Last week, I wrote a number of essays critical of Twitter’s decision to provide a collection of public Tweets to the Library of Congress for permanent archiving. I argued that by taking user data and putting it into a public archive, Twitter had meaningfully restricted the privacy rights of users. Some of you agreed with my position, many didn’t; but all who commented or wrote to me helped shape my thinking. In this post, I want to provide a little more context on the nature of privacy in systems like Twitter.
Last week, I gave a talk on the dynamics of privacy in Facebook. In the research, we modeled a behavior that is increasingly pervasive in Facebook: having a friends-only profile. I want to draw attention to one slide from the talk:
In this slide, the two slopes you see are the growth of Facebook, and the proportion of UNC undergraduates with friends-only profiles. Now, the data are on different axes, and Excel is fitting the lines, but the trend is meaningful. With growth in the service we see a correlated turn towards privacy.
While the pattern I observe is only general to Facebook at UNC, other researchers have observed similar patterns of privacy behavior in other social software. For example, as Friendster scaled,
[S]o too did the diversity of the social networks represented. A growing portion of participants found themselves simultaneously negotiating multiple social groups—social and professional circles, side interests, and so on. (boyd, 2007)
With the increasing complexity of diverse audiences, individuals turned to a range of strategies to manage their privacy: multiple accounts, limiting disclosure, or simply dropping out of the service. Regarding Myspace, Caverlee and Webb (2008) reported (bold is mine):
Overall, the fraction of private profiles is increasing with time, indicating that new adopters of social networks may be more attuned to the inherent privacy risks of adopting a public Web presence. We find that women favor private profiles 2-to-1 over men, and that (perhaps, counter-intuitively) younger users are more likely to adopt a private profile than older users. We also find that the more connected a user is in the social network, the more likely she is to adopt a private profile.
And now in Facebook, our research finds a similar movement towards privacy as the service grows and networks diversify. One can only suspect that Facebook’s recent “privacy upgrades” and changes to the terms of service prohibiting privacy of certain information has something to do with this normative shift.
Looking at the data across systems, I’d like to speculate that there’s a general property at work. In a social software system, as the system grows and diversity of networks increases, so does utilization of privacy. Here’s a graph I’ve constructed illustrating the trend (larger version):
The slope is purposefully convex. In the early stages of adoption, network use is sparse, so individuals are incentivized to lower privacy, to increase the odds of finding others. As time passes and the service grows, individuals form dense, small-world clusters. At this stage, individuals are mainly connected to one another within one context, and there are minimal bridges between contexts. Therefore, individuals can afford to keep privacy low, due to minimal risk of inadvertent sharing across context. As the system expands, however, we see a turn back towards privacy as an increasing number of bridges across context are created. In this moment of context collapse, individuals erect barriers of privacy to facilitate continued disclosure. Here’s a closer look at the (simulated) networks:
By linking privacy to context collapse, I argue that mobilization towards privacy is largely a function of perceived audiences (and harms). This distinction is important because it holds privacy attitudes constant. Research, both mine and by others, has demonstrated that privacy attitudes do not necessarily predict privacy behaviors. Awareness of privacy-in-context is actually the key variable causing the dynamic shift towards privacy in social software systems.
Let’s return our attention to Twitter. What does your Twitter network look like? If you’re an average user, your network probably contains a few offline friends (many, many fewer than Facebook or Myspace) and some celebrities (your definition may vary). There may also be a few friends you’ve made on Twitter, who you don’t know offline. Chances are, the average Twitter user’s network looks like the sparse “Early Adopter” or “Small World” network.
We see evidence in cultural practice that users have sparse networks in Twitter. Going back to my notes on Alice Marwick’s AOIR ’09 talk, the culture of celebrity serves a very functional purpose for Twitterers with sparse networks, who wish to connect out of limiting contexts. “Talking” to celebrities (and finding others who talk to the celebs you talk to) is a way of escaping one’s sparse world, finding new people to follow in a known context. Hashtag culture provides further evidence that individuals are trying to talk “across” or “out” of limited contexts. If your network is sparse, turning to site-level anchors like hashtags and celebs provides a reliable stream of conversation in networks where conversation is lacking due to structural impediments.
I wonder how long these practices will need to continue. Just the other day, Twitter announced that 100 million people had created accounts. You can’t turn the news on without hearing about Twitter. A large group of people, primed on social software by Facebook, are waiting to join Twitter. And over the next year or two, they will, raising issues of context collapse, and prompting a turn toward increased privacy among early adopters.
My major problem with the Twitter/LoC agreement is that the people who will be confronted with context collapse and a growing need for privacy have lost meaningful recourse. As I argued in my last post, it becomes impossible to take back what you’ve shared, a real and useful privacy strategy. You’ll still be able to make your account private, but it seems there’s little you can do about the Tweets you sent that were archived permanently in the Library of Congress.
Why is this bad? Let’s consider a hypothetical. In 2007, Myspace had 100 million users. Myspace was growing fast, with many users signing on for the first time. Myspace users had two options for privacy: public or friends-only. And a lot more people had public profiles in 2007 then they do today. How would we feel, now, if Myspace had given all of its public profiles to the Library of Congress for permanent archive in 2007? I can only guess that a bunch of people who had public profiles in 2007 might feel a little uncomfortable about it (cue the “it’s their own damn fault” chorus).
I guess I should feel relief that if Twitter is going to do this to users, at least they are partnering with the LoC (an admirable entity). But, in reading what LoC staff is saying about this effort, I’m not comforted. Of the dataset, LoC Blogger Matt Raymond writes “I’m certain we’ll learn things that none of us now can even possibly conceive.” National Archivist David Ferriero writes “What will historians be able to glean from our tweets? We can’t be sure, but it will probably be very interesting” (while also stating “Twitter is not for everyone. If you are anything like me, you don’t really care what someone had for breakfast.”) It strikes me that the Twitter archive is being treated like a novelty, promising to be an amazing treasure trove when new research methods are developed.
Maybe it’s all these years of running t-tests (developed 1908), but I’m skeptical that these Tweets are going to tell us something that we can’t quite imagine. Robust methods develop slowly, and are validated over time. We’ll probably still be doing text mining, linguistic and sentiment analysis, and content analysis 50 years from now. One area that is improving rapidly, however, is the identification of individuals in large data sets. The Netflix dataset was identified by Narayanan and Shmatikov. Acquisti and Gross demonstrated they were able to guess people’s social security numbers from public data. And old-fashion detective work by Michael Zimmer identified the T3 Facebook dataset. Of the future, we know this: It will be easier to connect you to your archived Twitter identity.
So here’s the thing. Why won’t Twitter make the archiving a simple, opt-in process? Or at least allow people to opt out? Twitter obviously knows that giving user data to a permanent archive is different from sharing an API or allowing a Google spider – they wouldn’t have approached the LoC if this wasn’t the case. I may be the only voice shouting about this, but this is a big, watershed moment regarding user privacy. EFF, EPIC, Facebook watchdogs – where are you? Let’s work with Twitter and make this right.
