Complexity and Social Networks Blog

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31 October 2007

Applying theory to managerial problems: how do you resolve communication problems inside firms?

When talking about information sharing and knowledge exchange inside firms, I am faced with the same question over and over again: "How do we know what we know and don't know?". Let me describe this to you with a small example.

HighTech Corp. is a medium sized technology firm in Europe. The communications department is responsible for ensuring a regular information flow and knowledge exchange between stakeholders inside and outside the firm. Internal stakeholders could be but are not limited to R&D engineers, sales staff or the management board of the firm. External stakeholders of the firm are distributors, clients or investors of the firm.

However, such information flow and knowledge exchange inside HighTech Corp. is often disturbed by physical, mental or psychological barriers of its personnel. Hence, the communication department faces serious problems when trying to find out what is going on inside the firm, what latest R&D trends are inside the firm/the industry, how clients react to HighTech Corps. novel product line etc.

As a consequence, HighTech Corp wants to embark on a project that puts a system/method/technology in place that can help the communication department to find out what HighTech Corp knows, what HighTech Corp does and who knows what inside HighTech Corp.

The overarching question(s) I have is/are: From everything we know about theories and concepts of information sharing in social networks, what are the theories with the most predictive power that can help us to better address such real-life issue?

On a more specific level, the questions could be formulated as follows:
- How do firms find out what they know and what they don't know?
- What methods should/should not be used?
- Can technology help?

- Can you get your personnel motivated to share their thoughts and ideas?
- If yes, how?
- If no, what do you do?

Posted by Thomas Langenberg at 10:55 AM | Comments (0) | TrackBack

17 October 2007

Real Time Social Network Feeback Experiment

My colleagues and I at the Media Lab recently completed an experiment where we used our sociometric badges to allow people to see how their social network changed over the course of an intensive two week international college student workshop in Japan. The 45 students were placed into teams of 6-8 after the second day of the workshop, where they learned about leadership and recent advances in manufacturing processes and environmental policy. Over the last few days of the workshop the groups competed on a creative engineering task that was judged by area experts. The students wore the badges all day every day for the entire workshop, giving us an unprecedented amount of compete data.

Over the course of the day we would collect data from the badges by transmitting data wirelessly to basestations, and at the end of the day we would download the data from these basestations for processing. Within ten minutes we printed out individual and group feedback sheets for all participants, who then had a reflection session on the feedback and their activies during the day. This feedback consisted not only of a social network diagram for the course of the workshop up to that point, but also of an analysis of the group dynamics patterns that the badges of observed. In our visualizations we showed how much each individual in the group spoke, who spoke after who, and how interactive (vs. lecture-style) each group member was.

There were many interesting things that we learned from this data. Predictably, at first the Japanese students spoke much less than the students from the US, since the workshop was conducted in English. In addition, most of the American students tended to exhibit "cliquish" behavior: American students would only talk with each other. After the first few days, however, these communication problems were solved, and according to qualititative data the feedback was very helpful on this front. At first the assigned group leaders also tended to monopolize conversations, and this was evident in the feedback. They quickly recognized this, however, and soon were engaging other members in meetings and conversations.

The social network diagrams that we provided were also enlightening. Predictably, before the groups formed communication was sparse with few clusters, but once people were placed into groups the intra-group communication amount rose dramatically, although some groups still exhibited sparse communication patterns. Participants and organizers felt this aspect of the feedback to be the most helpful, because it let each group situate itself in the context of the entire workshop and think about how they could cooperate with other group members and other groups more.

Of course, while this is not a formal experiment, the fact that we were able to generate this feedback in real time significantly drove up participation. While participation in the study was a requirement for participation in the workshop, we observed that people were much happier to wear the badges since they could see the effect so quickly. We think that incorporating this type of feedback into studies of this nature is important since it shows the participants that we really are collecting useful data. While it may have changed their behavior, without useful feedback or functionality it seems impractical to expect individuals to religiously wear a sensing devices for weeks or months all the time. We are currently conducting lab experiments to test how effective these feedback mechanisms are at changing group behavior, and we are planning more field experiments to see if we can actually change organizational structure as well.

Posted by Ben Waber at 10:43 AM | Comments (0)

16 October 2007

Nature editorial-- A matter of trust: Social scientists studying electronic interactions must take the lead on preserving data security

Nature had news article and an accompanying editorial in its most recent issue on the issues around privacy in the developing field of computational social science. These pieces do a nice job of highlighting the need to develop a powerful institutional infrastructure to facilitate the growth of computational social science. If I were to point to one place where this burgeoning field, which has enormous potential to do good, could trip up, it would be in dealing with privacy. The key challenges are balancing the need for privacy of the data of individuals, with the benefits of improved knowledge about human behavior. This balance is manageable, but requires a lot of work by social and computer scientists, as well as the existing self-regulatory systems of the research world (e.g., IRB's). Something that I will write about in the future, but below are excerpts from the article and editorial.

Excerpts from news article:

The hottest growth area in the field [of social science] is computational social science. This is often based on privileged access to electronic data sets such as e-mail records, mobile-phone call logs and web-search histories of millions of individuals. Such studies are ushering in a revolution in the social sciences, specialists say. But there is a trade-off between the scientific interest in working with such data and concerns about privacy. “It’s a huge issue,” says David Lazer, a researcher at the John F. Kennedy School of Government at Harvard University.

...

This work [referring to work by Jon Kleinberg that illustrates the potential to "de-anonymize" network data] reinforces the need for a systematic, institutional approach to improving the privacy rights of those whose data are used, says [Marshall] Van Alstyne [of Boston University]. That echoes the conclusions of a May study by the US National Academies, which said that safeguarding privacy cannot safely be left to individual researchers. It stated that: “Institutional solutions involve establishing tiers of risk and access, and developing data-sharing protocols that match the level of access to the risks and benefits of the planned research.” But [Myron] Gutmann [of the University of Michigan and co-author of the study] and other social scientists also stress that the risks should be kept in perspective. Scientists must meet strict rules on any research on human subjects. In contrast, private firms are largely free from such constraints, and already have wide latitude to snoop on, and data mine, their employees’ work habits.

Excerpts from editorial:

For a certain sort of social scientist, the traffic patterns of millions of e-mails look like manna from heaven. Such data sets allow them to map formal and informal networks and pecking orders, to see how interactions affect an organization's function, and to watch these elements evolve over time. They are emblematic of the vast amounts of structured information opening up new ways to study communities and societies. Such research could provide much-needed insight into some of the most pressing issues of our day, from the functioning of religious fundamentalism to the way behaviour influences epidemics....

But for such research to flourish, it must engender that which it seeks to describe. And so it is encouraging that computational social scientists are trying to anticipate threats to trust that are implicit in their work. Any data on human subjects inevitably raise privacy issues (see page 644), and the real risks of abuse of such data are difficult to quantify. But although the risks posed by researchers seem far lower than those posed by governments, private companies and criminals, their soul-searching is justified. Abuse or sloppiness could do untold damage to the emerging field.

Posted by David Lazer at 8:25 AM | Comments (4)

12 October 2007

Snijders workshop on “Analyzing longitudinal social network data using SIENA”

Full-day workshop “Analyzing longitudinal social network data using SIENA”
Kennedy School of Government, Harvard University
November 6, 2007

Tom A.B. Snijders, University of Oxford

This one-day course is designed primarily for researchers who are currently doing longitudinal social network research or who expect to do so in the future. More specifically, the course is about how to analyse panel data on complete social networks; ``complete’’ meaning that the collection of all network ties within one or several groups is being studied, ``panel” that it is observed at two or more discrete moments in time. The course will treat statistical modelling of network dynamics according to the stochastic actor-oriented approach (Snijders 2001, 2005) as well as the recent extension to the co-evolution of networks and behavior. The computer program SIENA will be used.

There will be the opportunity to discuss questions about the analysis of participants’ data sets, although the one-day restriction will not permit to do practical analyses of those data. The use of the program will be demonstrated, and participants are strongly encouraged to bring a laptop with SIENA installed in advance so as to be able to duplicate the analyses during the session. The program can be downloaded freely .

It is expected that participants have a basic knowledge of social network analysis and of statistical modeling. No prior knowledge of statistical models for networks, or of the SIENA program, is assumed. Further information and publications about this method and software can be found here.

For this event registration is required (space is limited). To register, please send an email to Ines Mergel: netgov@ksg.harvard.edu. We will inform participants about their status within the next two weeks. There is a $50 course fee, which will include lunch.

Posted by David Lazer at 10:38 AM | Comments (0)

9 October 2007

Darrell West on : "Global Perspectives on E-Government"

Below is a posting by Darrell West based on his chapter in Goveranance and Information Technology: From Electronic Government to Information Government, "Global Perspectives on E-Government":

Electronic government offers the promise of moving beyond the use of technology to improve public sector performance to thinking about how to employ new advances for information government and democracy itself. In this latter perspective, the technocratic vision of e-government is supplanted by a viewpoint that envisions technology empowering ordinary citizens and using digital means to bring citizens closer to leaders. In its boldest formulation, technology is seen as becoming a tool for long-term system transformation and democratization.

Not all technological innovation, though, leads to large-scale transformation. There are a number of reasons why political change tends to be small-scale and gradual. Government actions are mediated by a range of factors: institutional arrangements, budget scarcity, group conflict, cultural norms, and prevailing patterns of social and political behavior, each of which restricts the ability of technology to transform society and politics. The fact that governments are divided into competing agencies and jurisdictions limits the ability of policymakers to get bureaucrats to work together promoting technological innovation. Budget considerations prevent government offices from placing services online and using technology for democratic outreach. Cultural norms and patterns of individual behavior affect the manner in which technology is used by citizens and policymakers. In addition, the political process is characterized by intense group conflict over resources. With systems that are open and permeable, groups organize easily and make demands on the political system.

In my research, I look at the speed of global e-government change as a way to investigate whether digital technology is producing system-wide transformation. Thinking globally about technology is useful because it broadens the scope to nations that have very different political, organizational, and financial dynamics. One of the limits of relying on any single country is the difficulty of generalizing beyond that area. An international approach gives researchers a chance to see how political and institutional context affects the ability of governments to innovate in the technology area. Using a detailed content analysis of government websites in 198 different nations in 2001, 2002, and 2003, I measure the information and services that are online and discuss how e-government has changed overtime.

In general, I found that global e-government is not producing a major transformation of the public sector. While some countries have embraced digital government broadly defined, a number of other countries have not placed much information or services online, and are not taking advantage of the interactive features of the Internet. This limits the transformational potential of the Internet and weakens the ability of technology to empower citizens and businesses. Few nations view the Internet as a way to empower ordinary citizens and produce fundamental change in their political systems. This limits the transformational potential of digital government.

______________________________________________________

As noted earlier, I have negotiated with MIT a 20% discount for readers of this blog.

Posted by David Lazer at 12:23 PM | Comments (0)

4 October 2007

The contagiousness of voting

I just read a particularly nice paper on social contagion, that just so elegantly addresses one of the key issues around whether social networks really have an impact on behavior—the direction of the causal arrow. This particular paper examined the “contagiousness of voting.” Does it affect you whether the people you know vote? Generally, it does turn out that there is a positive correlation between whether you vote and whether the people you hang out with vote. Well, the problem—as in many domains—is that this pattern could be reverse causation (i.e. that you hang out with people because they are equally likely to vote as you are—unlikely, but in some domains possible), or, more likely, in this case, that there are other factors (general civic values, SES, etc) that affect both who you are connected to and your behavior. So, how to figure out the causal arrow? The problem with studying social influence in the lab (with all due respect to Asch, etc) is that you can’t simulate a real relationship in a laboratory. What’s the alternative? David Nickerson came up with experimenting with real relationships. Nickerson conducted a field experiment, with a get out the vote (GOTV) treatment, aimed at detecting the contagion of the GOTV treatment through pre-existing relationships. This builds on other randomized field experiments (e.g., Gerber and Green 2000; Green, Gerber, and Nickerson 2003) that have demonstrated that GOTV campaigns actually do increase turnout significantly.

Nickerson took this one step further, to see if the stimulus of the GOTV campaign was contagious to other members of a household. The basic model was that you have a treatment group, which receives the GOTV pitch at the door (this is a door to door canvass), and a placebo group (which receives a pitch about recycling). Treatment and placebo are randomly allocated. By selection, each of these households has two voters.

Thus, we have Treatment/placebo → ego (person who answers the door) →? Alter (person who does not answer the door)

The key research question is whether the GOTV signal is somehow transmitted to the alter by ego. Given “atomistic” assumptions about people (i.e., no interdependence of behavior), even if there is an effect on ego, there should be no effect on alter.

So, what did Nickerson find? First, unsurprisingly, he did find a big effect on ego. In one site (Denver) turnout of the placebo group was 39.1% and of the treatment group 47.7%, and in the second site (Minneapolis) 16.2% vs 27.1%. What about the numbers for the alters? In Denver, the numbers were 36.9% vs 42.4%, and in Minneapolis 17.3% vs 23.6% (pooled one tailed sig < .02). In other words, the secondary effects were about 60% of the primary effects (and this does not measure other possible ripple effects).

Nice.

A few minor critiques of the paper. First, while the main point is to demonstrate the treatment effect, it could do more to examine the pathway of the treatment effect. Is the secondary treatment completely the result of ego voting, thus increasing the probability of alter voting? I doubt it—it’s just too big an effect. Let’s say that 10% of the people who received the treatment voted because of the treatment. For some of those people their alters would have voted anyhow (less than the population mean, likely, but more than 0)—let’s say one in five. Further, let’s say that for some of the remaining 8% there were exogenous reasons why the alter could not vote—they were traveling, working all day, sick, etc—let’s say one in ten. That leaves about 7% who would not have voted, almost all of which now have to turn out by this interpretation. I am skeptical of a contagion effect of close to 100%

More likely: there are indirect effects even when there aren’t direct effects. In particular, I bet that the treatment increased turnout among alters in cases where the ego did not turn out. For example, imagine ego is traveling on election day, gets the GOTV pitch, reminds alter to vote. Ego cannot vote, but alter’s likelihood of voting may increase.

It would have been possible to get at this by looking at turnout rates of alters in cases where ego did or did not receive the treatment, split by whether ego did or did not turn out. This is not perfect, because households where ego did not turn out even after receiving the treatment are likely different than the equivalent households in the placebo condition (e.g., these may be the hard core nonvoting households). How well this could be finessed depends on whether there were other data on subjects (e.g., were there data on whether they had voted in the preceding election). In any case, I bet that it would have been possible to discern some of that pathway.

It also would have been useful to incorporate into the analysis data about ego and alters (again, to the extent possible). Most obviously, were there gender effects? Did it matter whether ego was male and alter female, or vice versa? Did the relative ages of ego and alter matter? For example, was contagion more likely between people the same age (one would guess married couples)? And for pairs where there was a generational difference (one would guess parent-child)—was contagion more likely from senior to junior or vice versa?

These points, I should note, simply would have been whipped cream on an awfully nice pie. And the basis for causal inference in these analyses (what I liked so much about this paper) might be weaker. But so what if there are some neat quasi-experimental results are combined with solid experimental findings? (There is also a more general lesson here about looking for more than just the treatment effect in experiments-- especially where there are possible moderators.)

I also have some concerns about whether the treatment might have spilled over onto the alters, depending on exactly how the canvassing was done. Surely there some cases out of the 486 treatment subjects where the alter was also at the door, or somehow perceptibly in the background. How were these cases handled? Were they discarded? Were they noted?

I strongly doubt that this last issue could greatly have affected the results; and the other analyses I have suggested would just be building on what is already a very nice finding. In any a strongly recommended read for those who are into contagion:

Nickerson, David W. 2008. "Is Voting Contagious? Evidence from Two Field Experiments," American Political Science Review 102(Feb).

Also see

Gerber, Alan, and Donald Green. 2000. “The Effects of Canvassing, Telephone Calls, and Direct Mail on Voter Turnout: A Field Experiment.” American Political Science Review 94: 653-63.

Green, Donald, Alan Gerber, and David Nickerson. 2003. “Getting out the Vote in Local Elections: Results from Six Door-to-Door Canvassing Experiments.” Journal of Politics 65: 1083-96.

Posted by David Lazer at 9:12 PM | Comments (0)

1 October 2007

More on Governance and Information Technology…

As I noted earlier, we will be having a series of entries about a volume that Viktor Mayer-Schönberger and I edited, Governance and Information Technology: From Electronic Government to Information Government. The key theme of the book is to examine the implications of (and obstacles to) rewiring the flow of information within government, between government and society, and within society. Our assertion is that, at this time, the paradigmatic focus needs to be on the bits and the institutions that support (or block!) them, rather than on the hardware through which the bits flow. The subtitle captures this conceptual shift.

Having attended “back to school” nights the last two weeks, let me offer an example grounded in that experience. In the 11 years I have had children in public schools, there has been a major shift (accelerating the last 2 years) in the informational architecture surrounding their education. In particular, the boundaries between the schools and families have become more malleable. This is particularly notable for high school, where students have many teachers, who, in years past, parents en masse would meet just at back to school night. For most parents, that would be the extent of the communication with teachers for the year. Now, however, it is possible to e-mail teachers. It is also possible to sign on to “teachernet” to find out what assignments students have, and, sometimes, grades in real time. The net result is (for many parents) are order of magnitudes increases in communication with teachers. These changes, I would note, are not inevitable, but reflect a set of policy choices by the schools, where the menu of choices is expanded due to the Internet. And these policies might change depending on the experiences of schools. The question one might/should ask is whether these are desirable changes for the education of children. My strong intuition is (generally) yes—that parents have information and power that can increase the effectiveness of schools (although I would have a caveat about the potential amplification of inequalities in society). I should also note that my children are not so thrilled about the elimination of this particular structural hole (kids these days get “disintermediation” as part of their first grade vocabulary).

In any case, this books attempts to explore these themes, looking at the information flows (1) between government and citizens, (2) within government, and (3) among citizens (focusing, of course, on the public/political sphere).

You can download a copy of the first chapter. As noted earlier, I have negotiated with MIT a 20% discount for readers of this blog.

I would also note that we have a wide disciplinary array of contributors, and with each conceptual chapter we have a brief case illustration. Below is the table of contents for the book.

Governance and Information Technology:
From Electronic Government to Information Government

Acknowledgments xi
About the Contributors xiii
1 From Electronic Government to Information Government
Viktor Mayer-Schönberger and David Lazer 1

I Technological Change and Information Flows in Government 15

2 Global Perspectives on E-Government
Darrell M. West 17

Case Illustration
FirstGov: The Road to Success of the U.S. Government's Web Portal
Maria Christina Binz-Scharf 33

3 Electronic Government and the Drive for Growth and Equity
Edwin Lau 39

Case Illustration
"E-Government Is an Outcome": Michael Armstrong and the Transformation of Des Moines

Viktor Mayer-Schönberger and David Lazer 59

4 Challenges to Organizational Change

Multi-Level Integrated Information Structures (MIIS)
Jane E. Fountain 63

Case Illustration
From Computerization to Convergence: The Case of E-Government in Singpore
Ines Mergel 94

Case Illustration
Dubai's Electronic Government
Viktor Mayer-Schönberger and David Lazer 97

II The Blurring of the Informational Boundary between State and Society 99

5 Weak Democracy, Strong Information

The Role of Information Technology in the Rulemaking Process
Cary Coglianese 101

Case Illustration
The EPA EDOCKET System
Gopal Raman 123

6 Freedom of Information and Electronic Government
Herbert Burkert 125

Case Illustration
Protecting Privacy by Requesting Access: Marc Rotenberg and EPIC
Viktor Mayer-Schönberger and David Lazer 142

7 Socio-Technologies of Assembly
Sense Making and Demonstration in Rebuilding Lower Manhattan
Monique Girard and David Stark 145

Case Illustration
The Rise and Fall (?) of Participatory Electronic Information Infrastructures
Åke Grönlund 177

8 "Open-Source Politics" Reconsidered
Emerging Patterns in Online Political Participation
Matthew Hindman 183

8 Case Illustration
Cyberprotesting Globalization: A Case of Online Activism
Sandor Vegh 183

III Evaluating the Impact of Reengineering Information Flows 213

9 The Challenge of Evaluating M-Government, E-Government, and P-Government
What Should Be Compared with What?
Robert D. Behn 215

Case Illustration
The Swiss E-Government Barometer: Kuno Schedler Feels the Temperature of E-Government Services
Viktor Mayer-Schönberger and David Lazer 239

10 Information Quality in Electronic Government
Toward the Systematic Management of High-Quality Information in Electronic Government-to-Citizen Relationships
Martin J. Eppler 241

Case Illustration
Information Quality in Electronic Government Websites: An Example from Italy's Ministry for Public Administration
Lorenzo Cantoni 257

11 It Takes a Network to Build a Network
David Lazer and Maria Christina Binz-Scharf 261

Case Illustration
TeleCities: Sharing Knowledge among European Cities
Viktor Mayer-Schönberger and David Lazer 279

12 The Governing of Government Information
Viktor Mayer-Schönberger and David Lazer 281

Index 293

Posted by David Lazer at 1:02 PM | Comments (0)