
The network nonsense of Albert-László Barabási - Gatsky
https://liorpachter.wordpress.com/2014/02/10/the-network-nonsense-of-albert-laszlo-barabasi/
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smallworld
I work in a lab that directly competes with Barabási.

Barabási is seen as a mortal enemy and we try to discredit his work as often
as possible, just as this article does.

But the truth is, the whole field is pretty much nonsense.

We try to apply network theory in a way which doesn't really apply. We make
assumptions about biology that are trivially false. Any statistical results
that reach significance fail to be significant on retesting. Any results which
continue to be significant do not match the experimental data.

This field has not yet proven anything of true biological value.

~~~
atemerev
How about Vespignani's result on epidemic thresholds?

[http://works.bepress.com/avespignani/13/](http://works.bepress.com/avespignani/13/)

~~~
chaoplexity
You may have meant to cite
[http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.86....](http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.86.3200),
and for a discussion about that paper see this by Robert May
[http://www.sciencemag.org/content/292/5520/1316](http://www.sciencemag.org/content/292/5520/1316)

What other papers do you consider to be hallmarks of the success of network
science from the stat. phys. point of view? The largest critique from non-
stat. phys. researchers is that context seems more important than network
topology in most applications. Indeed it is important to understand why there
is degree heterogeneity. Without understanding the technology surrounding the
network however you can not only make incorrect predictions, instead you might
be predicting the opposite of reality.
[http://discovermagazine.com/2007/nov/this-man-wants-to-
contr...](http://discovermagazine.com/2007/nov/this-man-wants-to-control-the-
internet)

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jboggan
I studied graph theory heavily in undergrad, started working in a genetics
lab, and spent ~7 years in a bioinformatics PhD program focusing on biological
networks. Barabasi was, at one time, the brightest contemporary star in my
scientific pantheon.

Suffice to say, his publications (and most biological applications of network
theory) are fairly meaningless beyond advancing careers. It's a case of cool
sounding math that is misused and every PI wants to show that their tiny area
of study is also scale-free/subject to cool network effects and therefore
worthy of a publication pointing this out. The math is incredibly shoddy all
around, and I was burned on several occasions by sticking up for actual
scientific principles and pointing out when the math contradicted the
assumptions they were trying to prove.

As an aside - this is my main distinction between Research and Science.
Researchers do an excellent job of confirming their hypotheses via whatever
model they can lay their hands on. Scientists falsify their hypotheses until
no suitable model is left. I've met a lot of Researchers in my experience but
couldn't truthfully tell you a true Scientist since the system discourages
their existence.

Anyway, my advisor wanted me to SCALE-FREE ALL THE THINGS. The way that
everyone gets a power-law in their system is (1) plot their system on a log
axis, (2) do a linear fit, (3) voila the slope of the linear approximation is
now the exponent of your scale-free power law system, no need to apply any
statistical tests to show that your original system is actually exponential!
And if you did want to take that extra step, just fiddle with the data until
it does fit within your chosen margin of error.

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throwaway77779
I know several acclaimed mathematicians who have little stake in the arguments
between network scientists, but who all seem to think that Barabasi's work is
extremely low on good ideas.

I am inclined to believe that two decades from now, 'complex network research'
will be in a much better state, and there'll be less room for the likes of
Barabasi.

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ChristianMarks
"Mathematics and the Internet: A Source of Enormous Confusion and Great
Potential"
[http://www.ams.org/notices/200905/tx090500586p.pdf](http://www.ams.org/notices/200905/tx090500586p.pdf)
Is critical of scale-free networks of the preferential-attachment type, in
particular of Barabasi's work. The paper is unusual for its polemic tone and
for its name dropping. Researchers will trash each other in private--it is
unusual to see this in print.

Much of the article is consumed with invidious comparisons of scale-free,
preferential attachment network models of the internet with the authors’ own
HOT (”highly organized/optimized tolerances/tradeoffs”) models: “In view of
such a simple physical explanation of the origins of node degree variability
in the Internet’s router-level topology, Stogartz’ question, paraphrasing
Shakespeare’s Macbeth, ‘…power law scaling, full of sound and fury, signifying
nothing?’ has a resounding affirmative answer.” The authors seem to suggest by
this literary reference that a scale-invariant model of the Internet is a
“tale told by an idiot.” This would not be lost on the readership of the
Notices of the American Mathematical Society.

Its authors spare no opportunity to criticize their competition, as well as
mathematicians and physicists generally, whom they regard as foppish, insular
ivory tower aesthetes, whose nostrils are unacquainted with the bracing scent
of an expertly soldered electrical connection.

Despite all of that, the authors are correct. I mention Doyle _et al._ because
other authors have been critical of work on scale-free networks--this is not
new. Doyle _et al._ warned about the misapplication of such networks to
biology, though they mysteriously claimed that such failures of the scientific
method "would reflect poorly on mathematics," as if mathematicians ought to be
held responsible.

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dlan1000
What I found more interesting than Pachter's analysis of the specific failings
of the Barzel-Barabási paper is the more general implications for our
scientific process. I have two parallel trains of thought:

1) We all know that we have scientific "celebrities" and that their work is
often over-represented in high-quality journals (while dissenting viewpoints
are often suppressed). There is nothing wrong with critizing the work of the
celebrity du jour (or in this case, maybe, du décennie), but framing is
everything and you will find more success in your scientific career with
constructive and respectful criticism without resorting to ad hominem attacks
such as "the emperor has no clothes". No one benefits from a bloody cage
match.

2) Network science (like many interdisciplinary fields) has problems because
many of its practitioners lack extensive knowledge of the systems,
experimental challenges and core research methodologies of the fields or
contexts to which they apply their developments. Success in such
interdisciplinary fields is often incentivized and measured in a very narrow
way and not associated with the primary goal of science -- useful and
meaningful advances in our collective body of knowledge. You want to be at the
top of your field, but presumably (or hopefully) you have more noble
aspirations -- you want your work to have real meaning. But this lofty goal is
challenged by the rapidly growing body of scientific work and the fracturing
of science into siloed sub-fields. For example, finding the right set of peer
reviewers for an interdisciplinary submission becomes increasingly
challenging. Consequently, mistakes will be made, missed in the peer review
process, and published. Dissenting opinions and followup work need to be given
equal representation.

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atemerev
A case of so-called envy. The scale-free networks are nearly trivial and about
as common as power law instances.

Barabási's works were the reason I entered science.

~~~
stonogo
If there are more like you -- more people working in scientific fields because
of Barabási -- then you people are the only real contribution he's made. His
"works" are handwaving and gibberish.

~~~
atemerev
The entire field of modern epidemiology depends on his results.

~~~
stonogo
This is almost comedically incorrect. The only reason I can think of for
someone to claim this is for entertainment.

