Will the desire for other perspectives trump the “friendly world syndrome”?
Some recent journalism at NPR and The New York Times has addressed some aspects of the “friendly world syndrome” created by personalized media. A theme common to both pieces is that people want to encounter different perspectives and will use available resources to do so. I’m a bit more skeptical.
If we keep seeing the same links and catchphrases ricocheting around our social networks, it might mean we are being exposed only to what we want to hear, says Damon Centola, an assistant professor of economic sociology at the Massachusetts Institute of Technology.
“You might say to yourself: ‘I am in a group where I am not getting any views other than the ones I agree with. I’m curious to know what else is out there,’” Professor Centola says.
Consider a new hashtag: diversity.
This is how Singer ends this article in which the central example is “icantdateyou” leading Egypt-related idioms as a trending topic on Twitter. The suggestion here, by Centola and Singer, is that people will notice they are getting a biased perspective of how many people agree with them and what topics people care about — and then will take action to get other perspectives.
Why am I skeptical?
First, I doubt that we really realize the extent to which media — and personalized social media in particular — bias their perception of the frequency of beliefs and events. Even though people know that fiction TV programs (e.g., cop shows) don’t aim to represent reality, heavy TV watchers (on average) substantially overestimate the percent of adult men employed in law enforcement.1 That is, the processes that produce the “friendly world syndrome” function without conscious awareness and, perhaps, even despite it. So people can’t consciously choose to seek out diverse perspectives if they don’t know they are increasingly missing them.
Second, I doubt that people actually want diversity of perspectives all that much. Even if I realize divergent views are missing from my media experience, why would I seek them out? This might be desirable for some people (but not all), and even for those, the desire to encounter people who radically disagree has its limits.
Similar ideas pop up in a NPR All Things Considered segment by Laura Sydell. This short piece (audio, transcript) is part of NPR’s “Cultural Fragmentation” series.2 The segment begins with the worry that offline bubbles are replicated online and quotes me describing how attempts to filter for personal relevance also heighten the bias towards agreement in personalized media.
But much of the piece has actually focuses on how one person — Kyra Gaunt, a professor and musician — is using Twitter to connect and converse with new and different people. Gaunt describes her experience on Twitter as featuring debate, engagement, and “learning about black people even if you’ve never seen one before”. Sydell’s commentary identifies the public nature of Twitter as an important factor in facilitating experiencing diverse perspectives:
But, even though there is a lot of conversation going on among African Americans on Twitter, Professor Gaunt says it’s very different from the closed nature of Facebook because tweets are public.
I think this is true to some degree: much of the content produced by Facebook users is indeed public, but Facebook does not make it as easily searchable or discoverable (e.g., through trending topics). But more importantly, Facebook and Twitter differ in their affordances for conversation. Facebook ties responses to the original post, which means both that the original poster controls who can reply and that everyone who replies is part of the same conversation. Twitter supports replies through the @reply mechanism, so that anyone can reply but the conversation is fragmented, as repliers and consumers often do not see all replies. So, as I’ve described, even if you follow a few people you disagree with on Twitter, you’ll most likely see replies from the other people you follow, who — more often than not — you agree with.
Gaunt’s experience with Twitter is certainly not typical. She has over 3,300 followers and follows over 2,400, so many of her posts will generate replies from people she doesn’t know well but whose replies will appear in her main feed. And — if she looks beyond her main feed to the @Mentions page — she will see the replies from even those she does not follow herself. On the other hand, her followers will likely only see her posts and replies from others they follow.3
Nonetheless, Gaunt’s case is worth considering further, as does Sydell:
SYDELL: Gaunt says she’s made new friends through Twitter.
GAUNT: I’m meeting strangers. I met with two people I had engaged with through Twitter in the past 10 days who I’d never met in real time, in what we say in IRL, in real life. And I met them, and I felt like this is my tribe.
SYDELL: And Gaunt says they weren’t black. But the key word for some observers is tribe. Although there are people like Gaunt who are using social media to reach out, some observers are concerned that she is the exception to the rule, that most of us will be content to stay within our race, class, ethnicity, family or political party.
So Professor Gaunt is likely making connections with people she would not have otherwise. But — it is at least tempting to conclude from “this is my tribe” — they are not people with radically different beliefs and values, even if they have arrived at those beliefs and values from a membership in a different race or class.
- Gerbner, G., Gross, L., Morgan, M., & Signorielli, N. (1980). The “Mainstreaming” of America: Violence Profile No. 11. Journal of Communication, 30(3), 10-29. [↩]
- I was also interviewed for the NPR segment. [↩]
- One nice feature in “new Twitter” — the recently refresh of the Twitter user interface — is that clicking on a tweet will show some of the replies to it in the right column. This may offer an easier way for followers to discover diverse replies to the people they follow. But it is also not particularly usable, as it is often difficult to even trace what a reply is a reply to. [↩]
Political arithmetic: The Joy of Stats
The Joy of Stats with Hans Rosling is quite engaging — and worth watching. I really enjoyed the historical threads running through the piece. I think he’s right to emphasize how data collection by states — to understand and control their populations — is at the origin of statistics. With increasing data collection today, this is a powerful and necessary reminder of the range of ends to which data analysis can be put.
Like others, I found the scenes with Rosling behind a bubble plot made difficult by the distracting lights and windows in the background. And the ending — with analyzing “what it means to be human” — was a bit much for me. But a small complaint about a compelling view.
Ideas behind their time: formal causal inference?
Alex Tabarrok at Marginal Revolution blogs about how some ideas seem notably behind their time:
We are all familiar with ideas said to be ahead of their time, Babbage’s analytical engine and da Vinci’s helicopter are classic examples. We are also familiar with ideas “of their time,” ideas that were “in the air” and thus were often simultaneously discovered such as the telephone, calculus, evolution, and color photography. What is less commented on is the third possibility, ideas that could have been discovered much earlier but which were not, ideas behind their time.
In comparing ideas behind and ahead of their times, it’s worth considering the processes that identify them as such.
In the case of ideas ahead of their time, we rely on records and other evidence of their genesis (e.g., accounts of the use of flamethrowers at sea by the Byzantines ). Later users and re-discoverers of these ideas are then in a position to marvel at their early genesis. In trying to see whether some idea qualifies as ahead of its time, this early genesis, lack or use or underuse, followed by extensive use and development together serve as evidence for “ahead of its time” status.
On the other hand, in identifying ideas behind their time, it seems that we need different sorts of evidence. Taborrok uses the standard of whether their fruits could have been produced a long time earlier (“A lot of the papers in say experimental social psychology published today could have been written a thousand years ago so psychology is behind its time”). We need evidence that people in a previous time had all the intellectual resources to generate and see the use of the idea. Perhaps this makes identifying ideas behind their time harder or more contentious.
Y(X = x) and P(Y | do(x))
Perhaps formal causal inference — and some kind of corresponding new notation, such as Pearl’s do(x) operator or potential outcomes — is an idea behind its time.1 Judea Pearl’s account of the history of structural equation modeling seems to suggest just this: exactly what the early developers of path models (Wright, Haavelmo, Simon) needed was new notation that would have allowed them to distinguish what they were doing (making causal claims with their models) from what others were already doing (making statistical claims).2
In fact, in his recent talk at Stanford, Pearl suggested just this — that if the, say, the equality operator = had been replaced with some kind of assignment operator (say, :=), formal causal inference might have developed much earlier. We might be a lot further along in social science and applied evaluation of interventions if this had happened.
This example raises some questions about the criterion for ideas behind their time that “people in a previous time had all the intellectual resources to generate and see the use of the idea” (above). Pearl is a computer scientist by training and credits this background with his approach to causality as a problem of getting the formal language right — or moving between multiple formal languages. So we may owe this recent development to comfort with creating and evaluating the qualities of formal languages for practical purposes — a comfort found among computer scientists. Of course, e.g., philosophers and logicians also have been long comfortable with generating new formalisms. I think of Frege here.
So I’m not sure whether formal causal inference is an idea behind its time (or, if so, how far behind). But I’m glad we have it now.
- There is a “lively” debate about the relative value of these formalisms. For many of the dense causal models applicable to the social sciences (everything is potentially a confounder), potential outcomes seem like a good fit. But they can become awkward as the causal models get complex, with many exclusion restrictions (i.e. missing edges). [↩]
- See chapter 5 of Pearl, J. (2009). Causality: Models, Reasoning and Inference. 2nd Ed. Cambridge University Press. [↩]
Ambiguous signals: “the Facebook”
When Facebook was sweeping Stanford in Spring 2004, it wasn’t yet just Facebook — it was [thefacebook.com]. Many of my friends who were undergrads at Stanford around that time (and shortly after) will still refer to it as “The Facebook” or “the facebook dot com”. This usage can be a jokey signal to members of the in-group that one was an early user. This also may signal attendance at one of the universities Facebook was available at early on (e.g., Harvard, Stanford, Yale, Columbia).1
Of course, this signal can fail for various reasons. The audience may not understand — may see “the Facebook” as a grammatical error. Or widespread attention to Facebook’s history (say, via a fictionalized movie) may put many people in possession of the ability to use this signal, even though they weren’t early users and are not alumni at the appropriate universities.
Worse still, for some audiences, this usage might seem to put the speaker in a late-adopting category, rather than an early-adopting one! For example, in President G. W. Bush’s visit to Facebook today, he said he is now on “the Facebook”. So to many ears, “the Facebook” does exactly the opposite of the effects described above.
In fact, at least one friend has had just this experience: she used “the Facebook” and got a “are you a luddite?” kind of response. To avoid ambiguity (but also subtlety), “the facebook dot com” is still available.
- Though it is worth noting that by the time of the domain-name change, many more schools had access to Facebook. But I would guess the likelihood of adoption and attachment to the name is lower. Update: see this more detailed timeline of Facebook university launches. [↩]
Academia vs. industry: Harvard CS vs. Google edition
Matt Welsh, a professor in the Harvard CS department, has decided to leave Harvard to continue his post-tenure leave working at Google. Welsh is obviously leaving a sweet job. In fact, it was not long ago that he was writing about how difficult it is to get tenure at Harvard.
So why is he leaving? Well, CS folks doing research in large distributed systems are in a tricky place, since the really big systems are all in industry. And instead of legions of experienced engineers to help build and study these systems, they have a bunch of lazy grad students! One might think, then, that this kind of (tenured) professor to industry move is limited to people creating and studying large deployments of computer systems.
There is a broader pull, I think. For researchers studying many central topics in the social sciences (e.g., social influence), there is a big draw to industry, since it is corporations that are collecting broad and deep data sets describing human behavior. To some extent, this is also a case of industry being appealing for people studying deployment of large deployments of computer systems — but it applies even to those who don’t care much about the “computer” part. In further parallels to the case with CS systems researchers, in industry they have talented database and machine learning experts ready to help, rather than social science grad students who are (like the faculty) too often afraid of math.