Posts filed under Social Media (61)

February 27, 2015

Siberian hamsters or Asian gerbils

Every year or so there is a news story along the lines of”Everything you know about the Black Death is Wrong”. I’ve just been reading a couple of excellent posts  by Alison Atkin on this year’s one.

The Herald’s version of the story (which they got from the Independent) is typical (but she has captured a large set of headlines)

The Black Death has always been bad publicity for rats, with the rodent widely blamed for killing millions of people across Europe by spreading the bubonic plague.

But it seems that the creature, in this case at least, has been unfairly maligned, as new research points the finger of blame at gerbils.

and

The scientists switched the blame from rat to gerbil after comparing tree-ring records from Europe with 7711 historical plague outbreaks.

That isn’t what the research paper (in PNAS) says. And it would be surprising if it did: could it really be true that Asian gerbils were spreading across Europe for centuries without anyone noticing?

The abstract of the paper says

The second plague pandemic in medieval Europe started with the Black Death epidemic of 1347–1353 and killed millions of people over a time span of four centuries. It is commonly thought that after its initial introduction from Asia, the disease persisted in Europe in rodent reservoirs until it eventually disappeared. Here, we show that climate-driven outbreaks of Yersinia pestis in Asian rodent plague reservoirs are significantly associated with new waves of plague arriving into Europe through its maritime trade network with Asia. This association strongly suggests that the bacterium was continuously reimported into Europe during the second plague pandemic, and offers an alternative explanation to putative European rodent reservoirs for how the disease could have persisted in Europe for so long.

If the researchers had found repeated, prevously unsuspected, invasions of Europe by hordes of gerbils, they would have said so in the abstract. They don’t. Not a gerbil to be seen.

The hypothesis is that plague was repeatedly re-imported from Asia (where affected a lots of species, including, yes, gerbils) to European rats, rather than persisting at low levels in European rats between the epidemics. Either way, once the epidemic got to Europe, it’s all about the rats [update: and other non-novel forms of transmission]

In this example, for a change, it doesn’t seem that the press release is responsible. Instead, it looks like progressive mutations in the story as it’s transmitted, with the great gerbil gradually going from an illustrative example of a plague host in Asia to the rodent version of Attila the Hun.

Two final remarks. First, the erroneous story is now in the Wikipedia entry for the great gerbil (with a citation to the PNAS paper, so it looks as if it’s real). Second, when the story is allegedly about the confusion between two species of rodent, it’s a pity the Herald stock photo isn’t the right species.

 

[Update: Wikipedia has been fixed.]

February 19, 2015

London card clash sensitivity analysis

The data blog of the Daily Mirror reports a problem with ‘card clash’ on the London Underground.  You can now pay directly with a debit card instead of buying a ticket — so if you have both a transport card and a debit card in your wallet, you have the opportunity to enter with one and leave with the other and get overcharged. Alternatively, you can take the card out of your wallet and drop it.  Auckland Transport has a milder version of the same problem: no-touch credit cards can confuse the AT HOP reader and make it not recognise your card, but you won’t get overcharged unless you don’t notice the red light.

They looked at numbers of cards handed in at lost-and-found across the London Underground over the past two years (based on FOI request)

card-clash

If we’re going to spend time on this, we might also consider what the right comparison is. The data include cards on their own and cards with other stuff, such as a wallet. We shouldn’t combine them: the ‘card clash’ hypothesis would suggest a bigger increase in cards on their own.

Here’s a comparison using all the data: the pale points are the observations, the heavy lines are means.

allcards

Or, we might worry about trends over time and use just the most recent four months of comparison data:

recentcards

Or, use the same four months of the previous year:

matchedcards

 

In this case all the comparisons give basically the same conclusion: more cards are being handed in, but the increase is pretty similar for cards alone and for cards with other stuff, which weakens the support for the ‘card clash’ explanation.

Also, in the usual StatsChat spirit of considering absolute risks: there are 3.5 million trips per day, and about 55 cards handed in per day: one card for about 64000 trips. With two trips per day, 320 days per year, that would average once per person per century.

February 15, 2015

Caricatures and credits

 

A lot of surprisingly popular accounts on Twitter just tweet pictures, without giving any sources,and often with captions that misleading or just wrong.  One from yesterday had a picture of a picnic on a highway in the Netherlands in 1973 and described it as being from the US.

Here’s one that came from @AmazingMaps, today, captioned “Most popular word used in online dating profiles by state”

B916Zi9IIAAXAJb

 

Could it really be true that ‘NASCAR’ is the most popular word in Indiana dating profiles? Or that ‘oil’ is the most popular word in Texas? Have the standard personal-ad clichés become completely outdated? Aren’t Americans easy-going any more? Doesn’t anyone care about romance or honesty or humour?

We’ve seen this sort of analysis before on StatsChat. It’s designed to produce a caricature, though not necessarily in a bad way. This one comes from Mashable, based on analysis by Match.com. The original post says

Essentially, they broke down which words are used with relative frequency in certain states, as compared to relative infrequency in the rest of the country.

That is, the map has ‘oil’ for Texas and ‘NASCAR’ for Indiana not because these words were used very often in those states, but because they were used much less often in other states. Most Indiana dating profiles probably don’t mention NASCAR, but a much higher proportion do than in, say, New York or Oregon. Most Texas dating profiles don’t talk about oil, but it’s more common in Texas than in Maine or Tennessee. It’s not that everyone in Oregon or Idaho kayaks, but a lot more do than in Iowa or Kansas.

 

When this map first came out, in November, there were lots of stories about it, typically getting things wrong (eg an NBC motor sports site had the headline “NASCAR” is most frequently used word among Indiana online dating profiles”). That’s still bad, but most of these sites had links or at least mentioned the source of the map, so that people who care could find out what the facts are. @AmazingMaps seems confident none of its followers care.

January 16, 2015

Women are from Facebook?

A headline on Stuff: “Facebook and Twitter can actually decrease stress — if you’re a woman”

The story is based on analysis of a survey by Pew Research (summary, full report). The researchers said they were surprised by the finding, so you’d want the evidence in favour of it to be stronger than usual. Also, the claim is basically for a difference between men and women, so you’d want to see summaries of the evidence for a difference between men and women.

Here’s what we get, from the appendix to the full report. The left-hand column is for women, the right-hand column for men. The numbers compare mean stress score in people with different amounts of social media use.

pew

The first thing you notice is all the little dashes.  That means the estimated difference was less than twice the estimated standard error, so they decided to pretend it was zero.

All the social media measurements have little dashes for men: there wasn’t strong evidence the correlation was non-zero. That’s not we want, though. If we want to conclude that women are different from men we want to know whether the difference between the estimates for men and women is large compared its uncertainty.  As far as we can tell from these results, the correlations could easily be in the same direction in men and women, and could even be just as  strong in men as in women.

This isn’t just a philosophical issue: if you look for differences between two groups by looking separately for a correlation each group rather than actually looking for differences, you’re more likely to find differences when none really exist. Unfortunately, it’s a common error — Ben Goldacre writes about it here.

There’s something much less subtle wrong with the headline, though. Look at the section of the table for Facebook. Do you see the negative numbers there, indicating lower stress for women who use Facebook more? Me either.

 

[Update: in the comments there is a reply from the Pew Research authors, which I got in email.]

January 9, 2015

The Internet of things and its discontents

The current Consumer Electronics Show is full of even more gadgets that talk to each other about you. This isn’t necessarily an unmixed blessing

From the New Yorker

To find out, the scientists recruited more than five hundred British adults and asked them to imagine living in a house with three roommates. This hypothetical house came equipped with an energy monitor, and all four residents had agreed to pay equally for power. One half of the participants was told that energy use in the house had remained constant from one month to the next, and that each roommate had consumed about the same amount. The other half was told that the bill had spiked because of one free-riding, electricity-guzzling roommate.

From Buzzfeed

It’s not difficult to imagine a future in which similar data sets are wielded by employers, the government, or law enforcement. Instead of liberating the self through data, these devices could only further restrain and contain it. As Walter De Brouwer, co-founder of the health tracker Scanadu, explained to me, “The great thing about being made of data is thatdata can change.” But for whom — or what — are such changes valuable?

and the slightly chilling quote “it’s not surveillance, after all, if you’re volunteering for it”
Both these links come from Alex Harrowell at the Yorkshire Ranter, whose comment on smart electricity meters is

The lesson here is both that insulation and keeping up to the planning code really will help your energy problem, rather than just provide a better class of blame, and rockwool doesn’t talk.

 

January 2, 2015

Maybe not a representative sample

The Dominion Post asked motorists why they thought the road toll had climbed, and what should be done about it.

roadtoll

Interestingly, three of the five(middle-aged, white, male ,Wellington area) motorists attributed it to random variation. That’s actually possible: the evidence for a real change in risk nationally is pretty modest (and the Wellington region toll is down on last year).

(via @anderschri5 on Twitter)

Meaningless bignums

From the science journal Nature, who should know better than to quote big-sounding numbers without context.

B6R7QaNCIAI2Qsx

That’s roughly the same number of person-hours as the world spent watching the China Central Television news program Xīnwén Liánbō: estimated at 135 million people for half an hour a day.  Or about 1/3 as much time as spent watching YouTube.

 

December 29, 2014

Set to a possibly recognisable tune

The Risk Song: One hundred and eight hazards in 80 seconds

(via David Spiegelhalter)

December 14, 2014

Statistics about the media: Lorde edition

From @andrewbprice on Twitter: number of articles in the NZ Herald each day about the musician Lorde

lorde

The scampi industry, which brings in similar export earnings (via Matt Nippert), doesn’t get anything like the coverage (and fair enough).

More surprisingly, Lorde seems to get more coverage than the mother of our next head of state but two.  It may seem that the royal couple is always in the paper, but actually whole weeks can sometimes go past without a Will & Kate story.

December 12, 2014

Diversity maps

From Aaron Schiff, household income diversity at the census area level, for Auckland

AKL-income-diversity-better

The diversity measure is based on how well the distribution of income groups in the census area unit matches the distribution across the entire Auckland region, so in a sense it’s more a representativeness measure —  an area unit with only very high and very low incomes would have low diversity in this sense (but there aren’t really any). The red areas are low diversity and include the wealthy suburbs on the Waitemātā harbour and the Gulf, and the poor suburbs of south Auckland. This is an example of something that can’t be a dot map: diversity is intrinsically a property of an area, not an individual

 

From Luis Apiolaza, ethnic diversity in schools across the country

luis-school-diversity

 

This screenshot shows an area in south Auckland, and it illustrates that ‘diversity’ really means ‘diversity’, it’s not just a code word for non-white. The low-diversity schools (white circles) in the lower half of the shot include Westmount School (99% Pākehā), but also Te Kura Māori o Ngā Tapuwae (99% Māori), and St Mary MacKillop Catholic School (90% Pasifika).  The high-diversity schools in the top half of the shot don’t have a majority of students from any ethnic group.