Posts filed under Social Media (95)

The Herald says

Almost four in 10 young UK adults describe themselves as digital addicts, according to research published by Foresters, the financial services company.

The story does quote an independent expert who is relatively unimpressed with the definition of ‘digital addict’, but it doesn’t answer the question ‘what sort of research?”

Via Google, I found a press release of a digital addiction survey promoted by Foresters. It’s not clear if the current story is based on a new press release from this survey or a new version of the survey, but the methodology is presumably similar.

So, what is the methodology?

Over 1,100 people across the UK responded to an online survey in November 2013 , conducted by Wriglesworth Research

There’s also a related press release from Wriglesworth, but without any more methodological detail. If I Google for “wriglesworth survey”, this is what comes up

That is, the company is at least in the habit of conducting self-selected online polls, advertised on web forums and Twitter.

I tried, but I couldn’t find any evidence that the numbers in this online survey were worth the paper they aren’t written on.

From Cathy O’Neil: Ignore data, focus on power (and, well, most of the stuff on her blog)

From danah boyd and Kate Crawford: Critical Questions for Big Data

[Update: 538 now has an intro to the story explaining the mistakes and apologising. Good for them.]

So, at  fivethirtyeight.com there’s this story on mapping kidnappings in Nigeria using data from GDELT, the sort of thing data journalism is supposed to be good at. GDELT automatically extracts information from news stories to build a huge global database.

On Twitter, Erin Simpson, whose about.me page says she is “a leading specialist in the intersection of intelligence, data analysis, irregular warfare, and illicit systems – with an emphasis on novel research designs,” — and who has worked on the GDELT parser — is Not Happy.

Thanks to Storify, here are three summaries of what she says, but a lot of it can be boiled down to one point:

In conclusion: VALIDATE YOUR FREAKING DATA. It’s not true just because it’s on a goddamn map.

(via @LewSOS)

There’s a new report “Big Data: Seizing Opportunities, Preserving Values” from the Office of the President (of the USA).  Here’s part of the conclusion (there are detailed recommendations as well)

Big data tools offer astonishing and powerful opportunities to unlock previously inaccessible insights from new and existing data sets. Big data can fuel developments and discoveries in health care and education, in agriculture and energy use, and in how businesses organize their supply chains and monitor their equipment. Big data holds the potential to streamline the provision of public services, increase the efficient use of taxpayer dollars at every level of government, and substantially strengthen national security. The promise of big data requires government data be viewed as a national resource and be responsibly made available to those who can derive social value from it. It also presents the opportunity to shape the next generation of computational tools and technologies that will in turn drive further innovation.

Big data also introduces many quandaries. By their very nature, many of the sensor technologies deployed on our phones and in our homes, offices, and on lampposts and rooftops across our cities are collecting more and more information. Continuing advances in analytics provide incentives to collect as much data as possible not only for today’s uses but also for potential later uses. Technologically speaking, this is driving data collection to become functionally ubiquitous and permanent, allowing the digital traces we leave behind to be collected, analyzed, and assembled to reveal a surprising number of things about ourselves and our lives. These developments challenge longstanding notions of privacy and raise questions about the “notice and consent” framework, by which a user gives initial permission for their data to be collected. But these trends need not prevent creating ways for people to participate in the treatment and management of their information.

You can also read comments on the report by danah boyd, and the conference report and videos from her conference’The Social, Cultural & Ethical Dimensions of “Big Data”‘ are now online.

Heavy drinking and the societal harm it causes is a big issue and attracts a lot of media and scholarly attention (and Statschat’s, too). So we were interested to see today’s new release from the Journal of the American Medical Association. It describes a double-blind, parallel-group, individually-randomised trial that studied moderate to heavy student drinkers from seven of our eight universities to see if a web-based alcohol screening and intervention programme reduced their unhealthy drinking behaviour.

And the short answer? Not really. But if they identified as Māori, the answer was … yes, with a caveat. More on that in a moment.

Statistician Nicholas Horton and colleagues used an online questionnaire to identify students at Otago, Auckland, Canterbury, Victoria, Lincoln, Massey, and Waikato who had unhealthy drinking habits. Half the students were assigned at random to receive personalised feedback and the other students had no input. Five months later, researchers followed up with the students on certain aspects of their drinking.

The overall result? “The intervention group tended to have less drinking and fewer problems then the control group, but the effects were relatively modest,” says Professor Horton. The take-away message: A web-based alcohol screening and intervention program had little effect on unhealthy drinking among New Zealand uni students. Restrictions on alcohol availability and promotion are still needed if we really want to tackle alcohol abuse.

But among Māori students, who comprise 10% of our national uni population, those receiving intervention were found to drink 22% less alcohol and to experience 19% fewer alcohol-related academic problems at the five-month follow-up. The paper suggests that Māori students are possibly more heavily influenced by social-norm feedback than non-Māori students. “Māori students may have a stronger group identity, enhanced by being a small minority in the university setting.” But the paper warns that the difference could also be due to chance, “underscoring the need to undertake replication and further studies evaluating web-based alcohol screening and brief intervention in full-scale effectiveness trials.”

The paper is here. Read the JAMA editorial here.

A California head-lice treatment business has had huge success in publicising its business with the claim that selfies are causing a  rise in nits among teenagers. The Herald mentions this in Sideswipe, the right place for this sort of story, but other international sites have been less discriminating.

There are no actual numbers involved, and nothing like representative data even if you’re in the South Bay area of central California. More importantly, though, there is no comparison group. The owner of the business, Mary MacQuillan, says “Every teen I’ve treated, I ask about selfies, and they admit that they are taking them every day.”  That’s probably only a slight exaggeration at most, but every teen she hasn’t treated has also probably been taking photos that way. It’s something teenagers do.  Common exposures are common.

So, why were news organisations around the world publicising this? The fact that it’s about teenagers and the internet goes a long way to explaining it.  It doesn’t need evidence because teenage use of technology is automatically scary and newsworthy: as Ms MacQuillan says ” I think parents need to be aware, and teenagers need to be aware too. Selfies are fun, but the consequences are real.”

You get the same thing happening with ‘chemicals’, as the dihydrogen monoxide parody website loves to point out

A recent stunning revelation is that in every single instance of violence in our country’s schools, …, dihydrogen monoxide was involved.

If you have time, there’s an interesting event that will be streamed from New York University this (NZ) morning (10:30am today NZ time, 5:30pm yesterday NY time)

..the Data & Society Research Institute, the White House Office of Science and Technology Policy, and New York University’s Information Law Institute will be co-hosting a public event entitled The Social, Cultural, & Ethical Dimensions of “Big Data.” The purpose of this event is to convene key stakeholders and thought leaders from across academia, government, industry, and civil society to examine the social, cultural, and ethical implications of “big data,” with an eye to both the challenges and opportunities presented by the phenomenon.

The event is being organised by danah boyd, who we’ve mentioned a few times and whose new book I plan to write about soon.

A new blog of science-themed links and (NZ) event listings, Science Club.

Their most recent  post is for this story from the Guardian, which reports that one in every thirteen tweets contains swearing.

What do you think is the most commonly used swearword on Twitter? Well of course it is

There is, of course, substantial variation between users. Most of the people I follow are dragging the average down.

There’s a map going around Twitter, being described as the most popular band in each US state

Here’s the band that each state likes the most http://t.co/ANVw7ofA1s pic.twitter.com/HyI2u537rp

— Joseph Weisenthal (@TheStalwart) February 25, 2014

It’s a bit surprising that every state has a different favourite band, so I looked at the site listed on the map as the source.  In fact, the listed bands are not the most popular ones in any of the states. They are something more interesting.

Paul Lamere used Spotify (and perhaps other social music-streaming services) to get music listening preferences for 200000 people. He then looked at which artist in the top 100 for a state had the worst ranking over the US as a whole. He forced the result to be different for every state by bumping the less-populous state to its next choice when there was a tie. So, as the title on the map actually says, these are the most distinctive bands for a state, not the most popular.  They are caricatures, not photographs.

Since he had data based on postal code (ZIP code), it’s a pity he grouped these all the way up to the state level.  It would have been interesting to see urban vs suburban vs rural differences, and the major geographical trends across states such as Texas.

A maths-free article on data mining and surveillance, from the New York Review of Books

Using techniques ranging from supermarket loyalty cards to targeted advertising on Facebook, private companies systematically collect very personal information, from who you are, to what you do, to what you buy. Data about your online and offline behavior are combined, analyzed, and sold to marketers, corporations, governments, and even criminals. The scope of this collection, aggregation, and brokering of information is similar to, if not larger than, that of theNSA, yet it is almost entirely unregulated and many of the activities of data-mining and digital marketing firms are not publicly known at all.