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.