Archive for the ‘networks’ Category

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.

Written by epopp

June 29, 2014 at 3:00 am

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.

Check out a preview here.

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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Written by fabiorojas

January 13, 2014 at 3:56 am

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.

Post-Christmas blow out: From Black Power/Grad Skool Rulz 

Written by fabiorojas

December 26, 2013 at 12:18 am

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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Written by fabiorojas

December 20, 2013 at 12:01 am

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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Written by fabiorojas

December 18, 2013 at 12:01 am

Posted in education, fabio, networks

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.

If people buy $500 of my books by Christmas, I will leave David Graeber alone: From Black Power/Grad Skool Rulz

Written by fabiorojas

December 17, 2013 at 12:10 am

Posted in fabio, networks, sociology

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

Written by fabiorojas

December 16, 2013 at 12:01 am

enlightenment era networks

From “Brain Pickings.”

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

Written by fabiorojas

November 23, 2013 at 12:01 am

Posted in fabio, networks

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

Written by fabiorojas

November 18, 2013 at 3:47 am

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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Written by fabiorojas

November 5, 2013 at 12:01 am

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.”


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Written by fabiorojas

October 15, 2013 at 12:01 am

Posted in education, fabio, networks

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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Written by fabiorojas

August 7, 2013 at 4:53 am

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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Written by fabiorojas

March 3, 2013 at 12:03 am

Posted in education, fabio, networks

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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Written by fabiorojas

February 18, 2013 at 3:31 am

Posted in fabio, markets, networks

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.

Read the rest of this entry »

Written by fabiorojas

February 7, 2013 at 12:01 am

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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Written by fabiorojas

February 5, 2013 at 12:01 am

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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Written by fabiorojas

January 14, 2013 at 12:01 am

Posted in fabio, networks

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

Written by fabiorojas

December 7, 2012 at 6:13 pm

recent social networks

A few recent articles from the journal Social Networks:

The recent article page is here.

Crazy good books: From Black Power/Grad Skool Rulz

Written by fabiorojas

November 18, 2012 at 12:01 am

Posted in fabio, networks

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

Written by fabiorojas

November 12, 2012 at 12:42 am

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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Written by fabiorojas

October 2, 2012 at 12:01 am

Posted in culture, fabio, networks

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.

Read the rest of this entry »

Written by brayden king

September 13, 2012 at 3:03 pm

america is not getting lonelier

A key empirical question in social network analysis is whether Americans have more or less friends over time. Famously, Robert Putnam argued that indeed, we were “bowling alone.” In contrast, critics contend that these are misinterpreted results. Some types of networks disappear, while other appear.

On the social network listserv, Claude Fischer provides the latest round in the debate. Fischer uses 2010 GSS data to claim that the decline in strong personal relationships reported by McPhereson et al. (2006 in the ASR) is due to survey question construction. I’ll quote Fischer’s entire announcement: Read the rest of this entry »

Written by fabiorojas

September 3, 2012 at 2:55 am

The “Old” New Institutionalism versus the “New” New Institutionalism

I signed on to blog on Orgtheory a couple of months ago with the express purpose of writing about “A Theory of Fields” (Oxford Press, 2012), my new book with Doug McAdam. So here it goes.

Today I want to explain something about the shape of research in organizational theory for the past 35 years ago in order to situate “A Theory of Fields” in that research. The cornerstones of the “new institutionalism” in organizational theory are three works, the Meyer and Rowan paper (1977), the DiMaggio and Powell paper (1983), and the book edited by Powell and DiMaggio (1991).

I would like to take the provocative position that since about 1990, most scholars have given up on the original formulation of the new institutionalism even though they are ritually fixated on citing these canonical works. It is worth thinking why they found that formulation limited.

The Meyer/Rowan and DiMaggio/Powell position on organizations is that actors in organizations do not have interests and that their actions are “programmed” by scripts. Moreover, actors are unable to figure out what to do, so they either follow the leader (i.e. mimic those they perceive as successful), act according to norms often propagated by professionals, or else find themselves coerced by state authorities. The Meyer/Rowan and DiMaggio/Powell world was not only void of actors; it was also void of change. Once such an order got into place, it became taken for granted and difficult to dislodge. “People” in this world told themselves stories, used myth and ceremony, and they decoupled their stories from what they were doing. This meant that the consequences of their actions were not important.  DiMaggio recognized this problem in 1988 when he suggested that in order to explain change we needed another theory one that involved actors, interests, power, and what he called “institutional entrepreneurs”.

The core of organizational studies since the early 1990s has been to reintroduce interests, actors, power and the problem of change into the center of organizational studies. Indeed, the field of entrepreneurship in management studies is probably at the moment, the hottest part of organizational theory. If one looks at these papers, one still sees ritual citing of DiMaggio/Powell and Meyer/Rowan. But the core ideas of these papers could not be farther from those works. The focus on entrepreneurial studies is on how new fields are like social movements. They come into existence during crises. They invoke the concept of institutional entrepreneurs who build the space and create new cultural frames, interests and identities. In doing so, the entrepreneurs build political coalitions to dominate the new order. Indeed, the gist of the past 15 years of organizational research is entirely antithetical to the “old” new institutionalism.

I submit to you that the time is now right to reject the “old” new institutionalism” entirely, free our minds, and produce a “new” new institutionalism.

Read the rest of this entry »

Written by fligstein

August 23, 2012 at 9:19 pm

hey, it’s scale free and … and …

A focus of network research since, say 1999 or so, has been to identify “laws” that generate large networks with certain properties.* For example, the small world network is built by rewiring a grid. Various processes generate power-law networks (i.e., the node distribution is described by a power law).

I can see two justifications for this type of research. The first is diffusion theory. The speed at which something diffuses in a network is definitely governed by the structure. The second is a sort of physical science justification, where you think of a network as a “system” and you show that some micro-process (e.g., preferential attachment) creates that network.

Is there any other behavioral implication of studying power laws/small worlds or other specific large scale properties? In other words, why should I care about scale free or small world networks aside from diffusion theory?

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* Let’s leave aside recent criticism of power-law centric research for the sake of the post.

Written by fabiorojas

June 22, 2012 at 12:01 am

duncan watts moves from yahoo to (microsoft?)

The network news of the day:

Duncan Watts, the social science researcher who has been at Yahoo since 2007, has left the company.

Yahoo confirmed the departure. Watts has reportedly joined Microsoft’s research organization, but the software company declined to comment.

Comments? I’m excited to see what he does at his new job.

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Written by fabiorojas

April 30, 2012 at 4:28 am

Posted in fabio, networks

network science, a new journal

This seems like big news, a new multi-disciplinary journal on networks: Network Science.  First issue slated for Spring 2013.

(Hat tip: Rense Corten.)

Written by teppo

March 29, 2012 at 11:39 pm

Posted in networks

the abundance of living alone

Eric Klinenberg is a sociologist who also happens to be a very good writer. Who needs a Malcolm Gladwell to popularize sociology when we already have good writers, like Klinenberg, in the discipline? His book Heat Wave: A Social Autopsy of Disaster in Chicago is an example of his ability to present empirical sociology in an engaging and lucid form.

Eric’s latest book, Going Solo: The Extraordinary Rise and Surprising Appeal of Living Alone, expands on a theme of Heat Wave: that living alone is a growing trend, especially in urban areas, that has changed the nature of community and relationships.  In his former book Eric showed that the people most susceptible to the negative consequences of a major environmental disaster, like a heat wave, were those who lived alone and lacked a social safety net to assist them during the crisis. Although in Heat Wave he focused on the deleterious effects of “living and dying alone,” this book takes a broader perspective by first trying to understand why more people are making this life choice and then by examining its consequences on life quality.

One of the interesting insights of Going Solo is that living alone has become easier for people to do because there are so many ways in which people can create and flourish abundant social lives outside the home. Facebook, email, texting, and other social media provide numerous points of contact that shorten the social distance between friends and family. Someone who lived alone 30 years ago might have felt isolated because it was much more costly and difficult to maintain close contact with friends, but now personal communication with friends and family has become so easy to do that it can almost be overwhelming.

One woman we interviewed, an attorney in her early thirties who works in politics, tells me: ‘Of my nine-hour day, I’m spending seven hours responding to emails’ – mostly job related, but many from friends and family too. ‘I also have, like, three hundred fifty people in my cell phone,’ she explains. It buzzes often, she checks it constantly, and she always tries to respond quickly, even if she’s out with friends and the call or message is from work.

This behavior is not unusual. Although we often associate living alone with social isolation, for most adults the reverse is true. In many cases, those who live alone are socially overextended, and hyperactive use of digital media keeps them even busier. The young urban professionals we interviewed reported that they struggle more with avoiding the distraction of always available social activity, from evenings with friends to online chatter, than with being disconnected. ‘Singles in the U.S.: The New Nuclear Family’ confirms this. The large-scale study by the market research firm Packaged Facts reports that those who live alone are more likely than others to say that the Internet has changed the way they spend their free time, more likely to be online late at night, and more likely to say that using the Net has cut into their sleep. Not that they are homebodies. According to a Pew Foundation study of social isolation and technology, heavy users of the Internet and social media are actually more likely than others to have large and diverse social networks, visit public places where strangers may interact, and participate in volunteer organizations (pg. 64).

If people used to seek domestic life in order to avoid social isolation, social technology seems to have weakened some of that need. People, especially those who can afford to stay connected and have a busy social life, may find pairing up and having kids less appealing than ever.

This book is full of fascinating facts and anecdotes about why and how people manage to live alone. This would be a great book for undergraduate courses in urban/community sociology, social networks, social problems, or even an introductory course in sociology.

Written by brayden king

February 29, 2012 at 4:35 pm

creative groups

It’s been a while since we’ve knocked heads with our evil twin blog.  I can’t let this one pass. Peter Klein misrepresents the main point of this Jonah Lehrer New Yorker article, which dissects the myth that brainstorming leads to creativity and greater problem solving. Citing a quote by former orgtheory guest blogger Keith Sawyer – “Decades of research have consistently shown that brainstorming groups think of far fewer ideas than the same number of people who work alone and later pool their ideas” – Peter implies that groups would be more creative if they’d just let individuals work on their own. This fits nicely with a pure reductionist perspective but it’s not at all what the article is really trying to say.

This is the conclusion that Peter should have drawn from the essay: “[L]ike it or not, human creativity has increasingly become a group process.”  Lehrer goes on to cite research by my colleagues at Northwestern, Ben Jones and Brian Uzzi, which shows that both scientists and Broadway teams are more successful and creative when bringing together teams made up of diverse individuals. From an article in Science by Wuchty, Jones, and Uzzi:

By analyzing 19.9 million peer-reviewed academic papers and 2.1 million patents from the past fifty years, [Jones] has shown that levels of teamwork have increased in more than ninety-five per cent of scientific subfields; the size of the average team has increased by about twenty per cent each decade. The most frequently cited studies in a field used to be the product of a lone genius, like Einstein or Darwin. Today, regardless of whether researchers are studying particle physics or human genetics, science papers by multiple authors receive more than twice as many citations as those by individuals. This trend was even more apparent when it came to so-called “home-run papers”—publications with at least a hundred citations. These were more than six times as likely to come from a team of scientists.

And summarizing Uzzi’s and Spiro’s AJS paper on Broadway shows:

Uzzi devised a way to quantify the density of these connections, a figure he called Q. If musicals were being developed by teams of artists that had worked together several times before—a common practice, because Broadway producers see “incumbent teams” as less risky—those musicals would have an extremely high Q. A musical created by a team of strangers would have a low Q…..When the Q was low—less than 1.7 on Uzzi’s five-point scale—the musicals were likely to fail. Because the artists didn’t know one another, they struggled to work together and exchange ideas. “This wasn’t so surprising,” Uzzi says. “It takes time to develop a successful collaboration.” But, when the Q was too high (above 3.2), the work also suffered. The artists all thought in similar ways, which crushed innovation. According to Uzzi, this is what happened on Broadway during the nineteen-twenties, which he made the focus of a separate study. The decade is remembered for its glittering array of talent—Cole Porter, Richard Rodgers, Lorenz Hart, Oscar Hammerstein II, and so on—but Uzzi’s data reveals that ninety per cent of musicals produced during the decade were flops, far above the historical norm. “Broadway had some of the biggest names ever,” Uzzi explains. “But the shows were too full of repeat relationships, and that stifled creativity.”

In short, Uzzi argues that teams that had intermediate levels of relationship density were more creative and more successful.

It’s not that groups aren’t effective generators of creativity. As these studies show, innovation tends to be produced via group processes. Knowledge production is increasingly a collective outcome. Rather than assume that people work best alone, we should think more carefully about what kinds of groups are optimally designed for producing creativity.  Diverse groups will be more creative than homogeneous groups. Groups that embrace conflict and critical thought will be less susceptible to groupthink than groups that avoid such conflict.  Groups made up of members who have little experience with outsiders will be less creative.  I agree with Peter that brainstorming is ineffectively taught in many classrooms, but rather than throw out the idea altogether, we should try to teach people how to design groups that are good at generating new ideas.

Written by brayden king

February 14, 2012 at 12:05 am

the network that runs the world

Written by teppo

October 20, 2011 at 2:32 pm

Posted in networks

linkedin network bleg

Someone out there must use LinkedIn and know how its networking tools work. If that’s you, I need your help. I’d like to use LinkedIn to show students how to analyze their social network. I know that LinkedIn has its own network mapping tool that lets you visualize your network, but I don’t know if there is a way to export the nodes so that you can do your own analysis of it. I’d really like a way to export the network in a text or excel file. Does anyone know of a way to do this?

Written by brayden king

October 18, 2011 at 5:05 pm

Posted in brayden, networks

psychology of organizational networks

In case readers haven’t seen this, Organization Science has a call for papers out for a special issue on the psychology of organizational networks.  Details can be found by clicking here (pdf).  Or click below the fold.  Read the rest of this entry »

Written by teppo

October 6, 2011 at 7:35 pm

twitter, social science and mood

[link via David Lazer]

Twitter is getting lots of interest from social scientists.  Here’s a piece from the current issue of Science about how “social scientists wade into the tweet stream” (the figure below is from this article).  And, an NPR piece on a forthcoming Science article by Macy and Golder on affect and mood and twitter.

Written by teppo

September 29, 2011 at 11:02 pm

the performativity of networks

Prompted in part by some conversations at the ASA meetings, in part by Gabriel’s discussion of the Social Structures author-meets-critics session, and in part by some gentle prodding from Cosma Shalizi, here’s a current draft of a paper of mine, The Performativity of Networks, that I’ve been sitting on for rather too long. Here’s the abstract:

The “performativity thesis” is the claim that parts of contemporary economics and finance, when carried out into the world by professionals and popularizers, reformat and reorganize the phenomena they purport to describe, in ways that bring the world into line with theory. Practical technologies, calculative devices and portable algorithms give actors tools to implement particular models of action. I argue that social network analysis is performative in the same sense as the cases studied in this literature. Social network analysis and finance theory are similar in key aspects of their development and effects. For the case of economics, evidence for weaker versions of the performativity thesis in quite good, and the strong formulation is circumstantially supported. Network theory easily meets the evidential threshold for the weaker versions; I offer empirical examples that support the strong (or “Barnesian”) formulation. Whether these parallels are a mark in favor of the thesis or a strike against it is an open question. I argue that the social network technologies and models now being “performed” build out systems of generalized reciprocity, connectivity, and commons-based production. This is in contrast both to an earlier network imagery that emphasized self-interest and entrepreneurial exploitation of structural opportunities, and to the model of action typically considered to be performed by economic technologies.

The usual disclaimers about work-in-progress apply.

Written by Kieran

August 26, 2011 at 10:59 am


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