Слайд 1Daniel
Web Science: How is it different?
Daniel Tunkelang
Head of Query Understanding
Слайд 3tl;dr:
The scientific method is alive and well.
Big data has just changed
the economics.
Слайд 4How have the web and big data changed science?
Let’s ask some
of the experts.
Слайд 5“You have to kiss a lot of frogs to find one
prince. So how can you find your prince faster? By finding more frogs and kissing them faster and faster.”
Mike Moran
Do It Wrong Quickly: How the Web Changes the Old Marketing Rules, 2007
Cited by Kohavi in Online Controlled Experiments at Large Scale, 2013
Слайд 6Web Science = faster, cheaper experiments.
Слайд 7“The cost of experimentation is now the same or less than
the cost of analysis. You can get more value…by doing a quick experiment than from doing a sophisticated analysis.”
Michael Schrage
Value-Creation, Experiments, and Why IT Does Matter, 2010
Слайд 8Web Science = more experiments, less analysis?
Слайд 9“with massive data, this approach to science — hypothesize, model, test
— is becoming obsolete… Petabytes allow us to say: "Correlation is enough." We can stop looking for models…analyze the data without hypotheses…throw the numbers into the biggest computing clusters the world…and let…algorithms find patterns where science cannot.”
Chris Anderson
The End of Theory, 2008
Слайд 17The scientific method still works today.
What’s changed is the economics.
Слайд 20It’s the economy, science.
Yesterday
Experiments are expensive,
choose hypotheses wisely.
Today
Experiments are cheap,
do as
many as you can!
Слайд 22A/B testing: everybody’s doing it.
Слайд 23Google: 20k search experiments per year
Слайд 26Scientists gain insight
by staring at data.
Слайд 27Big data tools improve
data exploration.
Слайд 28In hypothesis generation,
quantity trumps quality.
Слайд 31Easier to analyze data than research humans.
Слайд 32But we pay the price.
Example: search engine improvements in batch evaluations
don’t always predict real user benefits.
[Hersh et al, 2000] Do Batch and User Evaluations Give the Same Results?
[Turpin & Hersh, 2001] Why Batch and User Evaluations do not Give the Same Results
[Turpin, Scholer, 2006] User Performance versus Precision Measures for Simple
Search Tasks
But also see…
[Smucker & Jethani, 2010] Human Performance and Retrieval Precision Revisited
Слайд 33When local optimization is cheap, you neglect the rest.
Слайд 34To summarize: how is web science different?
Online testing is cheaper and
scalable.
Data exploration tools make hypothesis generation cheaper and easier.
But the experiments that are easy and cheap aren’t always the most valuable.
Easy to forget our biases as scientists.
Слайд 35Take-Aways
The scientific method is alive and well. Big data has just
changes the economics.
Cheaper hypothesis testing and generation has already been transformative. That’s why big data matters.
But we neglect the human side of scientific experimentation at our peril.
Слайд 36Daniel Tunkelang
dtunkelang@linkedin.com
https://linkedin.com/in/dtunkelang