- Poor Economics — this is possibly the best thing I will read all year, an insightful (and research-backed) book digging into the economics of poverty. Read the lecture slides online, they’ll give you a very clear taste of what the book’s about. Love that the website is so very complementary to the book, and 100% aligned with the ambition to convince and spread the word. Kindle-purchasable, too. Sample boggle (one of many): children of children born during the Chinese famine are smaller, and children who were in utero during Ramadan earn less as adults.
- The Web Is Shrinking (All Things D) — graph that makes Facebook look massively important and the rest of the web look insignificant. It doesn’t take into account the nature of the interaction (shopping? research? chat?), and depends heavily on the comScore visits metric being a reliable proxy for “use”. I’d expect to see other neutral measures of “use” decreasing (e.g., searches for “school holidays”) if overall web use were decreasing, yet they don’t seem to be. Nonetheless, Facebook has become the new millennium’s AOL: keywords, grandparents, and a zealous devotion to advertising. At least Facebook doesn’t send me #&#^%*ing CDs.
- Orphan Works Project (University of Michigan) — library will digitize orphaned works for researchers. Lovely to see someone breaking the paralysis that orphaned works induce. (via BoingBoing)
- log.io — node.js system for real-time log monitoring in your browser. (via Vasudev Ram)
"metrics" entries
Mobile analytics unlock the what and the when
Flurry's Sean Byrnes on mobile metrics and tablet apps vs phone apps.
Flurry's CTO Sean Byrnes discusses app life cycles, the specifics of user engagement, and the difference between smartphone apps and tablet apps.
Moneyball for software engineering
How metrics-driven decisions can build better software teams.
Don't dismiss "Moneyball" just because it began in the sports world. Many of the system's metrics-based techniques can also apply to software teams.
When was the last time you mined your site's search data?
Lou Rosenfeld on the benefits of parsing and refining site search.
A gold mine is hiding in the data generated by website search engines, yet many site owners pay little attention to the analytics those engines yield. Author Lou Rosenfeld explains why site search is worth your time.
Mobile metrics: Like the web, but a lot harder
Flurry's Sean Byrnes on the challenges of mobile analytics.
Flurry's Sean Byrnes talks about the intricacies of mobile analytics, the metrics app developers care about most, and the problems that stem from Android fragmentation.
Four short links: 27 June 2011
Poor Economics, Shrinking Web, Orphans Put to Work, Realtime Log Monitoring
Four short links: 18 April 2011
Community, Metrics, Sensors, and Unicode
- Your Community is Your Best Feature — Gina Trapani’s CodeConf talk: useful, true, and moving. There’s not much in this world that has all three of those attributes.
- Metrics Everywhere — another CodeConf talk, this time explaining Yammer’s use of metrics to quantify the actual state of their operations. Nice philosophical guide to the different ways you want to measure things (gauges, counters, meters, histograms, and timers). I agree with the first half, but must say that it will always be an uphill battle to craft a panegyric that will make hearts and minds soar at the mention of “business value”. Such an ugly phrase for such an important idea. (via Bryce Roberts)
- On Earthquakes in Tokyo (Bunnie Huang) — Personal earthquake alarms are quite popular in Tokyo. Just as lightning precedes thunder, these alarms give you a few seconds warning to an incoming tremor. The alarm has a distinct sound, and this leads to a kind of pavlovian conditioning. All conversation stops, and everyone just waits in a state of heightened awareness, since the alarm can’t tell you how big it is—it just tells you one is coming. You can see the fight or flight gears turning in everyone’s heads. Some people cry; some people laugh; some people start texting furiously; others just sit and wait. Information won’t provoke the same reaction in everyone: for some it’s impending doom, for others another day at the office. Data is not neutral; it requires interpretation and context.
- AccentuateUs — Firefox plugin to Unicodify text (so if you type “cafe”, the software turns it into “café”). The math behind it is explained on the dataists blog. There’s an API and other interfaces, even a vim plugin.
Four short links: 4 April 2011
Library Game, Mac Security, Natural Programming, Selecting Metrics
- Find The Future — New York Public Library big game, by Jane McGonigal. (via Imran Ali)
- Enable Certificate Checking on Mac OS X — how to get your browser to catch attempts to trick you with revoked certificates (more of a worry since security problems at certificate authorities came to light). (via Peter Biddle)
- Clever Algorithms — Nature-Inspired Programming Recipes from AI, examples in Ruby. I hadn’t realized there were Artificial Immune Systems. Cool! (via Avi Bryant)
- Rethinking Evaluation Metrics in Light of Flickr Commons — conference paper from Museums and the Web. As you move from “we are publishing, you are reading” to a read-write web, you must change your metrics. Rather than import comments and tags directly into the Library’s catalog, we verify the information then use it to expand the records of photos that had little description when acquired by the Library. […] The symbolic 2,500th record, a photo from the Bain collection of Captain Charles Polack, is illustrative of the updates taking place based on community input. The new information in the record of this photo now includes his full name, death date, employer, and the occasion for taking the photo, the 100th Atlantic crossing as ocean liner captain. An additional note added to the record points the Library visitor to the Flickr conversation and more of the story with references to gold shipments during WWI. Qualitative measurements, like level of engagement, are a challenge to gauge and convey. While resources expended are sometimes viewed as a cost, in this case they indicate benefit. If you don’t measure the right thing, you’ll view success as a failure. (via Seb Chan)
The CIO's golden rule of management
With few exceptions, good data is the best way to make great decisions.
We make decisions with data and we measure performance with metrics. It's letting the data and metrics — the evidence — tell the story and then taking some form of action on it.
Four short links: 17 November 2010
Data Metrics, AR Intervention, Facebook Export, and Android ROMs
- Understanding Your Customers — I enjoyed Keith’s take on meaningful metrics. We talk a lot about being data-driven, but we interpret data with a model. The different take on meaningful metrics reflect the different underlying models that are lit up by data. It’s an important idea for the Strata conference, that gathering and processing data happens in the context of a world view, a data cosmology. (via Eric Ries)
- Bushwick AR Intervention 2010 — an augmented reality take over of Bushwick, Brooklyn NY. Artists will rework physical space with computer generated 3d graphics. A wide variety of works ranging from a virtual drug which has broken free of its internet constraints and is now effecting people in the real world, to a unicorn park, to serious commentary on the state of United States veterans will be free for the public to view [with correct mobile device]. (via Laurel Ruma)
- How to Mass Export all of your Facebook Friends’ Private Email Addresses (TechCrunch) — Arrington gives a big finger to Facebook’s “no, you can’t export your friends’ email addresses” policy by using the tools they provide to do just that. Not only is this useful, it also points out the hypocrisy of the company.
- TaintDroid — an Android ROM that tracks what apps do with your sensitive information. (via Brady Forrest on Twitter)
Open source givers and takers
Taking without giving isn't the problem. We need better open source contribution metrics.
We need better metrics to adequately gauge corporate participation in open source. For example: How many companies have employees who work on open source projects on their own time or company time, unbeknownst to the managers who fill out surveys?