate whether relations change “on the ground”
• David Graywell: Why is technology here represented as a node rather then a linking connetion? What is the value of separating them out as nodes?
  • Response: consider biological networks: it is often useful to distinguish between patterns of organizations and biological structures. Structure os an embodiment of particular relations
  • Yochai Benkler: My take was that this was about working with general purpose tools for dealing with theoretically generated claims about human relations
  • Michael Macy: To the question of whether the nodes have to be motivated or if they can be artifacts, CMC research demonstrates why. A nice metaphor is of two people crashing their cars. That interaction is mediated by the materials of the car they are driving
• Carter Butts: To describe things completely you need lots of variables, but there’s a danger of being overrun by the proffered complexity. a theoretical challenge is to have the development of the models keep pace with theoretical objects. There is a limit on the utility of additional complexity.
• Lada Adamic: How can we do different things with the data than we were able to do before, substantively? Or do we have to reduce things down to crunch the data anyway, in which case we would be comparing more of the same kinds of things?
• Response: Noshir Contractor: in this case the JT node becomes more central, and here it is obvious in a way that would not otherwise be as clear. You can specify the logic of attraction. The real advantage is that you can see those configurations and determine if they are more frequent than random.
• Response to the power questions raised by Wilson and Taplin: marginalization in the network is a distinct possibility — though those marginalized people would show up, perhaps as isolates, so the model does capture that to some extent.
• Paul Leonardi: How can we map these relationships? If you’re interested in power, you can ask those questions too — the advantage of the ethnographic sample is that we have the opportunity to learn what is important to the individuals in the network. That drove the decision about how to model it. That is a really important concern in scaling up to larger networks — how can you keep that kind of specificity alive?
• Is a certain measure an indicator of power,  or is power a relation?

Additional Readings:

Monge, P. R., & Contractor, N. S. (2003). Theories of communication networks. Oxford: Oxford UP.

Leonardi, P.M., & Bailey, D. (2008). Transformational Technologies and the Creation of New Work Practices: Making Implicit Knowledge Explicit in Task-based Offshoring. MIS Quarterly, Vol. 32, No. 2, pp. 159-176.