Stephen Wolfram’s longitudinal fables


There’s lots of interesting plots on Stephen Wolfram’s analysis of Facebook data, but what jumps out to me is the way he feels compelled to turn his cross-sectional data — information about people’s interests, structure of friendship networks, relationship status, etc. as a function of age — into a longitudinal story. For example, he describes this plotrelationship-status-vs-age2

by saying “The rate of getting married starts going up in the early 20s[…] and decreases again in the late 30s, with about 70% of people by then being married.” Now, this is more or less a true statement, but it’s not really what is being illustrated here. (And it’s not just the weird anomaly, which he comments on but doesn’t try to explain, of the 10% or so of Facebook 13 year olds who describe themselves as married.) What we see is a snapshot in time — a temporal cross section, in the jargon — rather than a description of how the same people (a cohort, as demographers would put it) moves through life. To see how misleading this cross-sectional picture can be if you try to see it as a longitudinal story of individuals moving through life, think first about the right-hand side of the graph. It is broadly true, according to census data, that about 80% of this age group are married or widowed. But it is also true that 95% were once married. In fact, if they had had Facebook when they were 25 years old, their Stephen Wolfram would have found that most of them (about 75%) were already married by that age. (In fact, about 5% of the women and 3% of the men were already in a second marriage by age 25.)

So, the expansion of the “married” segment of the population as we go from left to right reflects in part the typical development of a human life, but it reflects as well the fact that we are moving back in time, to when people were simply more likely to marry. And the absence of a “divorced” category masks the fact that while the ranks of the married expand with age, individuals move in and out of that category as they progress through their lives.

Of course, the same caveat applies to the stories that Wolfram tells about his (quite fascinating) analyses of structure of friend networks by age, and of the topics that people of different ages refer to in Facebook posts. While it is surely true that the surge in discussion of school and university centred at age 18 reflects life-phase-determined variation in interests, the extreme drop in interest in salience of social media as a topic is likely to reflect a generational difference, and the steep increase in prominence of politics with age may be generational as well. (I wonder, too, whether the remarkably unchanging salience of “books” might reflect a balance between a tendency to become less involved with books with age, cancelling out a generational shift away from interest in books.)

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