Describes 3 examples of ways crowdsourcing helped after the major quake in Nepal last year.
In the wake of the 7.8 magnitude earthquake that hit their country over the weekend, many Nepalis at home and abroad have found a new way to help — as digital volunteers, spending hours hunched over their laptops, using crowdsourcing technologies and social platforms to participate in the relief effort.
More at New York Times.
(Contributor: Jessica Lee)
Wikipedia announced on Thursday that it is collaborating with researchers from Sweden’s KTH Royal Institute of Technology to develop an open, crowdsourced speech engine that will make the online encyclopedia more accessible to people with reading or visual impairments. Wikipedia estimates that 25 percent of its user base — approximately 125 million people monthly — will benefit from the new service. And while the engine will be optimized for use on Wikipedia itself, any site running MediaWiki software will be able to integrate it as well.
Sadly,
“Initially, our focus will be on the Swedish language, where we will make use of our own language resources,” KTH speech technology professor Joakim Gustafson, said in a statement.
More at Engadget.
(Contributor: Jessica Lee)
Outgoogling Google on flu:
With big data comes big noise. Google learned this lesson the hard way with its now kaput Google Flu Trends. The online tracker, which used Internet search data to predict real-life flu outbreaks, emerged amid fanfare in 2008. Then it met a quiet death this August after repeatedly coughing up bad estimates.
But big Internet data isn’t out of the disease tracking scene yet.
With hubris firmly in check, a team of Harvard researchers have come up with a way to tame the unruly data, combine it with other data sets, and continually calibrate it to track flu outbreaks with less error. Their new model, published Monday in the Proceedings of the National Academy of Sciences, out-performs Google Flu Trends and other models with at least double the accuracy. If the model holds up in coming flu seasons, it could reinstate some optimism in using big data to monitor disease and herald a wave of more accurate second-generation models.
More at ArsTechnica.
(Contributor: Natch Ruengsakulrach)
A google doc for cataloging street food carts in India.
These are old style establishments and therefore don’t have an address, they can’t be found on apps like Yelp or Zomato. The problem this solves is, because these establishments don’t really do any marketing or advertisements, they are hard to discover.
Sometimes simple solutions are the best: https://docs.google.com/spreadsheets/d/1r0TExc9AxJmI9sGDHV4Ufjm77yy2RVoxQaYKpIBjBNk.
(Contributor: Chethan Krishna Nagaraja Rao)
Crowdsourcing the weather experience via your phone:
When it comes to the weather, there is no lack of applications to choose from to get your information. But there is very little diversity when it comes to those apps.
A new startup, called Sunshine, is looking to change all that. Using information delivered from the barometer sensor in the phone, as well as user-generated reports of local weather, the app is trying to change the way we consume information about the day’s weather.
More at TechCrunch.
(Contributor: Chethan Krishna Nagaraja Rao)
One example of human computation in citizen science is Feederwatch, here at Cornell’s Lab of Ornithology.
Project FeederWatch is a winter-long survey of birds that visit feeders at backyards, nature centers, community areas, and other locales in North America. FeederWatchers periodically count the birds they see at their feeders from November through early April and send their counts to Project FeederWatch. FeederWatch data help scientists track broadscale movements of winter bird populations and long-term trends in bird distribution and abundance.
More at the Feederwatch website.
(Contributor: Andrew Mullen)
An article about a thought piece that appeared in Science on using human computation in citizen science:
Combining human and computer intelligence could help solve the world’s most vexing problems, researchers envisioned in an article published Monday in the journal Science.
It refers to examples we’ve discussed in class, such as FoldIt.
More at TechNewsWorld.
(Contributor: Andrew Mullen)
Again, not exactly crowdsourcing, but it shows how lower organisms can use simple mechanisms to create collective action — in this case, respond to threats based on their size:
Many birds and mammals sound alarms to let others know they’ve spotted a predator. Some species even modulate their alarm calls, increasing the pitch or frequency depending on the size and distance of the attacker. Now, scientists have discovered that Asian honey bees (Apis cerana) also tune their signals to tell their hive-mates about the type and degree of danger and the context. It’s the first time that such sophisticated alarm signaling has been found in a social insect.
More at Science.
(Contributor: Haym Hirsh)
The paper is about mapping a small portion of the brain. What’s interesting is the use of crowdsourcing to generate the mapping:
To map the roughly 1300 connections, or synapses, between the cells, researchers used an electron microscope to take millions of nanoscopic pictures from a speck of tissue not much bigger than a dust mite, carved into nearly 3700 slices. Then, teams of “annotators” traced the spindly projections of the synapses, digitally stitching stacked slices together to form the 3D map.
More at Science.
(Contributor: Haym Hirsh)
Discusses Netflix’s positioning itself for the future, starting with a discussion about being driven by user data — even down to picking the image to use for its offerings:
The instant Daredevil premiered, Netflix greeted its users with eight header image variations of Matt Murdock and friends, shown to customers in eight identically sized chunks. Netflix immediately began tracking which top shots inspired the most streaming.
By now, those eight images will have given way to the best-performing two or three. After 35 days, one of those will become the default. The rest will vanish. This happens now for every Netflix original show. It’s survival of the clickest, all around the world.
More at Wired.
(Contributor: Haym Hirsh)
Crowdsourcing and Human Computation 