book spotlight: beyond technonationalism by kathryn ibata-arens

At SASE 2019 in the New School, NYC, I served as a critic on an author-meets-critic session for Vincent de Paul Professor of Political Science Kathryn Ibata-Arens‘s latest book, Beyond Technonationalism: Biomedical Innovation and Entrepreneurship in Asia.  

Here, I’ll share my critic’s comments in the hopes that you will consider reading or assigning this book and perhaps bringing the author, an organizations researcher and Asia studies specialist at DePaul, in for an invigorating talk!

“Ibata-Arens’s book demonstrates impressive mastery in its coverage of how 4 countries address a pressing policy question that concerns all nation-states, especially those with shifting markets and labor pools.  With its 4 cases (Japan, China, India, and Singapore),  Beyond Technonationalism: Biomedical Innovation and Entrepreneurship in Asia covers impressive scope in explicating the organizational dimensions and national governmental policies that promote – or inhibit – innovations and entrepreneurship in markets.

The book deftly compares cases with rich contextual details about nation-states’ polices and examples of ventures that have thrived under these policies.  Throughout, the book offers cautionary stories details how innovation policies may be undercut by concurrent forces.  Corruption, in particular, can suppress innovation. Espionage also makes an appearance, with China copying’s Japan’s JR rail-line specs, but according to an anonymous Japanese official source, is considered in ill taste to openly mention in polite company. Openness to immigration and migration policies also impact national capacity to build tacit knowledge needed for entrepreneurial ventures.  Finally, as many of us in the academy are intimately familiar, demonstrating bureaucratic accountability can consume time and resources otherwise spent on productive research activities.

As always, with projects of this breadth, choices must made in what to amplify and highlight in the analysis.  Perhaps because I am a sociologist, what could be developed more – perhaps for another related project – are highlighting the consequences of what happens when nation-states and organizations permit or feed relational inequality mechanisms at the interpersonal, intra-organizational, interorganizational, and transnational levels.  When we allow companies and other organizations to, for example, amplify gender inequalities through practices that favor advantaged groups over other groups, what’s diminished, even for the advantaged groups?

Such points appear throughout the book, as sort of bon mots of surprise, described inequality most explicitly with India’s efforts to rectify its stratifying caste system with quotas and Singapore’s efforts to promote meritocracy based on talent.  The book also alludes to inequality more subtly with references to Japan’s insularity, particularly regarding immigration and migration. To a less obvious degree, inequality mechanisms are apparent in China’s reliance upon guanxi networks, which favors those who are well-connected. Here, we can see the impact of not channeling talent, whether talent is lost to outright exploitation of labor or social closure efforts that advantage some at the expense of others.

But ultimately individuals, organizations, and nations may not particularly care about how they waste individual and collective human potential.  At best, they may signal muted attention to these issues via symbolic statements; at worst, in the pursuit of multiple, competing interests such as consolidating power and resources for a few, they may enshrine and even celebrate practices that deny basic dignities to whole swathes of our communities.

Another area that warrants more highlighting are various nations’ interdependence, transnationally, with various organizations.  These include higher education organizations in the US and Europe that train students and encourage research/entrepreneurial start-ups/partnerships.  Also, nations are also dependent upon receiving countries’ policies on immigration.  This is especially apparent now with the election of publicly elected officials who promote divisions based on national origin and other categorical distinctions, dampening the types and numbers of migrants who can train in the US and elsewhere.

Finally, I wonder what else could be discerned by looking into the state, at a more granular level, as a field of departments and policies that are mostly decoupled and at odds. Particularly in China, we can see regional vs. centralized government struggles.”

During the author-meets-critics session, Ibata-Arens described how nation-states are increasingly concerned about the implications of elected officials upon immigration policy and by extension, transnational relationships necessary to innovation that could be severed if immigration policies become more restrictive.

Several other experts have weighed in on the book’s merits:

“Kathryn Ibata-Arens, who has excelled in her work on the development of technology in Japan, has here extended her research to consider the development of techno-nationalism in other Asian countries as well: China, Singapore, Japan, and India. She finds that these countries now pursue techno-nationalism by linking up with international developments to keep up with the latest technology in the United States and elsewhere. The book is a creative and original analysis of the changing nature of techno-nationalism.”

—Ezra F. Vogel, Harvard University

“Ibata-Arens examines how tacit knowledge enables technology development and how business, academic, and kinship networks foster knowledge creation and transfer. The empirically rich cases treat “networked technonationalist” biotech strategies with Japanese, Chinese, Indian, and Singaporean characteristics. Essential reading for industry analysts of global bio-pharma and political economists seeking an alternative to tropes of economic liberalism and statist mercantilism.”

—Kenneth A. Oye, Professor of Political Science and Data, Systems, and Society, Massachusetts Institute of Technology

“In Beyond Technonationalism, Ibata-Arens encourages us to look beyond the Asian developmental state model, noting how the model is increasingly unsuited for first-order innovation in the biomedical sector. She situates state policies and strategies in the technonationalist framework and argues that while all economies are technonationalist to some degree, in China, India, Singapore and Japan, the processes by which the innovation-driven state has emerged differ in important ways. Beyond Technonationalism is comparative analysis at its best. That it examines some of the world’s most important economies makes it a timely and important read.”

—Joseph Wong, Ralph and Roz Halbert Professor of Innovation Munk School of Global Affairs, University of Toronto

“Kathryn Ibata-Arens masterfully weaves a comparative story of how ambitious states in Asia are promoting their bio-tech industry by cleverly linking domestic efforts with global forces. Empirically rich and analytically insightful, she reveals by creatively eschewing liberalism and selectively using nationalism, states are both promoting entrepreneurship and innovation in their bio-medical industry and meeting social, health, and economic challenges as well.”

—Anthony P. D’Costa, Eminent Scholar in Global Studies and Professor of Economics, University of Alabama, Huntsville

For book excerpts, download a PDF here.  Follow the author’s twitter feed here.

russian and chinese control of social media

Last week, I was asked to be a discussant on a panel for a conference on Russian media. I responded to a paper by journalist, Andrei Soldatov, whose paper chronicled the Russian state’s response to social media. The way I summarized it is as follows:

• As with most states, initial confusion.
• Then, journalists, and social media by extension, were granted Western style autonomy.  Until…
• The contraction of the Russian economy de-legitimized Western views of press freedom.
• And then the Russian state clumsily tried to usurp social media firms.
• And then that failed, they turned to the Chinese state for help managing social media.

In my reading, then, the Russian state is in between Western and Chinese models of social media control. The Western model is passive and uses law enforcement as a model. You let people post what they want but you do surveillance and intervene as needed. In the Chinese model, you control the entire platform and censor as needed.

Soldatov added that recently the Russian and Chinese states have met to set up standards and arrange for the purchase of Chinese equipment, which suggests that the Russian state is going deeper into the Chinese model of social control.

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new ways to measure movements via hyper network sampling

Rory, from the home office in South Bend, sends me links to new social movement research. A major question in social movement research is how you measure contentious politics. A lot of our sources are notoriously incomplete, such as media accounts. Kriage Bayerln, Peter Barwis, Bryant Crubaugh, and Cole Carnesecca use hypernetwork sampling (asking a random sample of people to list their social ties) to attack this issue. From Sociological Methods and Research:

The National Study of Protest Events (NSPE) employed hypernetwork sampling to generate the first-ever nationally representative sample of protest events. Nearly complete information about various event characteristics was collected from participants in 1,037 unique protests across the United States in 2010 to 2011. The first part of this article reviews extant methodologies in protest-event research and discusses how the NSPE overcomes their recognized limitations. Next, we detail how the NSPE was conducted and present descriptive statistics for a number of important event characteristics. The hypernetwork sample is then compared to newspaper reports of protests. As expected, we find many differences in the types of events these sources capture. At the same time, the overall number and magnitude of the differences are likely to be surprising. By contrast, little variation is observed in how protesters and journalists described features of the same events. NSPE data have many potential applications in the field of contentious politics and social movements, and several possibilities for future research are outlined.

Readers in social network analysis and organization studies will recognize the importance of this technique. As long as you can sample people, you can sample social ties and the adjust the sample for repetition. Peter Marsden used this technique to sample organizational networks. In movements research, my hybrids paper used the technique to sample orgs that were involved in movement mobilization. It’s great to see this technique expand to sample large samples of events.See Bayerlin’s research project website for more. Recommended.

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Appetite for Innovation: Creativity & Change at elBulli (To be published by Columbia University Press on July 12, 2016)

How is it possible for an organization to systematically enact changes in the larger system of which it is part? Using Ferran Adria’s iconic restaurant “elBulli” as an example of organizational creativity and radical innovation, Appetite for Innovation examines how Adria’s organization was able to systematically produce breakthroughs of knowledge within its field and, ultimately, to stabilize a new genre or paradigm in cuisine – the often called “experimental,” “molecular,” or “techno-emotional” culinary movement.

Recognized as the most influential restaurant in the world, elBulli has been at the forefront of the revolution that has inspired the gastronomic avant-garde worldwide. With a voracious appetite for innovation, year after year, Adrià and his team have broken through with new ingredients, combinations, culinary concepts and techniques that have transformed our way of understanding food and the development of creativity in haute cuisine.

Appetite for Innovation is an organizational study of the system of innovation behind Adrià’s successful organization. It reveals key mechanisms that explain the organization’s ability to continuously devise, implement and legitimate innovative ideas within its field and beyond. Based on exclusive access to meetings, observations, and interviews with renowned professionals of the contemporary gastronomic field, the book reveals how a culture for change was developed within the organization; how new communities were attracted to the organization’s work and helped to perpetuate its practice, and how the organization and its leader’s charisma and reputation were built and maintained over time. The book draws on examples from other fields, including art, science, music, theatre and literature to explore the research’s potential to inform practices of innovation and creativity in multiple kinds of organizations and industries.

The research for Appetite for Innovation was conducted when Adria’s organization was undergoing its most profound transformation, from a restaurant to a research center for innovation, “elBulli foundation”.  The book, therefore, takes advantage of this unique moment in time to retrace the story of a restaurant that became a legend and to explore underlying factors that led to its reinvention in 2011 into a seemingly unparalleled organizational model.

Appetite for Innovation is primarily intended to reach and be used by academic and professionals from the fields of innovation and organizations studies. It is also directed towards a non-specialist readership interested in the topics of innovation and creativity in general. In order to engage a wider audience and show the fascinating world of chefs and the inner-workings of high-end restaurants, the book is filled with photographs of dishes, creative processes and team’s dynamics within haute cuisine kitchens and culinary labs. It also includes numerous diagrams and graphs that illustrate the practices enacted by the elBulli organization to sustain innovation, and the networks of relationships that it developed over time. Each chapter opens with an iconic recipe created by elBulli as a way of illustrating the book’s central arguments and key turning points that enable the organization to gain a strategic position within its field and become successful.

To find a detailed description of the book please go to: http://cup.columbia.edu/book/appetite-for-innovation/9780231176781

Also, Forbes.com included Appetite for Innovation in its list of 17 books recommended for “creative leaders” to read this summer:  http://www.forbes.com/sites/berlinschoolofcreativeleadership/2016/05/15/17-summer-books-creative-leaders-can-read-at-the-beach/#7ac430985cef

 

the risky sex game paper – impact on current research

Yesterday, I described a paper written by Kirby Schroeder and my self on infection networks. Yesterday’s post addresses the professional lessons I learned. Today, I want to talk about the impact of the paper on current work. For a long time, the paper, literally, got zero citations in peer reviewed journals. Then, the citations increased around 2010, with people in economics, health, and biology discussing the paper.

Economics: The main commentary among economists is that this is a model of interaction, which can then be used to assess the impact of policy. For example, a paper in the American Law and Economics Review notes that the paper models risky behavior but does not model the law. Other economists are attracted to our prediction about infection knowledge and epidemic plateaus (once the disease becomes common knowledge, people shift behavior and transmission stalls).

Health: The Archives of Sexual Behavior has an article that discusses our article in the context of trying to expand models of disease transmission. For example, we critique the health belief model for ignoring interaction. We criticize sexual scripting theory for ignoring risk and strategic action.

Biology: Perhaps the most interesting impact of the paper is the impact on mathematical biology. In The Journal of Theoretical Biology, a team of mathematicians use the model to address group formation. In a model derived from our Risky Sex Game model, they show that the population, under certain conditions, will separate into specific groups based on HIV status.

Bottom line: People sure hated the paper when I wrote it, but its children are a joy to behold.

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the risky sex game paper – professional lessons

My first ever journal publication was an article called “A Game Theoretic Model of Sexually Transmitted Disease Epidemics.” It appeared in the journal Rationality and Society in 2002. As the title suggests, the goal of the paper is to model network diffusion using agents that play games with each other. Specifically, let’s assume people want to have sex with each other. The catch is that some people have HIV (or another disease) and some don’t. Further, let’s assume that people will estimate the probability that the partner has HIV based on the type of sex they offer and the current disease prevalence. In other words, offering unprotected sex in a world without STD’s is interpreted way differently than the same offer in a world where lots of people have infections. In this post, I want to briefly discuss what I learned by writing this paper. Tomorrow, I will talk about the small, but interesting, literature in biology and health economics that has referenced this paper.

Lesson #1: Interdisciplinary work doesn’t have to be garbage. The paper uses ideas from at least three different scholarly areas – game theory/economics; social networks/sociology; and probability theory/epidemiology. Orgtheory readers will be familiar with game theory and networks. But the paper uses a cool idea from probability theory called “pairs at a party model” – to model diffusion, you draw people from a pool and match them. I added these ideas: people can only be paired with people they know (the network) and then to decide if they have intercourse, they play a signalling game (game theory).

Lesson #2: Working with your buddies is amazing. My co-author on the project was Kirby Schroeder, who now works in the private sector. We developed the idea by thinking about his personal experience. Gay men often encounter the signaling problem – say you meet a partner and he offers unprotected sex. What does that suggest? We then joined forces to write the paper. Great experience.

Lesson #3: People can get angry at your research. During conferences and peer review, we experienced great hostility because we relied on the literature showing that sometimes, people don’t tell partners about STD’s and thus put them at risk. One woman, who claimed to be a researcher from Massachusetts General Hospital, literally yelled at me during an ASA session. The paper got rejected from Journal of Sex Research, after an R&R, because one reviewer got very upset and claimed that were defaming gay people and that “you don’t know what love means.” Do any of us, really?

Lesson #4: Long term matters. The paper was published in Rationality and Society and then quickly disappeared. But it had an interesting after life. It got an ASA grad student paper award from the Math Soc section. During the first couple of years on the job, it was the only journal publication on the CV, which saved me from complete embarrassment. In one review of my work, it was the *only* paper that the committee actually liked. Later, a member of the RWJ selection committee said that the paper was the only reason that they invited me for an interview, because it showed a genuine commitment to health research. Even better, starting around 2010, researchers rediscovered the paper and now it is part of a larger literature on sexual risk spanning biology, economics, and health. So even though it didn’t have an immediate impact, a well written paper can pay off in ways you might not expect.

Tomorrow: What people get from the Risky Sex Game paper.

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sexy orgtheory

Next week, we’ll discuss sex and sociology. Here are the topics:

• Why sex is important for sociologists to study
• My experience teaching social science research on sex
• Lessons from Laumann et al. (1994)
• Professional lessons from my first article on networks and STD’s
• The unexpected literature that sprung up from that article

If you want to discuss other topics, mention them in the comments and we’ll work it in.

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two paths to glory

Everyone wants to know the secrets to academic success. But despite the sizable academic self-help genre, actual evidence on whether scholars who pursue certain strategies are more successful than others is fairly thin on the ground.

Erin Leahey has written about the returns to research specialization, and I know of a couple of papers on the characteristics of highly cited scientists (gated links, sorry). There’s probably more in the voluminous scientometrics literature.

Some of our standard theories in organization theory suggest different answers to this question — and in particular, to the question of what research topic you should pick. (Assuming maximum academic success is your goal and not, say, following your passion.)

A whole line of research following from Ezra Zuckerman’s 1999 article on the penalty to category breaching suggests that not fitting into predefined categories can hurt a product. Audiences, for example, find genre-spanning work less appealing. On the flip side, though, Ron Burt’s work on structural holes would seem to imply that academics who bridge poorly connected networks are in a good position to benefit from their brokerage.

Of course, none of this work (at least the stuff I know) has looked specifically at academic research. But both theories fit plausible narratives of scholarly success.

It makes a lot of sense that people who bridge disconnected research communities would be in a position to bring useful ideas from one into the other, and reap the rewards that result. On the other hand, I can think of several examples of folks who seem to achieve less success than they merit because their work falls outside, or fits awkwardly between, well-defined research communities. A penalty to category-breaching or genre-spanning sounds entirely plausible too.

If I had to guess, I’d suspect that these two patterns may both exist in academia but intersect in fairly complex ways. So the network-broker can benefit from her ability to borrow insights from another discipline, or community. But only if the insights are recognizable enough to her home discipline that others can mentally place those insights in an understandable location within their field — that is, in an existing category.

The question is whether there’s a sweet spot — being just enough of a broker to benefit, without being so radical as to trigger a category-breaching penalty. Or maybe there’s a benefit to brokerage, but only in certain structural holes — ones that don’t cause the category problem. Or maybe there are a couple of mutually exclusive strategies for success.

What do you think? Will academic brokers be hit with an illegitimacy penalty for their category breaching? Or are these in fact orthogonal issues for ambitious academics? Maybe there’s actual research that speaks to this.

(H/T to Tim Bartley for the conversation that spurred these musings.)

measles, HIV, brendan nyhan, and an obscure paper I wrote in 2002

Vox has a nice interview with Dartmouth political scientist Brendan Nyhan about vaccine skeptics. What can be done to convince them? Brendan does research on political beliefs and has shown that in experimental settings, people don’t like to change beliefs even when confronted with correct information. His experiments show that this is true not only for political beliefs, but also controversial health beliefs like believing in the vaccine-autism link.

But there was an additional section in the interview that I found extremely interesting. Nyhan notes that it is easier to be a vaccine skeptic when you don’t actually see a lot of disease: “… many of the diseases that vaccines prevent today are essentially invisible in the US. Vaccines are a victim of their own success here.” This reminded me of a 2002 paper I wrote on STD/HIV transmission. In a model worked out by Kirby Schroeder and myself about people proposing to have risky sex with each other, we wrote that the model has an unusual prediction. If people are proposing risky sex based on how often their friends are infected, you may get unexpected outbreaks of disease:

In the models we have presented, there is no replacement; the population is stable. If we allow for replacement, then we arrive at a novel prediction: as uninfected individuals the population (through birth, migration, etc.) and HIV+ individuals leave (through illness), the proportion of infected individuals will decrease. Once this proportion falls, prior beliefs about the proportion of infected individuals will fall, and if this new prior belief is low enough , then HIV- negative individuals will switch from protected to unprotected sex. The long-term effect of replacement in our model, then, is an oscillation of infection rates… There is some evidence that oscillations in infection rates do occur… An intriguing avenue for research would be to link these patterns in infection rates to the behavior depicted in our model.

In other words, if your model of the world assumes that people take risk based on the infection rates of their buddies, then it is entirely possible, even predictable, that you will see sudden spikes or outbreaks because people “let their guard down.” For HIV, as more people use condoms and other measures, people may engage in more risky sex because few of their friends are infected. For measles and other childhood infections, people who live in very safe places may feel free to deviate from the standard practices that create that safety in their first place. I don’t know how to make vaccine skeptics change their minds, but I do know that movements like vaccine skepticism are some what predictable and we can prepare for it.

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abortion secrets in sociological science

Sociological Science has a new paper by Sara Cowan discusses when people share information using data on abortion:

Though abortion is a more common event in the United States than miscarriage, this article shows that more Americans hear of women who have had miscarriages than they hear of women who have had abortions. This is a result of both the patterns of secret telling and keeping: more Americans tell miscarriage secrets to more people than abortion secrets, and more Americans keep abortion secrets from more people than  miscarriage secrets.

In the introduction, I described two scenarios: one in which people tend to hear secrets they previously approved, and this pattern would contribute to a stasis in public opinion and a second scenario in which people hear secrets they previously condemned and this scenario would inspire social influence and facilitate social change. The data analyzed here illustrate the first scenario. They show a strong trend whereby individuals who hold restrictive views toward abortion are less likely than their liberal peers to report knowing someone who has had one. People tend to hear those secrets about which they already approve and are less likely to hear secrets about which they disapprove. Secret keeping and selective disclosure intensify this experience of homophily above and beyond any objective network segregation.

Check it out.

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this is not a post about ello

This is not a post about Ello. Because Ello is so last Friday. But the rapid rise of and backlash against upstart social media network Ello (if you haven’t been paying attention, see here, here, here) reminded me of something I was wondering a while back.

Lots of people are dissatisfied with Facebook — ad-heavy, curated in a way the user has little control over, privacy-poor. And it looks like Twitter, which really needs bring in more revenue, is taking steps to move in the same direction: algorithmic display of tweets, with the ultimate goal of making users more valuable to advertisers.

The question is, what’s the alternative? There have been a lot of social network flavors of the month, built on a variety of business models. Some of them, like Google Plus, are owned by already-large companies that would be subject to similar business pressures as Facebook and Twitter. Others, like Diaspora (remember Diaspora?), were startups with an anti-Facebook mission (privacy, decentralization), but collapsed under the weight of their own hype.

I can’t imagine that a public utility model would work for a social network — I just don’t see “government-owned” and “fast-moving technological change” going together successfully. But I keep wondering why a Wikipedia model couldn’t work. Make it a 501(c)3. Attract some foundation funding — it’s a pro-democracy project. Solicit gifts from pro-privacy people in the tech industry — there are lots of those. Then once it’s off the ground, ask users for donations.

Sure, there is the huge, huge hurdle of getting enough of a network base to attract new users. But it seems like the costs should not be insane. If it only takes 200 employees to run Wikipedia, as large as it is, how many would it take to get a big social network off the ground? Facebook employs 7000, but a lot of them have to be in the business of figuring out how to sell Facebook.

Maybe there have been (failed) efforts like this and I just haven’t noticed. Or maybe the getting-the-user-base issue is really insurmountable. But it seems like if a real Facebook alternative is to emerge, it can’t just be from a corporate competitor (e.g. Google), and the startup/VC model (e.g. Ello) is going to be susceptible to all the same problems as it grows. Why not a different model?

book announcement: party in the street – the antiwar movement and the democratic party after 9/11

It is my pleasure to announce the forthcoming publication of a book by Michael Heaney and myself. It is called Party in the Street: The Antiwar Movement and the Democratic Party after 9/11. It will be available from Cambridge University Press starting in early 2015.

The book is an in-depth examination of the relationship between the major social movement of the early 2000s and the Democratic Party. We begin with a puzzle. In 2006, the antiwar movement began to decline, a time when the US government escalated the war and at least five years before US combat troops completely left Iraq. Normally, one would expect that an escalation of war and favorable public opinion would lead to heightened  activism. Instead, we see the reverse.

We answer this question with a theory of movement-party intersections – the “Party in the Street.” Inspired by modern intersectionality scholarship, we argue that people embody multiple identities that can reinforce, or undermine, each other. In American politics, people can approach a policy issue as an activist or a partisan. We argue that the antiwar movement demobilized not because of an abrupt change in policy, but because partisan identities trumped movement identities. The demobilization of the antiwar movement was triggered, and concurrent with, Democratic victories in Congress and the White House. When push comes to shove, party politics trumps movement activism.

The book is the culmination of ten years of field work, starting with a survey of antiwar protesters at the Republican National Convention in August 2004. The book examines street protest, public opinion, antiwar legislation, and Iraq war policy to makes its case. If you are interested in American politics, political parties, peace studies, political organizations, or social movements, please check this book out. During the fall, I’ll write a series of posts that will explain the argument in some more detail.

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on facebook and research methods

Twitter is, well, a-twitter with people worked up about the Facebook study. If you haven’t been paying attention, FB tested whether they could affect people’s status updates by showing 700,000 folks either “happier” or “sadder” updates for a week in January 2012. This did indeed cause users to post more happy or sad updates themselves. In addition, if FB showed fewer emotional posts (in either direction), people reduced their posting frequency. (PNAS article here, Atlantic summary here.)

What most people seem to be upset about (beyond a subset who are arguing about the adequacy of FB’s methods for identifying happy and sad posts) is the idea that FB could experiment on them without their knowledge. One person wondered whether FB’s IRB (apparently it was IRB approved — is that an internal process?) considered its effects on depressed people, for example.

While I agree that the whole idea is creepy, I had two reactions to this that seemed to differ from most.

1) Facebook is advertising! Use it, don’t use it, but the entire purpose of advertising is to manipulate your emotional state. People seem to have expectations that FB should show content “neutrally,” but I think it is entirely in keeping with the overall product: FB experiments with what it shows you in order to understand how you will react. That is how they stay in business. (Well, that and crazy Silicon Valley valuation dynamics.)

2) This is the least of it. I read a great post the other day at Microsoft Research’s Social Media Collective Blog (here) about all the weird and misleading things FB does (and social media algorithms do more generally) to identify what kinds of content to show you and market you to advertisers. To pick one example: if you “like” one thing from a source, you are considered to “like” all future content from that source, and your friends will be shown ads that list you as “liking” it. One result is dead people “liking” current news stories.

My husband, who spent 12 years working in advertising, pointed out that this research doesn’t even help FB directly, as you could imagine people responding better to ads when they’re happy or when they’re sad. And that the thing FB really needs to do to attract advertisers is avoid pissing off its user base. So, whoops.

Anyway, this raises interesting questions for people interested in using big data to answer sociological questions, particularly using some kind of experimental intervention. Does signing a user agreement when you create an account really constitute informed consent? And do companies that create platforms that are broadly adopted (and which become almost obligatory to use) have ethical obligations in the conduct of research that go beyond what we would expect from, say, market research firms? We’re entering a brave new world here.

when hybrid organizational identities can help attract supporters – AJS paper by Heaney and Rojas now available online

How can social movements gain supporters?  According to Michael T. Heaney and Fabio Rojas‘s hot-off-the-virtual-press Jan. 2014 AJS paper “Hybrid Activism: Social Movement Mobilization in a Multimovement Environment,” one way that social movement organizations can appeal to prospective members is to use a hybrid identity that can attracts individuals from a variety of social movement interests. While prior studies have argued that hybrid organizations are penalized by an “illegitimacy discount” for not having a clear identity, the authors argue that boundary-crossing works for some contexts such as social movements.

Here’s the abstract:

Social movement organizations often struggle to mobilize supporters
from allied movements in their efforts to achieve critical mass. The
authors argue that organizations with hybrid identities—those whose
organizational identities span the boundaries of two or more social
movements, issues, or identities—are vital to mobilizing these constituencies.
They use original data from their study of the post-9/11 U.S.
antiwar movement to show that individuals with past involvement in
nonantiwar movements are more likely to join hybrid organizations
than are individuals without involvement in nonantiwar movements.
In addition, they show that organizations with hybrid identities occupy
relatively more central positions in interorganizational cocontact networks within
the antiwarmovement and thus recruit significantly more
participants in demonstrations than do nonhybrid organizations. Contrary
to earlier research, they do not find that hybrid organizations are
subject to an illegitimacy discount; instead, they find that hybridization
can augment the ability of social movement organizations to mobilize
their supporters in multimovement environments.

Kudos to the authors for wearing-out-the-shoe (p)leather: Using survey data collected from antiwar movement demonstrators in several major US cities between 2007-2009, the authors identified which organizations protestors belonged to, and which organizations had recruited them to these demonstrations.  After collecting online information about these organizations’ missions, a team of coders (followed by another team of coders for inter-rater reliability) then identified these organizations as belonging to one or more of 11 non–mutually exclusive categories: antiwar, peace, peace church, social justice, personal identity, partisan or ideological, education related, religious, environmental, labor union or labor related, and other.  Using these categories, the authors identified organizations as hybrids if they spanned categories.  As a validity check on this coding of organizational identities, the authors subsequently conducted interviews with organizational leaders.

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university of chicago visit – everything you wanted to know about tweets and votes, but were afraid to ask

I will be a guest of the computational social science workshop at the University of Chicago this coming Friday. I will present a very detailed talk on the more tweets/more votes phenomena called “Everything You Wanted to Know About the Tweets-Votes Correlation, but Were Afraid to Ask.” If you want to chat or hang out, please email me.

Refreshments will be served.

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comments on andrew gelman’s dec 21 post

Last Saturday, Andrew Gelman responded to a post about a discussion in my social network analysis course. In that post, my student asked about different strengths of a network effect reported in a paper. Gelman (and Cosima Shalizi) both noted that the paper does not show a statistically significant difference. I quote the concluding paragraphs of Andrew’s commentary:

I’m doing this all not to rag on Rojas, who, after all, did nothing more than repeat an interesting conversation he had with a curious student. This is just a good opportunity to bring up an issue that occurs a lot in social science: lots of theorizing to explain natural fluctuations that occur in a random sample. (For some infamous examples, see here and here.) The point here is not that some anonymous student made a mistake but rather that this is a mistake that gets made by researchers, journalists, and the general public all the time.

I have no problem with speculation and theory. Just remember that if, as is here, the data are equivocal, that it would be just as valuable to give explanations that go in the opposite direction. The data here are completely consistent with the alternative hypothesis that people follow their spouses more than their friends when it comes to obesity.

Fair enough. Let me add a pedagogical perspective. When I teach network science to undergrads, I generally have a few goals. First, I want to show them how to convert social tie data into a matrix that can be analyzed. Second, I want students to learn how network concepts might operationalize social science concepts (e.g., how group cohesion might be described as high density).  Third, I want to spark their imagination a little and see how network analysis can be used to describe or analyze a wide range of phenomena and thus encourage students to generate explanations. Given that students have very, very modest math skills and real problems generating hypotheses,  getting down into the weeds with the papers is often last.

So when I teach the week on networks and health, my discussion questions are like this: “Why do you think health might be transmitted from one person to another? How would that work?” I also try to get into basic research design: “How do you measure health? Do you know what BMI is?” So the C&F paper has many up sides. The downside is that the paper has an interesting hypotheses and you can easily get distracted from the methodological controversy the paper has generated, or even some very sensible observations on confidence intervals. The bottom line is that when you have to teach everything (theory, methods, research design and topic), you don’t quite get everything. But still, if a student, who self-admitedly knows little math or stats, can get to a point about asking about mechanisms, then that’s a teaching victory.

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friends vs. spouses in influence

After reading the Fowler/Christakis paper on networks and obesity, a student asked why it was that friends had a stronger influence on spouses. In other words, if we believe the F&C paper, they report that your friends (57%) are more likely to transmit obesity than your spouse (37%) (see page 370).

This might be interpreted in two ways. First, it might be seen as a counter argument. This might really indicate that homophily is at work. We probably select spouses for some traits that are not self-similar. While we choose friends mainly on self-similarity of leisure and consumption (e.g, diet and exercise). Second, there might be an explanation based on transmission. We choose friends because we want them to influence us, while spouses are (supposed?) to accept us.

Your thoughts?

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mean girls, part deux

“There’s a literature on everything.” – Tyler Cowen

Yup, it turns out that not only is there is a network analysis literature on mean girls, but it has been published in the ASR. I quote from an article by Bob Faris and Diane Felmlee called “Status Struggles: Network Centrality and Gender Segregation in Same- and Cross-Gender Aggression:”

Literature on aggression often suggests that individual deficiencies, such as social incompetence, psychological difficulties, or troublesome home environments, are responsible for aggressive behavior. In this article, by contrast, we examine aggression from a social network perspective, arguing that social network centrality, our primary measure of peer status, increases the capacity for aggression and that competition to gain or maintain status motivates its use. We test these arguments using a unique longitudinal dataset that enables separate consideration of same- and cross-gender aggression. We find that aggression is generally not a maladjusted reaction typical of the socially marginal; instead, aggression is intrinsic to status and escalates with increases in peer status until the pinnacle of the social hierarchy is attained. Over time, individuals at the very bottom and those at the very top of a hierarchy become the least aggressive youth. We also find that aggression is influenced not so much by individual gender differences as by relationships with the other gender and patterns of gender segregation at school. When cross-gender interactions are plentiful, aggression is diminished. Yet these factors are also jointly implicated in peer status: in schools where cross-gender interactions are rare, cross-gender friendships create status distinctions that magnify the consequences of network centrality.

Highly recommended.

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network analysis vs. public choice

I just wrapped up my undergrad course in networks for seniors. Near the end, in the week on networks and crime, we discussed Papachristos’ work on homicide in Chicago. If you haven’t read it, he has a very rich data set on gangs and traces the back and forth of gang revenge homicides. Great stuff. So I asked my students: “You are the police and now you have read this research, what did you learn?”

Student 1: You should target the most central gangs. They seem to generate a lot of violence.

Me: Good, what else?

Student 1: Since a lot seems to focus on revenge, maybe police should focus on friends of homicide victims. Maybe counsel them so they won’t get revenge and keep the cycle going.

Student 2: That would never work.

Me: Why?

Student 2: The cops gets no credit for counseling. Only for arrests.

Bingo. Great insight. In other words, we have a lot of good data on homicides and we know that a lot of it has to do with gang/revenge cycles. And that implies a solution – go after survivors and do what you can to keep them from acting out. But it is very hard to see how anyone could ever be rewarded in the system where people get promoted for arrests rather than crime prevention. It’s sad that you need have someone murdered first before you can be praised for being a good cop.

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more tweets, more votes: in foreign policy, PLoS One, and hitting the top 10 list

More Tweets, More Votes news:

1. I thank Alex Hanna for mentioning this work in a new Foreign Policy piece that discusses how social media can be used to monitor elections in nations where polling is rare, a possibility that I mentioned in my Washington Post article on MTMV. Alex and co-author Kevin Harris use social media data to track Iranian public opinion, because quality polling is not common there. A must read for people who want to see how social media can be used to measure and evaluate democratic processes.
2. The peer reviewed version of MTMV is now out in PLoS One. The paper presents the tweet share/vote share correlation for the 2010 and 2012 House elections and discusses possible mechanisms.
3. The working paper version of MTMV at Social Science Research Network has had over 1,200 downloads in its short life, pushing it into the top 10 most downloaded papers on models of elections and political processes at SSRN. Congratulations to my co-authors Joe DiGrazia, Karissa McKelvey, and Johan Bollen. Outstanding work.

Insider tip: New results be presented at the computational social science workshop at the University of Chicago in January 2014. Details forthcoming.

These books cure baldness: From Black Power/Grad Skool Rulz

enlightenment era networks

From “Brain Pickings.”

Two Turntables and Awesome Sauce: From Black Power/Grad Skool Rulz

mentors vs. sponsors in labor markets

A lot of sociologists buy into the theory of “sponsored mobility,” which means that elites pick who gets the mobility. So I think there should be a lot of sympathy for  recent research showing that mentorship (communicating with more advanced people) does not have an effect on career advancement but sponsors (people who pick you, push you, and get benefit from it) do have an effect. Robin Hanson reviews a book by economist Sylvia Ann Hewett that makes this claim:

In a new book, economist Sylvia Ann Hewlett uses data to show that mentorship, in its classic wise-elder-advises-younger-employee form, doesn’t produce statistically significant career gains. What does however, her research found, is something she has termed “sponsorship”—a type of strategic workplace partnering between those with potential and those with power. … –

And there is an important implication for the study of gender and inequality:

Women are only half as likely as men to have a sponsor—a senior champion at work who will basically take a bet on them, tap them on the shoulder, and really give them a shot at leadership. Women have always had mentors, friendly figures who give lots of advice. They’re great. They’re good for your self-esteem; they’re good for your personal development. But no one’s ever been able to show that they do anything to help you actually move up. …

We find that women in particular often choose the wrong people. … They seek out a senior person they’re very comfortable with. … For a sponsor, you should go after the person with power, because you need someone who has a voice at those decision-making tables. You need to respect that person, you need to believe that person is a fabulous leader and going places, but you don’t need to like them. You don’t need to want to emulate them.

If true, this forces me to modify my views. I have always believed that sponsored mobility is important in academia, but I believe that mentorship matters as well. If Hewett is right, my belief is misplaced. It’s really about sponsored mobility. So, if you care about women or minorities advancing in some career track (like academia), then forget the nice lunches. Administrators should double down on matching people with power players. A bit rude, but it might be one concrete way to chip away at inequality in the leadership of the academy.

Texts for the Ages: From Black Power/Grad Skool Rulz

incumbents, transparency, and social media data

At last week’s PLEAD conference on social media and political processes, Alex Hanna tweeted a summary of a talk by Mark Huberty of UC Berkeley political science, which raised some questions about using social media data to forecast electoral results. Alex suggested that we could have a good discussion about Mark’s talk. In these comments, I rely on Alex’s summary. If I mis-characterized a point, please email me or correct me in the comments.

1. Huberty noted, correctly, that incumbency highly correlates with electoral wins. The implication is that social media data is not valuable, or important, or accurate, because incumbency accounts for a lot of the variance in electoral outcomes.

Well, it depends on what your goals are. If you are making a claim that “A causes B”, then finding out that C account for much of the variance is extremely important. It shows that A isn’t causing B. However, if your claim is that “A is a decent measurement of B,” then finding out that C is a strong correlate of B is simply irrelevant.  The claim isn’t about what is some fundamental cause of B, just what tracks with B.

Different claim, different standard of proof. That’s we care about polls. Incumbency predicts elections better than polls, but as long as we don’t claim that polls cause election outcomes, we remain satisfied with the well documented correlation between voter surveys and final votes.

Also, incumbency is not a reasonable variable to benchmark against because incumbency is simply a word for “the person who won last time in the same election with a very similar group of voters.” As good social scientists know, a lot of human behavior is seriously auto-correlated. What I ate yesterday is the best predictor of what I’ll eat tomorrow. Politics is no different.

Thus, in a lot of social science, we aren’t interested in these sorts of time series because we know that answer already. X_t is almost certainly strongly correlated with X_t-1. The interesting question is why the time series is X_1, X2,… and not Y_1, Y_2, … Similarly, we might interested in “extracting a signal” from some new source of data to help us measure X_i or build a causal explanation that doesn’t fall back on trivial auto-correlated time series explanations. In other words, “The guy is an incumbent because there are a lot Black voters” is a much more meaningful statement than “The guy won this time because he won last time.”

That is ultimately why I remain interested in social media and electoral outcomes. Social media is a record of what people think that is different  than polls and traditional print or broadcast media. It deserves a serious examination as a signal. And given the work by Huberty himself, Tusmajan, Juengher, Beuchamp, the Indiana group, and others, the “social media as measurement of political sentiment” hypothesis is important and, as far as I can tell, supported to varying degrees by the Twitter data. Incumbency is a non-issue as long as researchers and political professionals avoid claims of causation.

2. Alex also indicated that Mark Huberty was concerned about how social media data is created. Here, I also agree. Transparency is important.  All data is imperfect – people lie on polls, surveys has selection biases, etc. There is a discussion about the properties of the samples that Twitter produces for researchers that might lead one to think that there might be an issue. The more we know about the way social media samples are generated, the better.

Still, the issue is *how much* of a problem this is.  On this point, I urge Mr. Huberty to be bluntly empirical.The blunt empiricist, I would argue, would just put it to the test. The empiricist would look for natural experiments in the data (transparent data vs. others) or well chosen comparisons to see how much it affects the social media-vote correlation. Rather than point to possible problems, research would actually identify them. It might not matter, or it might be a big deal. Let’s figure it out!

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mean girl sociology

In my undergraduate social network class, I tried to explain how social network analysis could be used to identify a certain “type” of person. I often use high schools as an example. One could ask students to identify friends and then use that data to map groups, cliques, and the like. At one point in the discussion, I then said, “for example, we could use network data to discover the most popular people, the MEAN GIRLS.” I then asked, “how would we discover mean girls?”

In our discussion, I think we settled on the following:

• Mean girls would have high centrality scores.
• With asymmetrical friendship network data, mean girls would not reciprocate.
• If people rated the content of the network tie, mean girls would receive a lot positives but send out negatives.
• Mean girls would cluster, or have structurally equivalent roles.

A student asked, “Fabio, were you a mean girl in high school?”

I said, “probably not, I was very shy and I rarely taunted kids or got in fights. In some ways, though, I am a mean nerd.”

The student responded, “Fabio, you are definitely a mean nerd. I read what you wrote about the critical realists.”

Do-oooh!!!

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recent work on social networks and politics

My dear friend and collaborator Michael T. Heaney has some new work that will be of interest to many readers. In the journal Social Networks, he has an article called Multiplex networks and interest group influence reputation: An exponential random graph model:

Interest groups struggle to build reputations as influential actors in the policy process and to discern the influence exercised by others. This study conceptualizes influence reputation as a relational variable that varies locally throughout a network. Drawing upon interviews with 168 interest group representatives in the United States health policy domain, this research examines the effects of multiplex networks of communication, coalitions, and issues on influence reputation. Using an exponential random graph model (ERGM), the analysis demonstrates that multiple roles of confidant, collaborator, and issue advocate affect how group representatives understand the influence of those with whom they are tied, after accounting for homophily among interest groups.

In the journal Interest Groups and Advocacy, he has a forthcoming article: Coalition Portfolios and Interest Group Influence Over the Policy Process, with Goeff Lorenz.

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use twitter, make money fa$t

My colleague at Indiana University, Johan Bollen has patented an algorithm that allows him to link Twitter traffic to stock price fluctuations. Click on the link for the TV news item. A clip from the report:

An IU professor and researcher just received a patent for software that crunches hundreds of millions of tweets, to predict where the stock market is headed…

Think of this way: The thoughts of two or three million people probably don’t add up to much, but if you multiply that by tens or hundreds of millions of people, then you may have something.

“We find that when people get more anxious, then there is a great likelihood of the market dropping 3-4 days later and vice versa,” Bollen said.

Definitely check it out.

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it’s official – facebook is a waste of time

Recent research has shown a change in Facebook use. While users tend to retain accounts, people are now reducing their use of the website. The reasons? From a recent NY Times survey of Facebook users:

The main reasons for their social media sabbaticals were not having enough time to dedicate to pruning their profiles, an overall decrease in their interest in the site, and the general sentiment that Facebook was a major waste of time.

This may indicate that we’ve hit “peak Facebook,” in terms of the site’s popularity level. It’s now a standard tool for networking, but the novelty has worn off. People don’t feel the obligation to use it. Now, the main users will be people who really enjoy networking – young people, businesses/orgs and extroverted people. Still, a huge market, but far short of the all encompassing vision of some. Probably the time to dig deep into that “platform” strategy we were talking about.

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emergence of organizations and markets, part I by padgett & powell

A guest post by John Padgett and Woody Powell about their new book The Emergence of Organizations and Markets:

Innovation in the sense of product design is a popular research topic today, because there is a lot of money in that. Innovation, however, in the deeper sense of new actors—new types of people, new organizational forms—is not even much on the research radar screen of contemporary social scientists, even though “speciation” (to use the biologists’ term for this) lies at the heart of historical change over the longue durée, both in biological evolution and in human history. Social science—meaning mostly economics, political science and sociology—is very good at understanding selection, both at the micro level of individual choice and at the macro level of institutional regulation and lock-in. But novelty, especially of actors but also of alternatives, has first to enter from off the stage of our collective imaginary for our existing theories to be able to go to work. Our analytical shears for trimming are sharp, but the life forces that push up novelty to be trimmed tend to escape our attention, much less our understanding. If this book accomplishes anything, we at least hope to put the research topic of speciation—the emergence of new organizational forms and people—on our collective agenda.

february guest bloggers: john padgett and woody powell

It is my pleasure to announce our February guest bloggers: Woody Powell and John Padgett. Professor Powell is Professor of Education and (by courtesy) Sociology, Organizational Behavior, Management Science and Engineering, Communication, and Public Policy at Stanford University. Professor Padgett is Professor of Political Science at the University of Chicago.

Woody and John are both leading figures in the study of organizations and networks. Professor Powell is co-author, with Paul DiMaggio, of the groundbreaking “iron cage” article and then went on to publish a series of highly influential papers in social network analysis. John Padgett is one of political science’s leading formal modellers, having written seminal papers on budgeting & garbage can processes, the courts, and state formation. His most well known work is likely the “Medici paper,” which used network analysis to describe the cultivation of political power in early modern Italy and introduced the idea of “robust action” into modern social theory.

They will be discussing their new book: The Emergence of Organizations and Markets. Here’s a summary:

The social sciences are rich with ideas about how choice occurs among alternatives, but have little to say about the invention of new alternatives in the first place.  These authors directly address the question of emergence, both of what we choose and who we are.  With the use of sophisticated deductive models building on the concept of autocatalysis from biochemistry and rich historical cases studies spanning seven centuries, Padgett and Powell develop a theory of the co-evolution of social networks.  Novelty in new persons and new organizational forms emerges from spillovers across multiple, intertwined networks.  To be sure, actors make relations; but the mantra of this book is that in the long run relations make actors.  Through case studies of early capitalism and state formation, communist economic reforms and transition, and technologically advanced capitalism and science, the authors analyze speciation in the context of organizational novelty.  Drawing on ideas from both the physical sciences and the social sciences, and incorporating novel computational, historical, and network analyses, this book offers a genuinely new approach to the question of emergence.

This week and next week, I’ll post some thoughts that John and Woody have shared with me. This is *required* reading for sociologists, management scholars, political scientists, and economists. And yes, there, will be a quiz!

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is network analysis stuck?

Here’s how I view the history of social network analysis:

• Pre-history – Simmel (1900s) to Moreno (1930s): People start thinking about the “geometry” of social relationships.
• Network science 1.0 – Harary, Heider, Freeman, etc. (1950s – 1970s): People learn to convert relational data into matrix algebra.
• The holistic turn (1970s – 1980s): People start inventing measures of network structure (Bonacich, White).
• Statistical theory of networks (1970s-2000s):  The creation of P* models, and later dynamic network models, to account for non-independence.
• Socio-physics networks (2000s): Watts, Barbasi, and others from physics work on large scale properties of networks (e.g., power laws or small worlds).

So, by my account, the last major development in network analysis was about 10 years ago. Now, this isn’t to say that there isn’t excellent work, but it is normal science. Pick up a copy of Social Networks, or Network Science. You’ll see great articles, but they are usually investigating specific networks, or figuring out the details of some specific. Am I missing the next generation of network analysis? One possibility is that there will be new ideas coming from people doing experiments on networks for estimate causal effects. Other areas?

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friendship bleg

Someone asked me: what is the go to source on when people make friends during the life course?

Read these books backwards: From Black Power/Grad Skool Rulz

recent social networks

A few recent articles from the journal Social Networks:

• Parigi and Sartori discuss party networks and cleavages in Italy.
• Networks and soccer team wins by Grund.
• Crossley, Edwards, Harries, and Stevenson discuss the trade off between efficacy and secrecy in movement networks.
• Amicus curiae (“friends of the court” briefing) networks by Box-Steffensmeir and Christensen

The recent article page is here.

Crazy good books: From Black Power/Grad Skool Rulz

political networks in american behavioral scientist

My collaborator, Michael Heaney, has a nice article in the new American Behavioral Scientist where he measures polarization in party networks:

Previous research has documented that the institutional behaviors (e.g., lobbying,  campaign contributions) of political organizations reflect the polarization of these organizations along party lines. However, little is known about how these groups are connected at the level of individual party activists. Using data from a survey of 738 delegates at the 2008 Democratic and Republican national conventions, we use network regression analysis to demonstrate that co-membership networks of national party convention delegates are highly polarized by party, even after controlling for homophily due to ideology, sex/gender, race/ethnicity, age, educational attainment, income, and religious participation. Among delegates belonging to the same organization, only 1.78% of these co-memberships between delegates crossed party lines, and only 2.74% of the ties between organizations sharing common delegates were bipartisan in nature. We argue that segregation of organizational ties on the basis of party adds to the difficulty of finding common political ground between the parties.

Good for those interested in the growing literature on networks in political science.

Every library needs these books: From Black Power/Grad Skool Rulz

abstract art networks

The art website Hyperallergic has a nifty new diagram illustrating the networks of artists responsible for abstract expressionism.

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Facebook field experiment shows strong ties affect voter turnout

The most recent Nature features an article by a team of political scientists and network scholars who did an experiment using Facebook to show that strong ties influenced voting behavior in the last election. You may say, so what? We’ve known for a long time that social influence operates through strong ties in interpersonal networks. That’s not a new insight.  But I think the study is innovative for a couple of reasons. The first is that the impact of of using direct messaging through Facebook was substantively significant  – that is, just messaging people reminders to go out and vote increased the likelihood that the person would vote – but that the larger effect was transmitted indirectly via social contagion. Consider the setup of the experiment.