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November 2012
- 3 participants
- 3 discussions
paper: "Friendship networks and social status" (Brian Ball, M. E. J. Newman)
by Eric Purdy 17 Jan '13
by Eric Purdy 17 Jan '13
17 Jan '13
First, some general advice about reading technical papers! Read the
introduction, then the discussion/conclusion, then the experimental
results, and THEN the technical details (in this case, the section
entitled "Inference of rank from network structure"). This is out of
order, obviously, but it's a good triage strategy: you read things in
increasing level of difficulty, so that you always know whether you
care enough to read the next, more difficult part. It's also good
because you have more context to interpret the difficult parts if
you've read all the easier parts of the paper.
I've put a list of wikipedia articles at the bottom of this email,
under the heading "Study Guide". They are a hopefully comprehensible
explanation of the math needed to understand the most technical parts
of the paper. But, if you don't feel like wading through the most
technical parts, you don't have to read the study guide articles in
order to participate in the discussion. (Also, I'm omitting some
background for technical parts that I don't know much about, like
ANOVA and statistical tests of model fit. If someone feels like adding
anything to the study guide, go for it.)
== Paper ==
PDF link: http://arxiv.org/pdf/1205.6822v1.pdf
Arxiv page: http://arxiv.org/abs/1205.6822
== Abstract ==
In empirical studies of friendship networks participants are typically
asked, in interviews or questionnaires, to identify some or all of
their close friends, resulting in a directed network in which
friendships can, and often do, run in only one direction between a
pair of individuals. Here we analyze a large collection of such
networks representing friendships among students at US high and
junior-high schools and show that the pattern of unreciprocated
friendships is far from random. In every network, without exception,
we find that there exists a ranking of participants, from low to high,
such that almost all unreciprocated friendships consist of a
lower-ranked individual claiming friendship with a higher-ranked one.
We present a maximum-likelihood method for deducing such rankings from
observed network data and conjecture that the rankings produced
reflect a measure of social status. We note in particular that
reciprocated and unreciprocated friendships obey different statistics,
suggesting different formation processes, and that rankings are
correlated with other characteristics of the participants that are
traditionally associated with status, such as age and overall
popularity as measured by total number of friends.
== Code ==
Mike Bishop has some C++ code that (I think?) the authors of the paper
are releasing publicly. Mike, can you send that out? It would probably
be a good base to start from if we want to run simulations.
== Study guide ==
These are just to be helpful, don't feel like you have to read any of
them to participate. And feel free to suggest additions, or say that
one of these articles wasn't very helpful.
Adjacency matrix: (http://en.wikipedia.org/wiki/Adjacency_matrix) This
is useful because it gives you a dictionary between graph theory and
linear algebra. It only comes up a little bit, but it's often used
without any explanation.
Elementary Bayesian stuff:
(http://en.wikipedia.org/wiki/Bayesian_statistics) This is a very
high-level article that gives links to more in-depth articles.
Less elementary Bayesian stuff:
(http://en.wikipedia.org/wiki/Bayesian_inference) This is the main
piece of background for the technical section of this paper. If you
really want to know this stuff, Bishop's "Pattern Recognition and
Machine Learning" is the best textbook I know, although it's not
accessible without a lot of mathematical background or a lot of free
time.
Bayesian games: (http://en.wikipedia.org/wiki/Bayesian_game) I've
never seen this before, but it seems like the appropriate math to use
when thinking about social science stuff with Bayesian methods.
EM: (http://en.wikipedia.org/wiki/Expectation%E2%80%93maximization_algorithm)
The workhorse of mathematically rigorous Bayesian statistics. It's a
flaky piece of shit, but it's pretty much all we have.
MCMC: (http://en.wikipedia.org/wiki/Markov_chain_Monte_Carlo) The
workhorse of mathematically rigorous frequentist statistics.
Gibbs sampling: (http://en.wikipedia.org/wiki/Gibbs_sampling) This is
the most mature mathematics that specifies how emergent properties
emerge from local interactions. It was first created to model
thermodynamics, which is basically all about emergent properties of
molecule interactions, like temperature, pressure, etc.
Ising model: (http://en.wikipedia.org/wiki/Ising_model) This is the
most straightforward example of a Gibbs distribution, it's what you
should think about when you try to understand them.
On Wed, Oct 3, 2012 at 10:37 AM, Eric Purdy <epurdy(a)uchicago.edu> wrote:
> I am starting a new listhost, math(a)moomers.org. I am hoping that it
> will function much like readings, but that we can have long and
> intricate technical discussions without annoying anyone.
>
> Some proposed ground rules:
>
> - There are no stupid questions, and we're interested in everyone's
> opinion. In particular, you are encouraged to subscribe to
> math(a)moomers.org even if you do not have much mathematical training.
> If you're interested in watching math being done, that's all that
> matters.
>
> - There will be no status games, and no arguments from authority.
> Nobody should sign up to math(a)moomers.org because they want to impress
> anyone, and nobody can cite their professional status or mathematical
> training to make someone else shut up.
>
> - If any publishable research is done on math(a)moomers.org, we will
> decide by consensus whose names should be on any papers that result.
>
> The first proposed paper to read is "Friendship networks and social
> status", by Ball and Newman. It is available online at
> http://arxiv.org/abs/1205.6822 . I am interested in it because it
> gives a nice model of social stratification as an emergent property of
> social networks. I think it would be cool to try to extend it, and I
> think it should be possible to give a scientific account of the
> phenomenon of discursive privilege.
>
> Here is the abstract:
>
> In empirical studies of friendship networks participants are typically
> asked, in interviews or questionnaires, to identify some or all of
> their close friends, resulting in a directed network in which
> friendships can, and often do, run in only one direction between a
> pair of individuals. Here we analyze a large collection of such
> networks representing friendships among students at US high and
> junior-high schools and show that the pattern of unreciprocated
> friendships is far from random. In every network, without exception,
> we find that there exists a ranking of participants, from low to high,
> such that almost all unreciprocated friendships consist of a
> lower-ranked individual claiming friendship with a higher-ranked one.
> We present a maximum-likelihood method for deducing such rankings from
> observed network data and conjecture that the rankings produced
> reflect a measure of social status. We note in particular that
> reciprocated and unreciprocated friendships obey different statistics,
> suggesting different formation processes, and that rankings are
> correlated with other characteristics of the participants that are
> traditionally associated with status, such as age and overall
> popularity as measured by total number of friends.
>
> --
> -Eric
--
-Eric
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I thought I'd give a quick overview of my research area because a) it's
math, and b) somebody might find it interesting. It also might give others
some idea of what I'm interested in and what I know about, which seems like
useful information for a math discussion list. I'll try to organize it
well enough that you can ignore the boring or incomprehensible parts. I'm
happy to elaborate on anything that I rushed over.
*What It's Called*
My research area goes by a few different names, of which Nonarchimedean
Geometry is my favorite. Rigid Analysis is another common one, or
sometimes Nonarchimedean Analysis. One might also hear of Berkovich
Theory, Tropical Geometry, or Nonarchimedean Dynamics, which are closely
related areas.
*Ultrametric Spaces*
A metric space formalizes the notion of distance. An ultrametric space
adds the axiom that all triangles are isosceles. To see why this can be a
meaningful axiom, consider the metric space X of all living organisms,
where d(A,B) is defined to be the number of years since the most recent
common ancestor of A and B was born (or 0, if A=B). Then X is an
ultrametric space, because, for any three organisms, the closest two must
be equally far from the third.
We can also regard the universe as an ultrametric space by taking
"ballpark" distances. For example, if I regard all points in London to be
equally far from myself (which, in practical terms, is almost true) but
closer than points on Mars, then I see, again, that for any three points,
the closest two are equally far from the third.
These both illustrate a deep fact about ultrametric spaces: that they are
very tree-like—even though, in both examples, the vertices of the tree are
not necessarily points in the space. One also detects a relationship
between ultrametric spaces and the notion of an order of magnitude.
*p-Adic Analyis*
To cut wildly away from the vaguely practical: The p-adics have been
important in number theory for quite some time. But those used to the
idyllic world of complex analysis have long been frustrated by the poor
analytic properties of the p-adics—as a metric space, they are totally
disconnected, which means that the only connected subspaces are single
points. The situation gets worse if we pass to the algebraic closure; then
they fail to even be locally compact (even after completion). Both of
these things are a disaster for traditional approaches to analysis, but
that hasn't stopped the gods of math from posing problems that require
analytical tools.
A number of technical tools were developed to get around these problems,
but the key intuition came in the 80s from Vladimir Berkovich, who saw that
fields like the p-adics could be embedded in larger spaces which *are
*connected
and locally compact. These spaces serve the same role in p-adic analysis
as the complex plane has served in traditional analysis—which is to say
that they're a really, really big deal.
The p-adics, as a metric space, are in fact ultrametric, the deeper fact
responsible for the problems mentioned above. Passing to the Berkovich
space involves adding points which correspond to the vertices of the trees
that we imagined in the previous section; for example, for the space of
life (which isn't a field, but the geometric issues are similar), we would
add a point corresponding to Chordata.
Clearly, these spaces bear little resemblance to the complex plane. Yet an
astonishing number of theorems from complex analysis hold true with almost
no modification in this new Berkovich setting. When there are
modifications, they usually take the form of adding juicy combinatorial and
graph-theoretic elements. My advisor is written a whole
book<http://arxiv.org/pdf/math/0407433v1.pdf>on this.
I'll finish here with a brief theorem. If F is a field with a metric, then
either F is a subfield of the complex numbers, or F is ultrametric. So if
we think of analysis on ultrametric fields, then the complex numbers are
the special case, a pathology within a wider, deeper, and weirder theory.
*Metric Graphs*
There's a lot I'll omit here for brevity (and because I'm procrastinating
far more important things), but there is a theory of chip-firing on metric
graphs that has played the role of the theory of divisors on algebraic
curves. This is a joyful mingling of analysis and algebra with
combinatorics, and most of the basic definitions have not yet been fully
worked out. Other things, like the graph-theoretic Laplacian, begin to
lose their distinction from the classical Laplacian. Metaphors from the
theory of electrical networks abound.
*Tropical Geometry*
Tropical geometry emerged out of study of the min-plus algebra, which is,
roughly, what happens if you take the logarithm of the usual real number
system. Tropical gadgets are these piecewise-linear doohickeys
(e.g.<http://www.crcg.de/wiki/images/c/c9/Ninecubics.jpg>)
which have been entertaining mathematicians for years. But it has become
more and more clear over the past two decades that they are all
cross-sections of something much larger: the Berkovich space.
Connected to this fact is the important observation that Berkovich spaces
are polyhedral in nature. Though they are generally infinitely-branching
monstrosities, they have a well-behaved polyhedral skeleton.
*Dynamical Systems*
This is something I know next to nothing about, but Berkovich spaces have
recently become a hot topic in the dynamical systems crowds. Somehow,
these are the right spaces in which to explore certain iterative phenomena.
*Algebraic Geometry*
The problem of understanding Berkovich spaces in two dimensions is deeply
connected to an old concern in algebraic geometry of the resolution of
singularities on surfaces. There is also a nonarchimedean version of the
old correspondence between complex algebraic curves and Riemann surfaces.
*Connections to Logic*
Some high-powered model theorists have become interested in nonarchimedean
geometry lately. Model theorists are to mathematicians what mathematicians
are to everyone else. The strange language of quantifier elimination and
stably dominated types brings the almost mystical ability to shuffle proofs
around as if math were a three-shell game. I have been studying this for
the past 10 weeks and I have no idea what it's about.
*Number Theory*
One shouldn't believe the hype that this stuff will prove the Riemann
Hypothesis, but there are many promising developments. For one, many of
the classical constructions in number theory can be seem in simple
geometric terms on an appropriate Berkovich-style space. Rigid analysis is
quickly becoming ubiquitous in algebraic number theory.
*What I'm Doing*
My own project has been leaning heavily on the theory of distributive
lattices, which has beautiful connections to topology. If we imbue the
Berkovich space with extra information about tangent directions (which are
more subtle in non-archimedi-land than in classical analysis) then we get a
strange space—sometimes called the 'adic' space—which is related to a
natural lattice and hides a few untapped secrets. My contribution, using
this point of view, has been showing that the Berkovich space is, in some
sense, a "completion", akin to producing the reals from the rationals (I
use filters on lattices which generalize Cauchy sequences).
The nature of this work is mainly to clarify the current state of discourse
in nonarchimedean geometry. Many theorems have been proved in a technical
fashion, but need to be redone in a way that exposes the underlying
intuitions.
OK, it's time for me to stop procrastinating. Hope that this spiced things
up a bit, and wasn't too bewildering.
2
2
Sent to you by Mike via Google Reader: Accounting for Numbers via
Steven Landsburg | The Big Questions: Tackling the Problems of
Philosophy with Ideas from Mathematics, Economics, and Physics by Steve
Landsburg on 11/13/12
Over at Less Wrong, the estimable Eliezer Yudkowsky attempts to account
for the meaning of statements in arithmetic and the ontological status
of numbers. I started to post a comment, but it got long enough that
I’ve turned my comment into a blog post. I’ve tried to summarize my
understanding of Yudkowsky’s position along the way, but of course it’s
possible I’ve gotten something wrong.
It’s worth noting that every single point below is something I’ve
blogged about before. At the moment I’m too lazy to insert links to all
those earlier blog posts, but I might come back and put the links in
later. In any event, I think this post stands alone. Because it got
long, I’ve inserted section numbers for the convenience of commenters
who might want to refer to particular passages.
1. Yudkowsky poses, in essence, the following question:
Main Question, My Version: In what sense is the sentence “two plus two
equals four” meaningful and/or true?
Yudkowsky phrases the question a little differently. What he actually
asks is:
Main Question, Original Version: In what sense is the sentence “2 + 2 =
4″ meaningful and/or true?”
This, I think, threatens to confuse the issue. It’s important to
distinguish between the numeral “2″, which is a formal symbol designed
to be manipulated according to formal rules, and the noun “two”, which
appears to name something, namely a particular number. Because
Yudkowsky is asking about meaning and truth, I presume it is the noun,
and not the symbol, that he intends to mention. So I’ll stick with my
version, and translate his remarks accordingly.
2. Yudkowsky provisionally offers the following answer:
First Provisional Answer: The sentence “two plus two equals four” means
that the expression “2 + 2 = 4″ is a valid inference from the axioms of
Peano arithmetic.
He then provisionally rejects this provisional answer on the grounds
(with which I wholeheartedly agree) that “figuring out facts about the
natural numbers doesn’t feel like the operation of making up
assumptions and then deducing conclusions from them.” He goes on to
say: “It feels like the numbers are just out there, and the only point
of making up the axioms of Peano Arithmetic was to allow mathematicians
to talk about them.”
He’s certainly right that it feels — to me, and, I am sure to almost
everyone who has ever thought much about arithmetic — like the numbers
are just “out there”. On the other hand, I’d quibble with Yudkowsky’s
assessment of the point of Peano arithmetic. The point isn’t to “allow
mathematicians to talk” about numbers; mathematicians from Pythagoras
through Dedekind had absolutely no problem talking about numbers in the
absence of the Peano axioms. Instead, the point of the Peano axioms was
to model what mathematicians do when they’re talking about numbers.
Like all good models, the Peano axioms are a simplification that
captures important aspects of reality without attempting to reproduce
reality in detail.
3. To reach a closer understanding of what numbers are, Yudkowsky
imagines trying to explain them to a logician with a full grasp of
logic but no grasp of numbers. Here I think Yudkowsky has fooled
himself into imagining an impossibility. If you grasp logic, you grasp
the idea of a proof. If you grasp the idea of a proof, you grasp the
idea of a sequence of logical steps. If you grasp the idea of a
sequence of logical steps, you grasp the idea of a sequence. If you
grasp the idea of a sequence, you already know a lot about numbers.
This is one reason why I believe that any attempt to account for
numbers via logic must ultimately be circular.
4. Be that as it may, Yudkowsky goes on to try to explain to his
fictional interlocutor what numbers are. He begins by essentially
stating the first order Peano axioms: 0 is a number, every number has a
successor, no two numbers have the same successor, and so forth.
Eventually, he realizes that this approach isn’t taking him quite where
he wants to go and makes a bit of a course correction (as we’ll see
below). But I think more than a course correction is called for; he’s
gone off in entirely the wrong direction. He’s listing the properties
of numbers, but not even trying to explain what they are. If I were
explaining numbers to a naif, I’d probably start with something like
Bertrand Russell’s account of numbers: We say that two sets of objects
are “equinumerous” if they can be placed in one-one correspondence with
each other; a “number” is that which all sets equinumerous to a given
set have in common. Whether or not that works in detail, it’s at least
an attempt at a definition, as opposed to a mere list of properties.
5. Yudkowsky, in his fictional conversation with his fictional
logician, eventually comes to realize that neither the first order
Peano axioms nor any other first-order system can uniquely characterize
the natural numbers. This is a consequence of Godel’s Incompleteness
Theorem, or even more fundamentally of the Lowenheim-Skolem Theorem.
What it means is that no matter what axioms you start with, there are
going to be multiple systems that satisfy those axioms; the natural
numbers are only one of those systems, so your axioms cannot
collectively specify the natural numbers.
6. Yudkowsky solves his problem by passing to second order Peano
arithmetic — “second order” meaning that, in addition to using
variables to represent numbers, you can also use variables to to
represent sets of numbers. He correctly notes that second order Peano
arithmetic has a unique model. (I am using the word “model” here in the
technical sense of logic, not in the informal social-sciencey sort of
way that I used it in point 2 above.) This means that sure enough,
there is one and only one system that satisfies all the axioms of
second-order arithmetic. And he concludes that:
Y’s conclusion: That’s why the mathematical study of numbers is
equivalent to the logical study of which conclusions follow inevitably
from the number-axioms.
But this is disastrously wrong for at least two reasons, each of which
deserves its own numbered point.
7. Yudkowsky leaps from “the natural numbers can be precisely specified
by second order logic” to “the .. study of numbers is equivalent to the
logical study of which conclusions follow inevitably from the
number-axioms”. This is wrong, wrong, wrong, because second order logic
is not logic. Indeed, the whole point of logic is that it is a
mechanical system for deriving inferences from assumptions, based on
the forms of sentences without any reference to their meanings. (Thus
if we assume that all bachelors are unmarried and that Walter is a
bachelor, we can infer that Walter is unmarried, without having to know
anything at all about who walter is, or what the words “bachelor” and
‘unmarried” mean.) That’s why you’re not allowed to set up an axiom
system in which all the true theorems of arithmetic are taken as axioms
— there is no mechanical procedure for determining whether a given
statement is or is not a true theorem of arithmetic (see Tarski’s
theorem on the undefinability of truth) and therefore no mechanical
procedure for determining what is or is not an axiom in that system. In
second-order Peano arithemetic, we have an analogous problem: The
axioms can be identified mechanically, but the rules of inference
can’t. A properly programmed computer can examine a first-order proof
and tell you if it’s valid or not; that is, it can tell you whether
each step does in fact follow logically from some of the previous
steps. But no computer can do the same for second-order proofs.
So the study of second-order consequences is not logic at all; to tease
out all the second-order consequences of your second-order axioms, you
need to confront not just the forms of sentences but their meanings. In
other words, you have to understand meanings before you can carry out
the operation of inference. But Yudkowsky is trying to derive meaning
from the operation of inference, which won’t work because in
second-order logic, meaning comes first.
8. Even putting all that aside, Yudkowsky is relying on a theorem when
he says that second-order Peano arithmetic has a unique model. That
theorem requires a substantial dose of set theory. So in order to avoid
taking numbers as primitive objects, he’s effectively resorted to
taking sets as primitive objects. But why is it any more satisfying to
take set theory as “given” than to take numbers as “given”? Indeed, the
formal study of numbers precedes the formal study of sets by millennia,
which suggests that numbers are a more natural starting point than sets
are. Whether or not you buy that argument, it’s important to recognize
that Yudkowsky has “solved” the problem of accounting for numbers only
by reducing it to the problem of accounting for sets — except that he
hasn’t even done that, because his reduction relies on pretending that
second order logic is logic.
9. All of which leaves us with the problem of accounting for numbers,
and for the meaning of statements like “two plus two equals four”. To
me, by far the most satisfying solution is a full-fledged Platonic
acknowledgement that numbers are indeed just “out there” and that they
are directly accessible to our intuitions. I embrace this view for (at
least) three reasons: A. After a lifetime of thinking about numbers, it
feels right to me. B. Pretty much every one else who spends his/her
life thinking about numbers has come to the same conclusion. C. It
seems enormouosly more plausible to me that numbes are “just out there”
than that physical objects are “just out there”, partly because there
is in fact a unique system of (standard) natural numbers, whereas the
properties of the physical universe appear to be far more contingent
and therefore unnecessary. I’ve given an account in The Big Questions
of how the existence of numbers can account for the existence of the
physical universe; I think it would be very difficult to go in the
opposite direction (though I’ve seen some pretty good attempts).
Therefore, accepting numbers as primary and accounting for the universe
as a necessary consequence of numbers seems to me to be the
ontologically parsimonious thing to do, and I like parsimony.
10. Needless to say, point 9 is not a proof. But I know of no
alternative story that strikes me as even remotely plausible. Moreover,
the alternative stories all seem to go wrong in pretty much the same
ways; for example, every single point above is one I’ve blogged about
before in other contexts, but here they are, all being relevant again.
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