Tag Archives: research

Risky Behaviors and Online Safety: A 2010 Literature Review

I’m pleased to announce a rough draft of Risky Behaviors and Online Safety: A 2010 Literature Review for public feedback. This Literature Review was produced for Harvard Berkman Center’s Youth and Media Policy Working Group Initiative, co-directed by John Palfrey, Urs Gasser, and myself and funded by the MacArthur Foundation. This Literature Review builds on the 2008 LitReview that Andrew Schrock and I crafted for the Internet Safety Technical Task Force. This document is not finalized, but we want to make our draft available broadly so that scholars working in this area can inform us of anything that we might be missing.

Risky Behaviors and Online Safety: A 2010 Literature Review

It’s been almost two years since the Internet Safety Technical Task Force completed its work. As a co-director of that project, I coordinated the Research Advisory Board to make certain that we included all of the different research that addressed online safety. When we shared our report, we were heavily criticized as being naive and clueless (or worse). Much of the criticism was directed at me and the researchers. We were regularly told that social network sites would radically change the picture of online safety and that we simply didn’t have new enough data to understand how different things would be in a few years. Those critiques continue. As researchers who were actively collecting data and in the field, many of us are frustrated because what we see doesn’t match what the politicians believe. It’s been two years since we put out that first Lit Review and I’m glad to be able to share an updated one with all sorts of new data. Not surprisingly (to us at least), not much has changed.

What you’ll find is that researchers have gone deeper, getting a better picture of some of the dynamics and implications. You’ll also find that the overarching picture has not changed much. Many of the core messages that we shared in the ISTTF report continue to hold. In this updated Lit Review, we interrogate the core issues raised in the ISTTF report and introduce new literature that complements, conflicts, or clarifies what was previously said. We bring in international data to provide a powerful comparison, most notably from the reports that came out in the EU and Australia. And we highlight areas where new research is currently underway and where more research is necessary.

This Literature Review does not include information on sexting, which can be found in Sexting: Youth Practices and Legal Implications. It also does not include some of the material on self-harm because we are working on a separate review of that material (to be released soon).

As I said, this is a draft version that we’re putting out for public commentary and critique. We will continue to modify this in the upcoming months. If you think we’re missing anything, please let us know!!

Upcoming fieldwork: What do you want to know?

I’m gearing up for a bunch of new on-the-ground fieldwork and intend to do a host of semi-structured interviews with American teenagers in different parts of the U.S. in the upcoming months. While I talk to teens regularly, new in-depth fieldwork allows me to really tease out core conceptual puzzles. My goal for this upcoming bout of fieldwork is to really go deep into questions surrounding privacy and publicity. But as I start fieldtesting new questions and running pilot interviews, I thought I’d throw it out to you too. So….

What do you want to know about teens and social media?

Also… if you have general questions for me about my findings, I’m trying out Formspring to field questions. Feel free to ask me questions about research at any time and I’ll do my best to answer them!

Pew Research confirms that youth care about their reputation

In today’s discussions about privacy, “youth don’t care about privacy” is an irritating but popular myth. Embedded in this rhetoric is the belief that youth are reckless risk-takers who don’t care about the consequences of their actions. This couldn’t be further from the truth.

In my own work, I’ve found that teenagers care deeply about privacy in that they care about knowing how information flows and wanting influence over it. They care deeply about their reputation and leverage the tools available to help shape who they are. Of course, reputation and privacy always come back to audience. And audience is where we continuously misunderstand teenagers. They want to make sure that people they respect or admire think highly of them. But this doesn’t always mean that they care about how YOU think about them. So a teenager may be willing to sully their reputation as their parents see it if it gives them street cred that makes them cool amongst their peers. This is why reputation is so messy. There’s no universal reputation, no universal self-presentation. It’s always about audience.

The teenagers that I first started interviewing in 2004 are now young adults. Many are in college or in the army and their views on their reputation have matured. How they think about privacy and information flow has also matured. They’re thinking about a broader world. At the same time, they’re doing so having developed an understanding of these challenges through their engagement with social media. Are their ideas about these technologies perfect? Of course not. But they’re a whole lot more nuanced than those of most adults that I talk with.

Earlier today, Pew Research Center’s Internet and American Life Project released a report entitled “Reputation, Management, and Social Media” which includes a slew of data that might seem counter-intuitive to adults who have really skewed mythical views of youth and young adults. They found that young adults are more actively engaged in managing what they share online than older adults. In fact, 71% of the 18-29s interviewed in August-September of 2009 who use social network sites reported having changed their privacy settings (vs. 55% of those 50-64). Think about that. This was before Time Magazine put privacy on their front page.

Now, let’s be clear… Young adults are actively engaged in managing their reputation but they’re not always successful. The tools are confusing and companies continue to expose them without them understanding what’s happening. But the fact that they go out of their way to try to shape their information is important. It signals very clearly that young adults care deeply about information flow and reputation.

Reputation matters. This is why Pew found that 47% of 18-29s delete comments made by others on their profiles (vs. 29% of 30-49s and 26% of 50-64s). Likewise, 41% of them remove their name from photos (vs. 24% of 30-49s and 18% of 50-64s). While Pew didn’t collect data on those under 18, I’d expect that this age-wise trend would continue into that age bracket. Much of this is because of digital literacy – the younger folks understand the controls better than the older folks AND they understand the implications better. We spend a lot more time telling teenagers and young adults that there are consequences to reputation when information is put up online than we do listening to ourselves. This is also because, as always, youth are learning the hard way. As Pew notes, young adults have made mistakes that they regret. They’ve also seen their friends make mistakes that they regret. All of this leads to greater consciousness about these issues and a deeper level of engagement.

As always, this Pew report is filled to the brim with useful information that gives us a sense of what’s going on. Here are some of my favorite bullet points:

  • Young adults are still more likely than older users to say they limit the amount of information available about them online.
  • Those who know more, worry more. And those who express concern are twice as likely to say they take steps to limit the amount of information available about them online.
  • The most visible and engaged internet users are also most active in limiting the information connected to their names online.
  • The more you see footprints left by others, the more likely you are to limit your own.
  • Those who take steps to limit the information about them online are less likely to post comments online using their real name.
  • More than half of social networking users (56%) have “unfriended” others in their network.
  • Just because we’re friends doesn’t mean I’m listening: 41% of social networking users say they filter updates posted by some of their friends.
  • Young adult users of social networking sites report the lowest levels of trust in them.

This Pew report does more than inform us about privacy and reputation issues. Its data sends an important message: We need more literacy about these issues. Ironically, I think that the best thing that’s going to come about because of Facebook’s ongoing screw-ups is an increased awareness of privacy issues. When youth see that they can do one of two things with their interests: delete them or make them publicly visible to everyone, they’re going to think twice. Sure, many will still make a lot of that content publicly accessible. And others will be very angry at Facebook for not giving them a meaningful choice. But this is going to force people to think about these issues. And the more people think about it, the more they actively try to control what’s going on. (Of course, we need Facebook to stop taking controls away from people, but that’s a different story.)

Pew’s report also counters a lot of myths that I’ve been hearing. For example, the desire for anonymity isn’t dead. Facebook tends to proudly announce that its users are completely honest about their names. Guess what? Many youth don’t trust Facebook. And they’re not providing them with real names either. Just take a look at this screen shot that I grabbed from a publicly accessible Facebook profile. This image isn’t doctored and while some of the names reflect real ones, there’s a lot of obscuring going on.

If you care about youth, if you care about issues of privacy and reputation, PLEASE read the Pew report. It is an example of brilliant research and tremendous reporting.

am I an academic?

academia (n.): The academic world or community; scholastic life.

academic (n.): 1) An ancient philosopher of the Academy.
2) A member of a college or university.
3) A member of a society for promoting art or science

At every academic conference I attend, I hear a constant refrain: “How does it feel to have left academia?” The tone changes dependent on who is doing the asking. Sometimes, it’s pure curiosity or puzzlement, fascination at my choice. At other times, there’s a hint of condescension, as though the question is actually: “Couldn’t make it in academia, eh? Stuck in industry, eh?” I try not to bristle at this but I do find myself getting defensive and trying to explain my position at Microsoft Research over and over again. So I couldn’t help but think that maybe it’s time to write it down.

Microsoft Research is an industrial research lab in the old skool sense. In the world of computer science, the industrial research lab is well understood; it has a long history of success in producing valuable, field-changing research. Like AT&T Bell Labs or Xerox PARC, the halls of MSR are filled with scientists of the highest caliber. People who invented things that you take for granted. MSR grew out of this tradition. It’s primarily filled with computer scientists (and engineers, physicists, mathematicians). Researchers are encouraged to pursue research questions that they feel are important and they are evaluated based on their publication record, contributions to the scholarly community, and innovative research that produces “tech transfer.”

Being a social scientist in one of these labs is peculiar, but not new. I have long admired the anthropological contributions Lucy Suchman made to research while at PARC. Being a social scientist at an industrial research lab can be a tricky balance. There are plenty of anthropologists and other social scientists who do applied work at Microsoft, focused on specific product needs. This is extremely important work, but it’s different than scholarly research. It’s also tricky to say what constitutes “tech transfer” as a social scientist. I don’t really produce IP in the traditional sense, but my work contributes to the company in other ways.

Yet, tech transfer is only a fraction of what I do. The vast majority of my time is spent doing the same type of research that I’ve been doing for years. I follow topics that interest me and dive head first in, regardless of whether or not it involves Microsoft’s current or future products. I publish articles without seeking approval from anyone. I blog about my research without vetting it through Microsoft. I attend academic conferences, review papers, and contribute to scholarly discourse. It looks a whole lot like academia to me. Yet, I hear all sorts of remarks that indicate that folks don’t believe that what I do is akin to academia. I feel the need to account for these and offer a different perspective.

But you’re working for a corporation! Since when are universities not corporations? Best that I can tell, most universities are fundamentally real estate barons who gain public credibility by offering higher education. The difference is that Microsoft’s products are very visible and related to the types of research that they seek to support. Both Microsoft and the university invest in research in the hopes that it will benefit the corporation as a whole, directly through the production (and protection) of IP or indirectly by creating an atmosphere where productive work can take place. The outcomes may look different, but both Microsoft and the university are large corporations with a fiscal mindset.

But a company makes you focus on the company’s bottom line! There is no doubt that Microsoft would love to have research that benefits it financially, but the dynamic is far more symbiotic than parasitic. We’re welcome to do the research we’re most passionate about, but we get financial bonuses for creating patents or for producing quality research that benefits the company. It’s an incentives system. On the contrary, I would argue that the university model is predominantly parasitic. Researchers at universities must run around begging external agencies for money so that they can do the research they love to do. When they finally succeed in getting a grant, how does the university respond? It takes 30-60% for “overhead.” And when they don’t get funding, they’re punished with lack of research resources and students. Furthermore, most university researchers don’t get to do as they please – they do what they (think they) can get funding for. I suspect I have far more freedom in terms of my research agenda than most university scholars.

Still, you have to spend time helping the company directly! Yes, I spend time working with product groups. But I like to think of it as my teaching duty. Rather than teaching Soc 101 to hung-over 18-year-olds who didn’t bother doing the reading, I teach an interactive form of Soc 101 to engineers who are filled with questions that start with “but why?” and “but how?” I have a hard time imagining that my engagement with product groups takes up more of my time than teaching, office hours, and prep. And it’s often quite fun and thought-provoking.

Well, there’s no tenure! What exactly is tenure? The promise that the university will promise you a salary in return for perpetual grant begging? Tenure guarantees a job, but it doesn’t guarantee an enjoyable one. There’s no promise of a pay raise or good classes to teach. Microsoft Research does have the right to fire me but, from what I can see, it’s more common for people to leave when they don’t gel well (just like in universities). The bigger threat is whether or not Microsoft will be around in N years (arguably, also true with many universities). I suspect that my job is just as solid as it would be in most university environments. The difference really comes down to bonuses. At the university, there are no performance-based bonuses. At Microsoft Research, a large chunk of my salary is linked to performance. Thus, I have an incentive to do well. There are also promotions that parallel university levels; Researcher = Assistant Professor, Senior Researcher = Associate Professor, Principle Researcher = Full Professor. This may not offer the on-paper guarantee of tenure, but it is pretty darn equivalent.

It’s not like you have students! Most professors love having students because of the collaboration potential. (Some enjoy the empire building but that’s not my bent.) Of course, this varies by field. Some scholars feel as though they need students to complete their work; in other fields, students are more an opportunity to mentor. My approach to students is more of collaboration and mentorship rather than slave labor. It’s true that I don’t have students, but I have the fortune of being able to take a handful of interns each year for 12 weeks each. These interns are primarily post-quals PhD students who have the skills and passion for collaboratively working on a constrained research project. No, it is not the same as 7-year students that you get to watch grow, but it’s not like I’m not engaged with younger scholars. My time with them is just more constrained and focused. There are also postdocs who come for 1-2 years. And when I’m craving collaboration, I can bring in visiting researchers to work with me. So it’s a bit more hodge-podge, but there’s still tremendous opportunities for engagement with scholars at all levels.

Whatever… it’s not real research. This is what it always comes down to… “Real” research comes from the university, suggesting that what comes out of industrial research labs is “fake.” I’m never quite sure how to best respond to this except to commit to proving folks wrong.

I feel very fortunate to have a position at Microsoft Research, even if lots of folks don’t seem to get why it’s a good deal. In many ways, this environment is far more academic than what I witnessed at MIT’s Media Lab or Berkeley’s iSchool. The biggest downside is that it’s not helping with my disciplinary identity crisis. If I had joined a specific disciplinary department, I might have had a clearer sense of the “top” journals, relevant conferences, and whether or not publishing a book is a must to succeed. Perhaps not, but I like to think so. Instead, I’m as confused as ever about where to publish and how to best disseminate my research in a manner that is generally useful. Thus, instead of becoming a proper -ist, I’m continuing to pave a strange path that may or may not bite me in the ass in the future. Of course, this identity crisis is pure academia. And one of the clearest reminders that I’m still an academic through-and-through.

I may not be a professor, but I’m still a scholar and, arguably, an academic. The title of “Researcher” may not seem very impressive or academic in social science realms, but practically speaking, it’s akin to “Assistant Professor” (and that’s even how people discuss it internally). What I do looks a lot like what any university researcher does, but with fewer restrictions. I don’t have to beg for grants. I don’t have to battle onerous IRBs (note: dealing directly with lawyers is MUCH easier than dealing with academics who are worrying about the legal repercussions of research). I can travel when I need to for research. I can do research that I think is important. I can collaborate with whomever I please. In return, I make certain that my research (and that of others) is translated into language that product people can understand. Personally, I think it’s a pretty amazing trade-off.

Teens Don’t Tweet… Or Do They?

Yesterday, Mashable reported Nielsen’s latest Twitter numbers with the headline Stats Confirm It: Teens Don’t Tweet. This gained traction on Twitter turning into the trending topic “teens don’t tweet” which was primarily kept in play all day yesterday with teens responding to the TT by saying “I’m a teen” or the equivalent of “you’re all idiots… what am I, mashed potatoes?”

I want to unpack some of what played out because I’m astonished by the misinterpretations in every which direction.

We have a methodology and interpretation problem. As Fred Stutzman has pointed out, there are reasons to question Nielsen’s methodology and, thus, their findings. Furthermore, the way that they present the data is misleading. If we were to assume an even distribution of Twitter use over the entire U.S. population, it would be completely normal to expect that 16% of Twitter users are young adults. So, really, what Nielsen is saying is, “Everyone expects social media to be used primarily by the young but OMG OMG OMG old farts are just as likely to be using Twitter as young folks! Like OMG.”

We have a presentation problem. Mashable presented this report completely inaccurately. First off, Nielsen is measuring 2-24. My guess is that there are a lot more 24-year-olds on Twitter than 2-year-olds. Unless Sockington counts. (And she’s probably older than 2 anyhow.) Regardless, the Nielsen data tells us nothing about teens. We don’t know if young adults (20-24) are all of those numbers or not. If all 16% of those under 24 on Twitter were teens, teens would be WAY over-represented in proportion to their demographic size.

We have a representation problem. The majority of people are not on Twitter, regardless of how old they are. Those who use Twitter are not a representative percentage of the population. Geeks are WAY over-represented on Twitter. Celebs and celeb-lovers are WAY over-represented on Twitter. Newshounds are WAY over-represented on Twitter. And while Joe the Plumber has an account on Twitter, I doubt it’s him. Age is not the right marker here.

We have an interpretation problem. Saying that 16% of Twitter users are 24 and under is NOT the same as saying that 16% of teens are on Twitter. We don’t know what percentage of youth (or adults) are on Twitter. If you want to compare across the ages, you need to know what percentage of a particular demographic is using the technology.

We have an impression management problem. There are teens on Twitter. Thousands of them. Saying “Teens Don’t Tweet” gives the wrong impression because there are plenty of teens who do tweet (as they so kindly vocalized on Mashable and on Twitter). Still, just because they suddenly became vocal doesn’t mean that those who are there are representative of teens as a whole. Furthermore, the presence of teens on Twitter doesn’t mean that Twitter is a mainstream tool amongst teens. It’s not.

Given all of these problems, I immediately dismissed the Nielsen report and the Mashable post as irrelevant and meaningless. Then it became a Trending Topic. So while I had a million things to do yesterday, I spent 6+ hours reading the messages of the people who added content to the trending topic, reading their posts about other things, going to their profiles on other sites, and simply trying to get a visceral understanding of what youth were engaged enough on Twitter to respond to the trending topic. What I found fascinated me. I’m still coding the data so you won’t get any quantitative data just yet, but I want to give you a sense of my impression.

Teens On Twitter

The majority of teens who responded to the Trending Topic simply responded to the statement “Teens Don’t Tweet” by noting that they were a teen and they tweeted. Others just noted that the trending topic was dumb. Many didn’t know why the term had become a trending topic, were unaware of the Mashable article or Nielsen study, and thought that Twitter chose the trending topics. (I was in awe of how many teens commented that Twitter was stupid for making such a lie a trending topic. Some thought it was Twitter’s attempts to tell them they didn’t belong. One did ask if it was a trap to get teens to come out of the closet about their real age.)

Many of the teens who responded to the TT were not American or Canadian. I saw bunches of Brazilian teens, some Indonesian teens, and a smattering of teens from Europe, China, and Mexico. Many of their Twitter streams mixed English and the local language of their country. English dominated the responses but I did see non-English responses to the English trending topic.

About half of the teens included a link to a non-Twitter page in their bio. The pages were really mixed. Among the SNSes, MySpace dominated, but there were some Facebook links and links to Piczo and Multiply. There were also links to YouTube, Blogspot, LiveJournal, Deviant Art, and personal homepages.

Very few of the teens put their age in their bio, although quite a few made their age available in the content or through links. Teens posted messages like “I’m 16 and I’m on Twitter.” And birthdays are a big enough deal that I was seeing things like, “I can’t wait until I’m 16 and can get a car. Only 3 months to go!” And of course there’s MySpace.

Most of the teens on Twitter followed on the order of 40-70 other people (with fewer followers). Who they followed included a smattering of other teens and a collection of big names – celebs, bloggers, geeks. There wasn’t much discussion on their feeds about the number of people following them but they frequently highlighted how many tweets they had. I was surprised by how many of them would write a tweet saying nothing more than “this is my 1207th tweet!” Their content is primarily phatic in nature with an eye for updating as often as possible.

The most salient visceral reaction that I got when looking at the teens’ Twitter streams was that teens on Twitter seemed to fit into three categories: 1) geeky teens, tech teens, fandom teens, machinema teens; 2) teens who are in love with the Jonas Brothers/Miley Cyrus, musicians, or another category of celebs; 3) multi-lingual foreign teens with friends/followers around the world who seemed to participate in lots of online communities.

While I can’t make any meaningful conclusions until I spend more time with the data, it seems to me that the teens on Twitter – or at least the teens responding to the trending topic – are not representative of teens as a whole. That’s not a bad thing. They’re geeks and passionate creators and trendsetters and pop culture addicts. I don’t get the sense that they’re dragging their friends into Twitter, but rather, focusing on using Twitter to engage with other people who share their interests or people that they admire.

Anyhow, I’m continuing to track this but I thought I should just report out what I’m seeing in case it’s of use to anyone but me.

Be warned: This blog post was written in brain-dump style to get some general impressions out there while I analyze the data. My goal is to give you a sense of what I’m seeing, assuming that you aren’t staring at thousands and thousands of tweets by teens. Please don’t interpret it as a “report” or a “study” or anything other than what it is: a blog post.

Would the real social network please stand up?

This ideas in this post are based on conversations with Bernie Hogan and should be interpreted as the production of our co-thinking.

All too frequently, someone makes a comment about how a large number of Facebook Friends must mean a high degree of social capital. Or how we can determine who is closest to who by measuring their email messages. Or that the Dunbar number can explain the average number of Facebook friends. These are just three examples of how people mistakenly assume that 1) any social network that can be boiled down to a graph can be compared and 2) any theory of social networks is transitive to any graph representing connections between people. Such mistaken views result in broad misinterpretations of social networks and social network sites. Yet, time and time again, I hear problematic assumptions so let me start with some claims:

  1. Not all social networks are the same.
  2. You cannot assume network transitivity.
  3. You cannot assume that properties that hold for one network apply to other networks.

To address this, I want to begin by mapping out three distinct ways of modeling a social network. These are not the only ways of modeling a social network, but they are three common ways that are often collapsed in public discourse.

Sociological “personal” networks. Sociologists have been working hard to measure people’s personal networks and much of the theory of social networks stems from analysis done on these networks. Different scholars have taken different approaches to measuring personal networks, but, most stereotypically, this takes the form of a clipboard and pencil as a young grad student queries an individual to recall who they talked to yesterday and indicate who they would lend money to or call when they are having an emotional breakdown. On classic measurement survey is an appendix in the back of Claude Fischer’s “To Dwell Among Friends.”

Most sociological theory stems from analyses of these personal networks. Social capital, weak ties, homophily, … all of those theories you’ve heard about are based on personal networks. Given that these are typically measured by eliciting people’s understandings of certain categories (e.g., “friend”), there’s a strong overlap between everyday language around social networks and the categories being measured.

If you’re a sociologist talking to anyone other than sociologists, you would probably speak of personal networks as the golden standard, the baseline truth. Of course, if you were being honest with yourself or your colleagues, you will note that these measurements have their methodological flaws and biases which is why the scales for measuring personal networks haven’t stabilized and why scholars still struggle with the best ways to elicit meaningful information from people being surveyed.

Behavioral social networks. Behavioral social networks are the networks derived from encounters between individuals. In their efforts to measure personal networks, sociologists have often tried to get people to manually document encounters with others through diary studies. With new technologies in place, folks have gone on to generate behavioral social networks through the traces people leave behind. For example, a record of someone’s email exchanges provides a handy accounting of that individual’s behavioral network. New technologies introduces new opportunities for measuring behavioral networks. Many genres of social media let us see who communicates with who. GPS technologies let us see who shares physical space.

Behavioral social networks provide valuable insight into people’s practices and interactions, but they do not confer meaning. This is not to say that they don’t have value. I would love to find the strangers that I regularly share space with as I traverse Boston. But we cannot assume that these are my friends or acquaintances. Yet, there seems to be a tendency (especially among geeks of all stripes) to overlay meaning-laden terms on top of these networks, to assume that high connectivity means friendship. This is where trouble often arises. Just because I spend a lot of time with my physical therapist does not mean that she is more important than other people in my network who I see less frequently.

The other difficulty in measuring behavioral social networks is that, at least to date, we measure distinct channels of connection. This complicates our ability to do meaningful comparison across people. If I use AIM as my primary way of keeping in touch with Person A and email as my primary way of keeping in touch with Person B and you only look at one medium, you get a distorted picture of who I communicate with. As communication channels proliferate, this only gets messier. So even when we talk about behavioral social networks, we have to talk about them in across a particular channel.

Publicly articulated social networks. Articulated social networks are the social networks that you intentionally list. In some senses, this is what sociologists are eliciting, but people also articulate their social networks for other purposes. Address books and buddy lists are articulated social networks. So too are invitation lists. Most recently, this practice took a twist with the rise of social network sites that invite you to PUBLICLY articulate your social network.

At this point, I would hope that most of us would realize that Friends != friends. In other words, who you connect to on Facebook or MySpace or Twitter is not the same list of people that you would say constitute your closest and dearest. The practice of publicly articulating one’s social network can be quite fraught because there are social costs to the process of public articulation. Issues of reciprocity emerge and people find themselves doing a lot of face-work to navigate the sticky nature of having to account for their social relations in a publicly accountable way. Thus, the list of who you might list as a Friend is often a mix of friends, acquaintances, family members, people from your past, fans, professional colleagues, familiar strangers, and people you don’t particularly like but don’t want to offend. Oh and the occasional celebrity you think is interesting.

Relating Different Social Networks

These networks are NOT the same. Your mother may play a significant role in your personal network but, behaviorally, your strongest tie might be the person who works in the cube next to you. And neither of these folks might be links on your Facebook for any number of reasons.

Our instinct then is to ask: which is the “real” social network? Frankly, it depends on who you ask. Your mother may be cranky that you don’t talk to her as often as your colleague and she may resent your refusal to Friend her on Facebook, but this doesn’t mean you love her any less. Of course, this doesn’t stop her from thinking you don’t love her. If we’re trying to understand emotional affinity, the behavioral and publicly articulated social networks aren’t particularly helpful. But if you’re mother thinks that time is not only a proxy for emotional depth but a proof of it, your behavioral social network might really upset her. (Note: behavioral social networks have gotten people into trouble in the past. See Cobot.)

The truth of the matter is that there is no “real” social network. It all depends on what you’re trying to measure, what you’re trying to do with those measurements.

We do ourselves an intellectual disservice when we assume that these different types of networks are interchangeable or that studying one automatically tells us about another. Most scholars get this, even when they’re quoted out of context by journalists to suggest otherwise (see Cameron Marlow). But I get the sense that a lot of journalists, marketers, advertisers, politicians, and everyday folks don’t. This is a problem.

Those who treat different social networks interchangeably project properties onto the network they’re analyzing that don’t hold. People aren’t inherently cool or connectors because they have a lot of Friends on a social network site. Bus drivers and waitresses are much more likely to encounter more new people on a daily basis than executives, but this doesn’t mean that they have more social capital. People who email regularly do not necessarily have strong tie strength.

This is not to say that structural information in behavioral social networks or publicly articulated social networks may not work as a proxy for personal networks. Perhaps the networks derived from a particular social media tool or through a particular channel of communication do actually provide insight into a person’s personal network. There are great ways to empirically test this hypothesis involving the combination of structural analysis and interviewing. But you cannot simply assume that they are meaningful proxies just because they are both social networks.

There are also many opportunities for new research when we tease out different types of social networks. What if we overlay the different types of social networks? Can we get a better sense of how someone manages their social network? Can we see new structural properties that give us new insights into how people connect, share information, gather support, etc.? So many possibilities!

I’m super excited that so many people from so many fields are getting interested in social networks, but I’m also scared that there are a lot of assumptions flying around that make it difficult to make sense of people’s contributions to this emergent field. Increasingly, I see sociologists and computer scientists and mathematician and economists outright dismiss work outside of their field as “wrong.” I think that part of the problem is that we’re each failing to account for what we can and cannot say based on the types of analysis we’re doing. And I think that we often talk past one another because we’re all talking about social networks but we’re talking about different social networks. In accounting for three types of social networks here, I’m not trying to be all-inclusive, but I am trying to point out that there are differences and that we cannot assume transitivity either in terms of structure or theory. If we can find a way to better identify what kinds of social networks we’re talking about and when and where what theories apply, I think that we’ll go a long way in bridging different intellectual discourses.

Research on Social Network Sites

UPDATE: This page is out-of-date. An updated list can be found here:

Research on Social Network Sites

Thank you!

I want to track down everyone who is actively doing research on social network sites. (Clarification: i’m looking for folks that are publishing in peer-reviewed spaces, not just researching for their company or blog.) Nicole Ellison and i are plotting to bring ways to bring everyone together. I’m also looking to create a list of all known publications. I know there’s more than what i’m listing so i need your help. Please!

Publications and Presentations