Research Methods Links: September 2012

Tuesday, September 25, 2012

Evaluating Design Patterns

The Effects of Design Pattern Application on Metric Scores
http://users.uom.gr/~achat/articles/Patterns_Metrics.pdf

A Quantitative Approach for Evaluating the Quality of Design Patterns
http://gannodss.csamu.org/diesel/images/1/10/Hsueh_Nien-Lin.pdf

Selection of Metrics for Predicting the Appropriate Application of Design Patterns
http://patterns-wg.fuka.info.waseda.ac.jp/asianplop/proceedings2011/asianplop2011_submission_20.pdf

Composing Design Patterns: A Scalability Study of Aspect-Oriented Programming
http://scc-aosd.lancs.ac.uk/allPublications/Applications/concerns/Composing_Design_Patterns.pdf

Development and Evaluation of Emerging Design Patterns for Ubiquitous Computing
http://cs.gmu.edu/~jpsousa/classes/699/papers/Chung-EvalPatterns-DIS2004.pdf

Modularizing Design Patterns with Aspects: A Quantitative Study
http://www.les.inf.puc-rio.br/wiki/images/0/04/Taosd-2006.pdf

How to preserve the benefits of Design Patterns
http://c-98-212-192-202.hsd1.il.comcast.net/pub/patterns/cornils/oopslaarticle.pdf

Design Patterns as Language Constructs
http://btu.se/fou/Forskinfo.nsf/all/8ec784abebff383bc12568a3002ca9e2/$file/Research%20Report%2017-96.pdf

Evaluation of Object-Oriented Design Patterns in Game Development
http://java.uom.gr/OOD/papers/IST_2007.pdf

Friday, September 21, 2012

When the Hiring Boss Is an Algorithm

"Joseph Walker writes at the WSJ that although personality tests have a long history in hiring, sophisticated software has now made it possible to evaluate more candidates, amass more data and peer more deeply into applicants' personal lives and interests. This allows employers to predict specific outcomes, such as whether a prospective hire will quit too soon, file disability claims, or steal. For example after a half-year trial that cut attrition by a fifth, Xerox now leaves all hiring for its 48,700 call-center jobs to software. Xerox used to pay lots of attention to applicants who had done the job before. Then, an algorithm told the company that experience doesn't matter. It determined what does matter in a good call-center worker — one who won't quit before the company recoups its $5,000 investment in training. By putting applicants through a battery of tests and then tracking their job performance, Evolv has developed a model for the ideal call-center worker (PDF). The data recommend a person who lives near the job, has reliable transportation and uses one or more social networks, but not more than four. He or she tends not to be overly inquisitive or empathetic, but is creative. 'Some of the assumptions we had weren't valid,' says Connie Harvey, Xerox's chief operating officer of commercial services. However, data-based hiring can expose companies to legal risk. Practices that even unintentionally filter out older or minority applicants can be illegal under federal equal opportunity laws. If a hiring practice is challenged in court as discriminatory, a company must show the criteria it is using are proven to predict success in the job."

http://science.slashdot.org/story/12/09/21/1437253/when-the-hiring-boss-is-an-algorithm?utm_source=feedburnerGoogle+Reader&utm_medium=feed&utm_campaign=Feed%3A+Slashdot%2Fslashdot+%28Slashdot%29&utm_content=Google+Reader

Tuesday, September 11, 2012

Prototyping/Wireframe/Mockup Tools

Pencil Project
http://pencil.evolus.vn/en-US/Home.aspx

Verify
http://verifyapp.com/

Web Site Wireframe Tool
http://wireframe.talltree.us/default.asp

Mockingbird
https://gomockingbird.com/mockingbird/

fluidA
http://stage.fluidia.org/

fluidUI
https://fluidui.com/

Cacoo
https://cacoo.com/

Lumzy
http://lumzy.com/app/

iPhone Mockup
http://iphonemockup.lkmc.ch/

Google SketchUp
http://www.sketchup.com/product/newin7.html

Are We Putting Too Much Emphasis on First-Person Shooter Stats?

By Mike Fahey

In today's 75 percent accurate edition of Speak Up on Kotaku, commenter BattleMoose87 wonders if we aren't giving first-person shooter statistics more weight than they deserve. Are we?

Do statistics matter to you when playing online games? With the recent release of two shooter heavyweights in Battlefield 3 and Modern Warfare 3, alongside their own respective stat tracking services, I feel there is too large an emphasis on stats dictating how we are viewed next to our fellow gamers.

For example, according to Battlelog I have an average accuracy of (gasp!) 5.7%. On its own that statistic is pretty shocking, but does it really reveal much about myself as a player? Am I someone who fires from the hip haphazardly, while my teammates thank the Lord (or admins) that team damage is off. Or am I someone who carefully suppresses the enemy so my team mates can advance and flank the enemy?

MORE AT:
http://kotaku.com/5858285/are-we-putting-too-much-emphasis-on-first+person-shooter-stats

Scientists determine the best way to win at Rugby

What does it take to be a world champion at a sport? Some might say that it's years of dedication and training, but according to a new scientific paper, sheer physical mass might have a lot to do with it — especially in the bruise-laden sport of Rugby.

For those of you who don't follow Rugby Football — be it Union or League — the team is divided into two groups: the forwards and the backs. There are further specifics, like props, hookers, and whatnot, but now's not the time nor place. A new piece of research in the British Journal of Sports Medicine, the sheer size of the team members has a lot to do with their victories, but so too their experience.

The researchers complied data on 20 years of Rugby World Cup players, some 2692 athletes, and looked at their height, weight, and previous experience in the tournament. What they found was a distinct physical advantage that translated to more victories. On average, more successful players weighed 2kg above the counterparts, especially amongst the forwards. For the backs, height made a key difference, with the more victorious players generally sitting around 2cm taller.

MORE HERE >>

Clicky: Web Analytics Tool

http://getclicky.com/

Analyzing Twitter data with IBM BigSheets

Crowdsourcing Sites

Croudsourcing.org
http://www.crowdsourcing.org/

Amazon Mechanical Turk
https://requester.mturk.com/

Quora
http://www.quora.com/about

Idea Bounty
http://www.ideabounty.com/

Scitable
http://www.nature.com/scitable

One Billion Minds
http://www.onebillionminds.com/

PsychExperiment.net
http://www.psychexperiment.net/

Transcribing Jeremy Bentham
http://www.ucl.ac.uk/transcribe-bentham/

Quadrant of Euphoria
http://mmnet.iis.sinica.edu.tw/proj/qoe/

All Our Ideas
http://www.allourideas.org/

Analytics Books and Videos

Analytics Books

Statistics: the Art and Science of Learning from Data by Alan Agresti, Christine Franklin
Head First Data Analysis: A learner's guide to big numbers, statistics, and good decisions by Michael Milton
Data Analysis with Open Source Tools by Philipp K. Janert
Click: What Millions of People Are Doing Online and Why it Matters by Bill Tancer
Glut: Mastering Information Through the Ages by Alex Wright
The Information: A History, a Theory, a Flood by James Gleick
Karl Pearson: The Scientific Life in a Statistical Age by Theodore M. Porter

Analytics Videos
Luis von Ahn: Massive-scale online collaboration
http://www.ted.com/talks/luis_von_ahn_massive_scale_online_collaboration.html

New Ratings Site Mines Credit-Card Data

The site uses credit-card data in an effort to make a more reliable, objective measure of customer trust in a store or restaurant

By Charles Q. Choi
March 1, 2012

Amazon, Yelp and similar Web sites rely on customer reviews to help users with their purchases. A nagging concern of shoppers, however, is how reliable these critiques are.

Bundle, a New York City-based start-up, has turned to a source it deems more objective: credit-card data. Bundle receives data on credit-card transactions from Citi, one of its investors. The data are stripped of personal details, but every cardholder is tagged with a unique identifier so spending can be tracked. The data also retain demographic information such as salary, marital status and household size. Bundle then compares each transaction against a commercially available list of 15 million merchants that accept credit cards, which includes the merchants locations. The idea is "to see people putting money where their mouth is," says Bundle CEO Jaidev Shergill. The company tracks such information as how many repeat customers a business has, the amounts customers usually spend, what types of people go there, and what other places customers of an establishment frequent.

MORE HERE >>