Archive for December, 2011

How the poor debtors still sell their daughters, How in the drought men still grow fat

| Gabriel |

[Update 12/18/2012: Struck through the bit about Apple because I think people make way too big of a deal about this. It’s an isolated mistake in a very long book, big deal. I used strike-through rather than out-right deleting it to preserve the record. On the other hand I stand by my criticism of the “tribute” thesis of chapter 12 as this is not nitpicking but a substantive disagreement with a sustained argument. In retrospect I might have changed a word here or there in my take on “tribute,” but overall I think my argument holds up.] 

I recently read Graeber’s Debt: The First Five Thousand Years and found it to be very impressive and thought-provoking. As an indication of how impressed I was, I’ll just say that: I’ve recommended it to several people, I’m citing it in one of my next papers, I’m very seriously considering assigning it as a text when I prep econ soc sometime in the next couple years, and it inspired me to go back and read The Gift by Mauss and several journal articles. I’d long been vaguely aware of the anthropology of exchange through my exposure to Zelizer and Fiske, but had never read very deeply in it and so I learned a lot. Debt is written as “big history” (not unlike JLM’s Social Structures and Fukuyama’s OoPO) and this gives it a different character than the more cross-sectional approaches taken by Mauss, Zelizer, or Fiske.

Large parts of the book could better be called Commerce: The First 5,000 Years or Exchange: The First 5,000 Years. However there are a few places where Graeber explicitly tackles debt. The most widely known of these (in part because Graeber opened a can of whup-ass on some guy at Mises who tenaciously stuck to the discredited view) is the origins of money. The received view from Adam Smith which still persists in econ textbooks is that primordial exchange takes the form of barter but that barter suffers from the “double coincidence of wants” problem wherein A can only trade with B if A has something B desires and vice versa. In this model, money lubricates exchange by creating a universal medium of exchange. As Graeber shows, this model of pre-monetized exchange assumes arms-length transactions whereas almost all documented exchange in primitive cultures is thoroughly embedded and takes one form or another of communal sharing or gift exchange. That is, delayed reciprocity is typical and this avoids the problem of coincidence of wants. From the economist’s perspective delayed reciprocity introduces further issues of trust, time preference, etc and thus is a more complex form of exchange than barter, but this is because (at least on this issue) economists are acting as arm chair philosophers of the social contract and it is the anthropologists who are (at least on this issue) being good empiricists.

The important exception to the “barter is a myth” point is that Graeber argues that arms-length exchange does occur in primitive cultures, but only between and not within meaningful social units and that such arms-length exchange is somewhat sketchy and dangerous. More broadly, one of the central points of the book is that arms length exchange in general and market economies in particular require the disembedding of people and commodities from their social context. Graeber sees this process as often violent and he makes a powerful argument that this originates with slavery, both in antiquity and in early modern Africa.

Other interesting points he makes on debt are various ways that it becomes a moral obligation such that debtors are seen as sinners and religious salvation is seen as a spiritual analog to redemption. This helps explain something I never completely understood when watching The Sopranos, which is why gangsters first go to the trouble of getting someone to incur an illegal debt before shaking them down? It turns out that the point of loan-sharking instead of mere naked extortion is the victim feels a certain moral obligation to repay the debt and so loan sharks exploiting gambling addicts has the same logic as how many grifts (e.g., 419 advanced-fee fraud, the fiddle game, etc.) first involve the victim as co-conspirator in a crime against a real or imagined third party. Moreover, Graeber makes the bold point towards the end of the book that debt can drive people to do things that they otherwise would be morally averse to, with his example being the conquistadores.

This is all fascinating but it depends a lot on how much you trust Graeber’s empirical claims. For instance, was it really true that everyday economic life in early modern Britain was largely cashless and instead used a combination of token currencies, informal credit, and asynchronous barter? Maybe, I really don’t know. I’d like to trust Graeber on this but I don’t know if I can since he gets some things pretty wrong, or at least dubious. At Unfogged there’s a review (and a very funny comments thread) pointing out that the following sentence contains six factual claims all of which are incorrect:

Apple Computers is a famous example: it was founded by (mostly Republican) computer engineers who broke from IBM in Silicon Valley in the 1980s, forming little democratic circles of twenty to forty people with their laptops in each other’s garages.

This is not exactly stuff written in the cuneiform of Mesopotamian diplomacy, the barbarian law codes of mediaeval Ireland, or the field notes of Victorian anthropologists, but something that occurred in suburban California around the time I was born and concerns the extremely well documented origins of one of the world’s biggest firms. If Graeber gets this wrong, how can we trust him about the stuff that’s harder to check, like all that business about barbarian law codes.

The thing that really bothers me though (because it’s more than an isolated sentence) is the last few chapters, which argue that America’s current account deficit constitutes military tribute. He means this literally. For instance, he suggests that the Iraq War was punishment for Iraq switching to the euro — meanwhile back in reality the euro area itself overlaps pretty closely with NATO and several eurozone countries invaded Iraq together with the United States. I guess we’ve just been too busy punishing Iraq for using euros to get around to dropping a few bombs on the European Central Bank which actually issues those euros. (This is pretty strange since the ECB is just a few minutes of flight time from a massive USAF base, so bombing it would be a very convenient way to ensure the continued flow of tribute).

When I first read this military tribute argument in the early 1990s (in Chomsky’s Deterring Democracy) it made a lot of sense to me, but two things were different then:

  1. I was a lot younger, less informed about economics, and more paranoid in my political thinking.
  2. In the early 1990s the US government’s major foreign debt holders were countries that could plausibly be described as military protectorates (Japan, South Korea, Saudi Arabia, etc.). Now the single largest holder of US government debt is the People’s Republic of China. For those of you following at home, China is most certainly not a US military protectorate but our major geostrategic rival against whom a post-GWOT DOD is orienting its strategic doctrine.

Graeber addresses problem #2 head on and tries to explain this away by some convoluted argument that I can’t even reproduce but I find his argument much less plausible than the more parsimonious explanation that the Chinese are buying t-bills (a) as a store of value (b) as a medium of exchange and (c) as a tacit export subsidy that suits their domestic politics. That is, they buy t-bills for basically the same reasons as everybody else, including those countries where we have Air Force or Navy bases. This deliberate obtuseness about how a reserve currency works and the paranoid understanding that it is provincial tribute is by far the worst part of the book. I’m trying to draw a fact/value distinction between my lack of sympathy for his political positions and his empirical claims as I’d like to think that when reading someone with whom I disagree I can distinguish between their empirical claims that are well-supported, debatable, and downright nuts. That is to say I don’t think these chapters upset me because they are normatively “anti-American” but because as an empirical matter they badly fail to understand how (for better or worse) American power works.

This business about tribute is at the end so I’d like to say that I recommend the book but that you stop on page 365, right before he gets his Chomsky on, but I honestly worry whether I can trust the parts of the book I’m not as informed about. This is the 13th chime of the clock, the brown M&Ms in the Van Halen dressing room; pick your metaphor, but this business about Apple computer and especially about Chinese t-bill holdings ultimately makes me take a “trust but verify” attitude towards a book that I found both extremely enjoyable and intellectually inspirational as I was reading it. My recommendation is that people interested in exchange read the book, but do so with an appropriate degree of skepticism and look to see reactions from historians and anthropologists who are qualified to assess the empirical claims. Also see other reviews at Understanding Society and OrgTheory. [Update 2/23/12, also see the Crooked Timber symposium. Like all of their book clubs it’s truly excellent]

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December 29, 2011 at 8:01 am 21 comments

Is Facebook “Naturally Occurring”?

| Gabriel |

Lewis, Gonzalez, and Kaufman have a forthcoming paper in PNAS on “Social selection and peer influence in an online social network.” The project uses Facebook data from the entire college experience of a single cohort of undergrads at one school in order to pick at the perennial homophily/influence question. (Also see earlier papers from this project).

Overall it’s an excellent study. The data collection and modeling efforts are extremely impressive. Moreover I’m very sympathetic to (and plan to regularly cite) the conclusion that contagious diffusion is over-rated and we need to consider the micro-motives and mechanisms underlying contagion. I especially liked how they synthesize the Bourdieu tradition with diffusion to argue that diffusion is most likely for taste markers that are distinctive in both sense of the term. As is often the case with PNAS or Science, the really good stuff is in the appendix and in this case it gets downright comical as they apply some very heavy analytical firepower to trying to understand why hipsters are such pretentious assholes before giving up and delegating the issue to ethnography.

The thing that really got me thinking though was a claim they make in the methods section:

Because data on Facebook are naturally occurring, we avoided interviewer effects, recall limitations, and other sources of measurement error endemic to survey-based network research

That is, the authors are reifying Facebook as “natural.” If all they mean is that they’re taking a fly on the wall observational approach, without even the intervention of survey interviews, then yes, this is naturally occurring data. However I don’t think that observational necessarily means natural. If researchers themselves imposed reciprocity, used a triadic closure algorithm to prime recall, and discouraged the deletion of old ties; we’d recognize this as a measurement issue. It’s debatable whether it’s any more natural if Mark Zuckerberg is the one making these operational measurement decisions instead of Kevin Lewis.

Another way to put this is to ask where does social reality end and observation of it begin? In asking the question I’m not saying that there’s a clean answer. On one end of the spectrum we might have your basic random-digit dialing opinion survey that asks people to answer ambiguously-worded Likert-scale questions about issues they don’t otherwise think about. On the other end of the spectrum we might have well-executed ethnography. Sure, scraping Facebook isn’t as unnatural as the survey but neither is it as natural as the ethnography. Of course, as the information regimes literature suggests to us, you can’t really say that polls aren’t natural either insofar as their unnatural results leak out of the ivory tower and become a part of society themselves. (This is most obviously true for things like the unemployment rate and presidential approval ratings).

At a certain point something goes from figure to ground and it becomes practical, and perhaps even ontologically valid, to treat it as natural. You can make a very good argument that market exchange is a social construction that was either entirely unknown or only marginally important for most of human history. However at the present the market so thoroughly structures and saturates our lives that it’s practical to more or less take it for granted when understanding modern societies and only invoke the market’s contingent nature as a scope condition to avoid excessive generalization of economics beyond modern life and into the past, across cultures, and the deep grammar of human nature.

We are, God help us, rapidly approaching a situation where online social networks structure and constitute interaction. Once we do, the biases built into these systems are no longer measurement issues but will be constitutive of social structure. During the transitional period we find ourselves in though, let’s recognize that these networks are human artifices that are in the process of being incorporated into social life. We need a middle ground between “worthless” and “natural” for understanding social media data.

December 22, 2011 at 11:07 am 16 comments

Scraping Using twitteR (updated)

| Gabriel |

Last time I described using the twitteR library for R. In that post I had R itself read over a list to loop. In this post I make the have looping occur in Bash with argument passing to R through the commandArgs() function.

First, one major limitation of using Twitter is that it times you out for an hour after 150 queries. (You can double this if you use OAuth but I’ve yet to get that to work). For reasons I don’t really understand, getting one feed can mean multiple queries, especially if you’re trying to go far back in the timeline. For this reason you need to break up your list into a bunch of small lists and cron them at least 80 minutes apart. This bit of Bash code will split up a file called “list.txt” into several files. Also, to avoid trouble later on, it makes sure you have Unix EOL.

split -l 50 list.txt short_tw
perl -pi -e 's/\r\n/\n/g' short_tw*

The next thing to keep in mind is that you’ll need to pass arguments to R. Argument passing is when a script takes input from outside the script and processes it as variables. The enthusiastic use of argument passing in Unix is the reason why there is a fine line between a file and a command in that operating system.

In theory you could have R read the target list itself but this crashes when you hit your first dead URL. Running the loop from outside R makes it more robust but this requires passing arguments to R. I’d previously solved this problem by having Stata write an entire R script, which Stata understood as having variables (or “macros”) but which from R’s perspective was hard-coded. However I was recently delighted to discover that R can accept command-line arguments with the commandArgs() function. Not surprisingly, this is more difficult than $1 in Bash, @ARGV in Perl, or `1′ in Stata, but it’s not that bad. To use it you have to use the “–args” option when invoking R and then inside of R you use the commandArgs() function to pass arguments to an array object, which behaves just like the @ARGV array in Perl.

Here’s an R script that accepts a Twitter screenname as a command-line argument, uses the twitteR library to collect that feed, and then saves it as a tab-delimited text file of the same name. (It appends if there’s an existing file). Also note that (thanks to commenters on the previous post) it turns internal EOL into regular spaces. It’s currently set to collect the last 200 tweets but you can adjust this with the third line (or you could rewrite the script to make this a command-line argument as well).

args <- commandArgs(trailingOnly = TRUE)
library(twitteR)
howmany <- 200 #how many past tweets to collect

user <- args[1]
outputfile <- paste('~/project/feeds/',user,'.txt',sep="")
print(user)
print(outputfile)

tmptimeline <- userTimeline(user,n=as.character(howmany))
tmptimeline.df <- twListToDF(tmptimeline)
tmptimeline.df$text <- gsub("\\n|\\r|\\t", " ", tmptimeline.df$text)
write.table(tmptimeline.df,file=outputfile,append=TRUE,sep="\t",col.names=FALSE)

quit()

To use the script to get just a single feed, you invoke it like this from the command-line.

R --vanilla --args asanews < datacollection.R

Of course the whole reason to write the script this way is to loop it over the lists. Here it is for the list “short_twaa”.

for i in `cat short_twaa`; do R --vanilla --args $i < datacollection.R ; done

Keep in mind that you’ll probably want to cron this, either because you want a running scrape or because it makes it easier to space put the “short_tw*” files so you don’t get timed out.

December 20, 2011 at 11:04 pm 1 comment

Scraping Using twitteR

| Gabriel |

Previously I’d discussed scraping Twitter using Bash and Perl. Then yesterday on an orgtheory thread Trey mentioned the R library twitteR and with some help from Trey I worked out a simple script that replaces the twitterscrape_daily.sh and twitterparse.pl scripts from the earlier workflow. The advantage of this script is that it’s a lot shorter, it can get an arbitrary number of tweets instead of just 20, and it captures some of the meta-text that could be useful for constructing social networks.

To use it you need a text file that consists of a list of Twitter feeds, one per line. The location of this file is given in the “inputfile” line.

The “howmany” line controls how many tweets back it goes in each feed.

The “outputfile” line says where the output goes. Note that it treats it as append. As such you can get some redundant data, which you can fix by running this bash code:

sort mytweets.txt | uniq > tmp
mv tmp mytweets.txt

The outputfile has no headers, but they are as follows:

#v1 ignore field, just shows number w/in query
#v2 text of the Tweet
#v3 favorited dummy
#v4 replytosn (mention screenname)
#v5 created (date in YMDhms)
#v6 truncated dummy
#v7 replytosid
#v8 id
#v9 replytouid
#v10 statussource (Twitter client)
#v11 screenname

Unfortunately, the script doesn’t handle multi-line tweets very well, but I’m not sufficiently good at R to regexp out internal EOL characters. I’ll be happy to work this in if anyone cares to post some code to the comments on how to do a find and replace that zaps the internal EOL in the field tmptimeline.df$text.

library(twitteR)
howmany <- 30 #how many past tweets to collect
inputfile <- "~/feedme.txt"
outputfile <- "~/mytweets.txt"

feeds <- as.vector(t(read.table(inputfile)))
for (user in feeds) {
	tmptimeline <- userTimeline(user,n=as.character(howmany))
	tmptimeline.df <- twListToDF(tmptimeline)
	write.table(tmptimeline.df,file=outputfile,append=TRUE,sep="\t",col.names=FALSE)
}

Finally, if you import it into Stata you’ll probably want to run this:

drop v1
ren v2 text
ren v3 favorited 
ren v4 replytosn
ren v5 created
ren v6 truncated 
ren v7 replytosid
ren v8 id
ren v9 replytouid
ren v10 statussource
ren v11 screenname
gen double timestamp=clock(subinstr(created,"-","/",.),"YMDhms")
format timestamp %tc

December 13, 2011 at 1:21 pm 5 comments

Mainstream

| Gabriel |

I recently read Frédéric Martel’s book Mainstream and my initial reaction was shock to discover that I can still read French this many years out from lycée. After I got over that I was able to have a more substantive reaction which was that I really liked it. First there is the sheer scale of the book. He did hundreds of interviews, many of them with extremely high-placed people who I can’t even imagine trying to get access to. He covers pretty much every media industry you can think of and gives a good overview of each. (I know most of the industries he describes pretty well and concur with his descriptions). The first half of the book is primarily concerned with the US media industry and the second half with globalization. In addition to the sheer wealth of detail there is a consistent thesis which is that there is such a thing as a global mass culture centered in America, but there is also a multi-polar nature to this with things like telenovelas, Bollywood, and K-pop circulating within their  respective regional spheres.

My copy of the book visiting Disneyland

On the subject of theme, it’s worth noting that different editions of the book have different subtitles. The original subtitle translates to “inquiry into the culture that pleases everyone” (actually, it’s a pun that can also be translated as “inquiry into the culture that pleases the whole world”). The paperback’s subtitle is “inquiry into the global war over culture and media.” The subtitles of various translated editions follow one or the other. I find the original subtitle to be a better description of the book, especially the first half. However throughout the book there is an appreciation for the politics of media globalization. For instance, there is lengthy discussion of US trade policy and piracy, censorship in various countries, Chinese film import quotas (which can be effective leverage for censorship), etc. This interest in both the comparative and IR politics of cultural production is not only important but Frédéric is in a good position to understand and explain it, having been a cultural attache posted to Boston and remaining a cultural policy intellectual associated with the socialist party.

Even in my semi-literacy with the French language I was able to pick up on how good the writing style is. In a lot of ways Frédéric reminds me of Tom Wolfe. That is, they are both PhD sociologists by background but this perspective is implicit rather than explicit and their writing style is exuberant, with the narrative jumping from location to location every two pages and with an occasional pause to savor absurdity. Likewise, in both cases the thesis gradually swirls into view out of a vortex of detail.

The book has been translated into several languages already and I hope it gets an English translation, but if you can read French and are interested in the culture industries and/or globalization you might want to check out the original rather than waiting. (I found it well worth it to read the original even though I read about half as fast in French as I do in English).

FWIW, Frédéric is a friend of mine and gave me the book when I visited him in June. I’ve been looking forward to this book since I saw him in LA a few years ago when he was doing the field work for the book and in particular I remember the “WRITER” t-shirt he mentions in the book.

Finally, there seems to be something of an arbitrage opportunity for selling foreign books in the US. The paperback goes for 9 euros in France, but the remailers who list on Amazon.com offer it for $30. I would be surprised if the marginal cost of forwarding a book from France to the US is actually $18. I doubt that it’s inventory costs either as they make you wait 10 days which implies that it’s an on-demand service.

December 5, 2011 at 10:18 am


The Culture Geeks