
Ask HN: How do you read Academic Papers? - milesf
I have never really consciously taken the time to learn how to read academic papers, because it never occurred to me it&#x27;s something I needed.<p>I replied to a tweet today suggesting people ought to take a course how to read them, and got a great reply from Glenn Vanderberg on a starting point:<p>https:&#x2F;&#x2F;twitter.com&#x2F;glv&#x2F;status&#x2F;579411305347489792<p>Does anyone else have any thoughts or opinions about this? I have a hard time learning things. Maybe this insight is part of the reason why.
======
sarahj
I have spent a large portion of my adult life finding and reading and
understanding scientific papers. The advice offered in the tweet is good, so I
won't restate it - but I will offer a couple of my own:

* Print the paper out and make notes on it by hand (this has a small mention in one of the articles) - this technique got me through university, I tried every software package imaginable but in the end having a hard copy forced me to deal with sheer amount of reading I had to do. It also allowed me to freely make notes, add sticky notes etc. Since then I have done this with any collection of papers I want to get my head around.

* Try to comprehend __something __on every read through - it doesn 't have to be big, just something - whether it is the sample makeup or part of the methodology or the conclusions etc. You don't need to understand these in any particular order, but ensure to revise your understanding as you become more familiar with the paper.

* Most papers are useless (to you at the time you are reading them) - the sad truth about research is that 90% of the stuff you devote yourself to understanding will be wrong, outdated or not useful to what you are working on. It is very hard to pick out useful papers with nothing to go on but titles, and abstract and citations. As you get more used to the field it becomes easier and familiar names, authors and institutions can guide you, but even close to a decade after reading my first paper I still probably only manage a 10% hit rate when conducting research (but hey - 10% of a lot of papers is still a lot of papers!)

~~~
jwr
> * Most papers are useless (to you at the time you are reading them) - the
> sad truth about research is that 90% of the stuff you devote yourself to
> understanding will be wrong, outdated or not useful to what you are working
> on.

This is very important advice. Do not assume that just because it's a
published research paper it is valuable, correct, or useful. In fact,
especially in applied CS, I found that authors will sometimes make what looks
like an intentional effort to obfuscate the methods so that the paper is
publishable (peer reviewers will not try to reproduce the results anyway), but
the methods are not implementable, or at least not easily.

This makes sense when you think about the competition in academia, authors
doing consulting work for companies, or intending to start businesses of their
own.

~~~
seanmcdirmid
Usually the idea is bunk and they are trying to obscure that, more often than
that the idea is great and they are trying to protect their IP for a startup.

If you know something is possible, then it is not impossible to replicate
results even with obscure directions about it. Except for Paxos, you really
need good instructions at that point (that guy should get an award).

~~~
striking
Hah. I'm pretty dumb myself. That'll teach me. (I'm leaving the link, though.
Great paper.)

[1]: [http://research.microsoft.com/en-
us/um/people/lamport/pubs/p...](http://research.microsoft.com/en-
us/um/people/lamport/pubs/pubs.html#lamport-paxos)

~~~
tokenrove
Leslie Lamport is a man. You could argue something about Barbara Liskov's
Viewstamped Replication, though, I guess.

~~~
striking
Whoops. Thanks, I messed up pretty badly, didn't I.

~~~
tokenrove
It's an easy mistake to make. It's interesting, though, because there are at
least three important women who were involved in related work at the same time
-- I'm thinking of Liskov, Dwork, and Lynch.

------
karmacondon
That's kind of like asking, "How do you learn how to code?"

The answer is to do it. Do it often, do it a lot, over and over. The linked
tweet provided great advice, as do other resources and comments in this
thread. But the bottom line is that you learn by doing, and trying hard.

I remember reading the same section of a paper at least 30 times, no
exaggeration. I would read it, then go and look up the topic online, then read
it again, then go do something else, and then read it again. Over and over for
days. i parsed every symbol and word of every line. And then one day I was
elucidated. I finally understood it, and it was a feeling of awesome communion
with the gods.

I'm not sure if there's a short cut, but I'll be monitoring this thread along
with you in the hopes of finding one. Do what the others said and print the
paper out, and take a pencil and highlighter to it. Look up terms you don't
know online and be diligent in your use of search engines. Just stay at it,
and don't give up!

As an afterthought, most modern computer science papers have a graphic or
figure on the second or third page that does a good job of explaining the idea
visually. Older papers tend not to have this, or it's buried deeper in the
paper. Look for this key graphic and use it as a guide or framework to
understand the rest of what's being said.

------
seanwilson
Academic papers can seem incredibly intimidating but you have to remember:
they're not written to be readable to the casual reader unlike articles on the
web.

Journals have strict page limits so there's no space to introduce domain
specific terminology or give a brief tutorial on the topic. They only have
enough room to tersely describe directly relevant background material and will
assume you are knowledgable in the domain.

Read the abstract then the conclusion. If it sounds like you want to
understand the rest of the paper after that, be prepared to look up
terminology, read citations, follow tutorials and reread the paper multiple
times to really understand it. Don't be put off if you can barely understand
it the first time.

~~~
jvdh
Reading the abstract and the conclusion is the most important part of reading
and selecting academic papers. Especially in the beginning.

If you read the abstract and the conclusion you should have a good sense of
what this paper is about, what it is trying to prove, and perhaps also a sense
of how they prove this. These are the primary factors for you to see if this
paper is worthwhile to you.

~~~
Squarel
Agreed.

I read the abstract, if it seems relevant, then I flip to the conclusion, if
it still seems relevant then I skim read it through, then print it out if it
looks like something I need to dig deeper into.

Often those lightbulb moments have only come for me after printing it out,
despite reading it 4-5 times on readcube.

------
middleclick
How to Read a Paper by S. Keshav

[http://ccr.sigcomm.org/online/files/p83-keshavA.pdf](http://ccr.sigcomm.org/online/files/p83-keshavA.pdf)

~~~
CSDude
Useful: Literature Review Matrix mentioned there:
[https://d1b10bmlvqabco.cloudfront.net/attach/i7ax2kxrsnn3v5/...](https://d1b10bmlvqabco.cloudfront.net/attach/i7ax2kxrsnn3v5/gyqyt9p1qfs4cd/i7fydo2u2dx4/LitReviewMatrix.pdf)

------
jordanpg
The answer depends on why you're reading the papers, of course.

If it's only a dilettante's interest, then read it like you would read news:
skim for a general sense, emphasizing the introduction, conclusion, and
graphics.

For academics reading papers, the situation is (potentially) different. There
are genuine professional consequences for failing to read or understand the
material.

There are many approaches -- many good ideas here -- most of which are
rehashing of basic study skills, but I would add one piece of generic advice.

Reading academic papers well takes a lot of time. Sometimes this is called
active reading. If you are doing this type of reading, make sure you take
_something_ away from the reading. And by "take away" I mean "memorize", not
index in Mandalay or outline in Evernote. Deliberately bolt each bit of
information onto the edifice you have already built. Think about it in
context. Wonder about it. Doubt it. Be skeptical. If you can't summarize the
paper next week at a cocktail party, you're not reading, you're just filling
out a bibliography.

~~~
stewbrew
I have to disagree. IMHO most papers weren't written to be read with care. So
you shouldn't waste your time on them. Skimming through is ok when you have to
filter out the few papers that actually make a difference.

~~~
jordanpg
I don't think this can be true, except for experts. In the biography of
Oppenheimer, _American Prometheus_ , he was described as having an uncanny
ability to flip through publications and understand their conclusion and
significance in seconds. That description, or anything like it, certainly
isn't true for me.

I would suggest that any paper that you perceive as a waste of time or not
worth reading with care probably isn't worth reading at all. If it is the case
that this sort of thing is the norm, as I know full well it is in some
disciplines, then that says something important about what's being published
in that discipline. It says nothing about what the best way to read and
understand the latest pubs in a discipline with real research going on.

------
tdaltonc
I try not to read primary research papers. Most of them are wrong[0]. Even the
one's that are right are written for consumption by a very specialized
community that I'm rarely a member of.

If I decide that i absolutely need to understand a particular paper, I start
by finding a relevant review article. I look and see if the papers cited in
the background section are also cited in a recent review of the state of the
field. These are less likely to be flat out wrong, and they provide better
context.

I try to read a paper with other people (preferably people who know the field)
and we take turns trying to explain the figures and methods to each other.

But to reiterate: any given paper is most likely wrong and your default
position should be persistent skepticism.

[0]
[http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1182327/](http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1182327/)

------
auxym
This is the way I learned to do it in grad school. There a lot of litterature
out there and most chances are 97% is irrelevant to what you're interested in.
So, a lot of "reading papers" is efficiently figuring out if it is interesting
or not. You'll never realistically have time to read everything.

First read title and abstract. This is where you'll likely eliminate a lot of
stuff.

Interestingly, I've found that the best point to go from there is the
conclusion. A good conclusion will generally tell you the results (which is
generally what interests you), plus a good summary of the motivation and
approach/methods.

From there figure out what is interesting to you. Go through the background or
motivation, specific areas of methodology you're interested in, or detailed
analysis of the results.

------
Gatsky
Disclaimer: I spend a lot of time reading life sciences papers, which are
mainly about experimental procedures and data rather than theory and which are
almost universally frustrating, often misleading, wrong or actually just made
up.

I hope that soon reading papers will be supplanted by automated aggregation
and parsing of content, and eventually almost real time dissemination of data
and results. Frankly, encasing scientific knowledge in papers is now beyond a
joke. Why we are still relying on parchment based technology and pre-
enlightenment publishing norms drives me nuts. Examples:

1\. Genomics papers that have a table with thousands of rows printed in a PDF
in the appendix. Almost willfully annoying.

2\. Two page papers in top life sciences journals that have 100 page
appendices which are not searchable or indexed.

3\. Papers that are heavily criticised in letters, but none of this is obvious
when looking at the original paper HTML page, the abstract or the PDF.

4\. Long clinical trials that are published repeatedly over 20 years, where
the previous interim data updates are locked away in journal archives that
requires extra payment or a subscription to JSTOR.

5\. Papers with 10 supplementary tables, all single file excel spreadsheets.

6\. Papers are submitted for publication 12 months before they are actually
published. Bad luck if you started working on the same thing 6 months ago.

7\. If I want to show a table from your paper in a presentation, I have to
manually snapshot from the PDF and paste it on my slide.

8\. Because the only way to disseminate data is with a paper, important trial
results can be given as a presentation at a conference, and not become
available until published much later. Until then, the only record of these
results are your memory if you were there, a pay-walled recording of the
presentation, a drug company press release, or sandwiched between banner ads
on a 'medical news' site.

9\. Old papers get ignored, because they just aren't readily available. Life
science researchers regularly 'discover' something that was published in the
1970s.

10\. It is impossible to read all these papers. One part of my research field
easily has 10000 papers or more that could be justifiably relevant. Biology
has now reached the absurd tipping point where it is easier and cheaper in
terms of labour costs to do an experiment yourself rather than thoroughly
survey the literature.

Hopefully computer science papers aren't like this.

EDIT: grammar

~~~
return0
In life sciences, just read the figures. Papers are full of exaggerations,
overgeneralizations and other self-aggrandizing claims. AFAIK it's not like
that in physics, and CS is different altogether. Anyone who has tried to do
research to create a model based on biological data can attest how hard it is
to find reliable meaningful consensus values in the literature.

------
glup
I think one important thing to note is the hourglass format of most scientific
papers: statement of the broad problem and general importance of the question
at hand, gradually more specific identification of the current
challenge/contribution, down to the methods/model and results, and then
widening to look at the implications and relationship of the new findings to
the rest of the field.

Where you focus on the paper depends on what you want: if you are just
learning the central questions and theoretical views in the field then the
beginning and end are more useful; as you gain an understanding of the field
you may be more interested in the particular advances in a given paper and may
devote more attention to the middle.

At least in several of the fields I read regularly (linguistics, cognitive
science, NLP, and developmental psychology) there are three key paragraphs
that tend to have the most useful information: 1) the abstract (duh!) 2) the
last paragraph of the introduction (this usually has the most concise
statement of the motivation) 3) the first paragraph of the discussion (this
usually recaps whatever advances they make in a usable way; actual results
sections often contain a level of detail that isn't very memorable after a few
days).

Citations are shorthand for entire sets of ideas--they're a means by which
whole arguments can be referred to very concisely. One of the challenges in
reading a new literature is in learning what set of citations are commonly
reused and how, especially because the conventionalized citation of a paper
isn't necessarily what the author expected it to be known for, nor what you
might take from a paper on a first reading (or any number of readings). For
this reason I highly recommend reading papers with inline full citations
(Chomsky, 1965) rather than numeric/ indexical citations that you have to look
up [1].

Finally, mock-reviewing a paper is a fantastic way to make sure you're being
honest about how much of the paper you understand. Another technique at higher
grad school levels is mock-reviewing a paper from someone else's (=prominent
academic's) perspective--which imposes the dual constraint of understanding
the paper at hand as well as the theoretical perspective behind someone else's
critique.

------
acadien
Its the citation chain game! When you first start reading papers in a new
field you essentially have to read every citation present to understand whats
going on. As you accrue knowledge you'll need to read fewer citations and
you'll understand more of the jargon. That, to me, is the primary challenge.

It took me about 2 years before I could read a paper end to end and understand
it. Of course by that point I realized that reading most papers was a waste of
time. You often only need the figures, conclusion and methods section.

------
arihant
Like anything else, figure out why you're reading a paper, what are your
goals?

If you're reading for expanding your knowledge in a field, then a good area to
start is by reading well known dissemination in the field in past decade or
so. So, say, you're into datastrucures, read the paper that brought Red-black
tress by Rudolf Bayer. This is also a great route for somebody reading for the
first time. Well written papers are less off-putting. Most papers out there
are very poorly written.

If you're trying to extend the field, then it helps scouting what interests
you in extremely recent, interesting works. You can use sites like arxiv to
find edgy works done in past month of so, and then drill down the references
to understand where they came from. You can then work on improving that work.

So it depends on what you're trying to do. For software, I usually use
GoodReader on iPad. Nothing fancy, but it annotates, stores all my research
papers and organizes them. On computer, give Zotero a try.

If you're at a university, remember to catalog papers you read. It's so much
easier now with things like Dropbox. After you get out of the college, you
will need to pay huge amounts of money for them, so it behooves to maintain a
steady collection safe somewhere where you can always look back to. So catalog
what you read properly. Don't get overwhelmed and start losing the PDFs.

------
ams6110
As far as deciding whether to read a paper in depth, the advice I've heard is
to read the abstract, and if you're still interested read the conclusion. If
you're still interested after that, dig into the detail.

Don't let the "academic" format and style fool you. There's plenty of BS
churned out in academia, though if you're not used to reading papers it may
not be apparent at first.

------
jalcazar
Besides the S. Keshav's paper on how to read papers "How to Read a Paper",
take a look at the section "Reading Research Papers" by Margo Seltzer in
"CS261: Graduate Operating Systems (2014)"
[http://www.eecs.harvard.edu/cs261/notes/intro.html](http://www.eecs.harvard.edu/cs261/notes/intro.html)

------
austinl
In addition to the other advice, I'd recommend starting with the "seminal"
articles in topic of interest – articles that are heavily cited by other
researchers – before moving on to something more fine-grained. Even though
I've read a fair amount of academic literature, it'd be difficult for me to
pull an article off of arXiv and understand what's going on, since much of
academic writing is building off of prior work and requires context. Seminal
works are usually written more clearly because the author is trying to
introduce a new idea.

Google scholar makes it a bit easier to identify seminal works, as the results
return a count for "cited by". You'll see that some are cited thousands of
times by other researchers. Plus, these are typically the most interesting
articles to read either way.

~~~
pvg
A related approach is to also start with review/survey papers in a given
field. Beside giving you a more digestible overview, they'll also cite the
papers describing important results that one might want to read for the
details.

------
eng_monkey
With great skepticism. (I worked for years in academia and have published many
papers.)

------
pjungwir
A related question: How do you _access_ academic papers?

I've got a list of papers I'd like to read on the Church-Turing Thesis and
Quantum Computing, but I'm just a working freelance programmer with no access
to a research library. For instance how do I get this one?:

K. Steiglitz (1988), _Two non-standard paradigms for computation: Analog
machines and cellular automata_ , in Performance Limits in Communication
Theory and Practice, Proceedings of the NATO Advanced Study Institute, Il
Ciocco, Castelvecchio Pascoli, Tuscany, Italy, July 7-19, 1986, J. K.
Skwirzynski, ed., Kluwer Academic Publishers, pp. 173-192.

~~~
sireat
There is a reddit for precisely this purpose, I believe it is r/scholar

Mind you I have no first hand experience with this, usually just going to
author's site is good enough for most recent authors.

------
delinquentme
1) You will stand up and scream with delight when you realized that the things
which were once impossibly convoluted are not comprehensible ( yes this even
applies to abstracts )

2) Be cognizant of absorbtion / attention: Its easy to get stuck glossy-eyed
and pacing through the lines

3) As stated elsewhere in here: They can be filled with LOTS of crap -- keep
this in mind and work on attenuating your bullshit-detection.

------
azai91
Read the abstract a couple of times. Internalize every sentence. Then you can
start reading the rest of the paper. The abstract is meant to be easy to read
and it'll help you form an outline of the paper in your head before you start
reading. This will help you stay on track while you read the rest of the paper
as it's pretty easy to get lost in the middle somewhere.

------
streptomycin
Not that it's perfect, but [http://mendeley.com/](http://mendeley.com/) is the
best tool I've seen for organizing and annotating papers. If you don't have a
reasonable way of staying organized, then no matter how you read academic
papers, you'll wind up forgetting what you read eventually.

~~~
marinabercea
In addition, the bulk paper renaming feature has been an invaluable time saver
to me.

Throughout the years I've collected thousands of papers, many still unread,
but my 'must read' ('must skim' mostly) folder currently houses several
hundred of them and I can't imagine how much time I would've wasted by
manually renaming using the template {Author} - {Year} - {Title}.

Mendeley is free, but a paid alternative is Papers
([http://www.papersapp.com/](http://www.papersapp.com/)), which used to be
Mac-only and the reason I ended up discovering and using Mendeley. Haven't
personally tried it, but heard very good things about it.

My paper reading selection process consists in reading the abstract and the
conclusion. Quite a few papers have disappointing conclusions despite
attention-grabbing titles. If all is sound and promising, I keep it and
depending on other factors, I decide when to read it in its entirety and/or
where to store it for later use.

------
chm
Well it really depends on your situation but I guess the main question to ask
is: Do you possess the necessary background to read the paper? It takes a lot
of groundwork before you can read a paper and be confident you understood the
gist of it.

I personally have to sit down with pen and paper and toy with key equations,
maybe take out a book or two to make sure the author and I are agreeing on
specific vocabulary, or even double check symbols used which can differ from
what one is used to.

And keep in mind that completely novel, truly groundbreaking papers in a field
are rare. Most of what I've read is iterations on very well known basic
methods, a modification of this or that, some change to XYZ etc.

Just keep reading. And re-reading. And...

------
88e282102ae2e5b
Accepting that I have to read a paper two or three times before I really
understand it has been the biggest breakthrough I've had.

Usually this is because I just didn't have the background to understand the
paper until I read it, but academic papers can be pretty poorly written. For
example, a recent paper hinged upon something that I considered physically
impossible - only in the last paragraph did it explain why it wasn't (they
were even like "everyone is probably assuming this is impossible - here's why
it's not". I really wish that had led with that as it was an overwhelmingly
convincing argument.

------
brandonlipman
If it is a case study often there is usually a problem
definition/scope/abstract (it really depends on what type and who is
publishing). I often start with that and then skip to the back to te
conclusion. This gives me a bit if a road map of how and what to read. If I
read beginning to end I often get lost in confusing technical academic jargon.

After doing that I think about all the questions I have. Then go forth and
read it through keying in on the areas that may answer my questions.

I really like data and graphs so I usually spend lots if time playing around
and testing theories that I may have as I analyze.

------
jeeyoungk
[http://ccr.sigcomm.org/online/files/p83-keshavA.pdf](http://ccr.sigcomm.org/online/files/p83-keshavA.pdf)
\- this paper is actually pretty insightful.

------
MichaelGG
More literally, does anyone know of a way to physically read papers on a
Kindle? I've never been able to reformat even simple two-column PDFs into a
format suitable for ereaders. Calibre seems like a good start, but I get
mangled results. I end up printing stuff out. Which is OK, but I'd like to
have the option.

Even something as basic as trimming ridiculous margins seems rather difficult
to accomplish. Is there a software package that'll make this easy?

~~~
osdf
I had good results with
[http://www.willus.com/k2pdfopt/](http://www.willus.com/k2pdfopt/).

------
syllogism
Not start-to-finish, that's for sure. Or --- almost never.

If you're doing post-grad (or research) computer science, you should really
think about learning to read the literature faster. I was very slow at this
when I started, and I notice new grad students struggling at it.

A common problem is to try to read too deeply. You should get good at reading
a paper for 1 minute, or 5 minutes, or 10 minutes.

------
chris_wot
Try:

[http://violentmetaphors.com/2013/09/08/an-example-of-how-
to-...](http://violentmetaphors.com/2013/09/08/an-example-of-how-to-read-a-
vaccine-safety-study/)

And

[http://violentmetaphors.com/2013/08/25/how-to-read-and-
under...](http://violentmetaphors.com/2013/08/25/how-to-read-and-understand-a-
scientific-paper-2/)

------
chaosfactor
Read the abstract. Then the figures. Then the introduction. Then the
conclusion. If you're still in the paper, read the whole thing.

------
wsxcde
As seanwilson has pointed out already, academic papers are written to be
intelligible to experts in the field. They're not meant to be tutorials for
practitioners. So you can easily get stuck if you're reading a paper in a
field in which you're not an expert.

I also see a lot of useful tips here such as making notes, rewriting parts of
the paper, and so forth. I think these ideas only work when you're already
getting something out of the paper. These tips are optimizers, they can help
you get more out of a paper if you're already somewhat conversant in the
field.

In theory, if you're not an expert, you can keep following the citation trail,
read all the papers there, become an expert and finally read the paper you
actually want to read. I don't think this actually works. If you're not a
expert, the paper itself will seem like gibberish. You won't know what
citations are actually important and what citations were just pushed in to
please a reviewer. And even if you somehow do, the citations themselves will
be just as difficult to read.

So what are the solutions? First, seek out accessible papers. There are a lot
of tutorials that get published in magazines like the CACM and IEEE Spectrum.
These are written with an explicit goal of being accessible to a technical
non-expert audience, so you will get something out of these articles. Maybe if
you read one such article, you'll get the big ideas in the article and _then_
you can read the technical paper(s) that the article was based on. Since you
already know the big ideas, the technical paper won't seem so daunting. And
maybe now, you can follow up on a few citations.

The general trick is to find alternate sources that simplify and explain the
paper and then read the paper. Alternate sources can be tutorial articles,
slides, blog posts, textbooks, talks and so on. This is actually how people
learn to read papers in grad school. First, you go to few a masters level
classes where the professors teach from papers rather than textbooks but don't
necessarily expect students to read and understand all the details in the
paper. Next you go to a few seminar-type classes where professors and students
discuss the nuances of a number of important papers. There's a lot of non-
obvious spoonfeeding that happens: the professors use their expertise to pick
papers that important and accessible, they guide the discussion towards the
important parts of the papers, they point out flaws and discuss methodologies,
suggest projects for the students to implement and learn from, and so on. Over
time, the students absorb these lessons by osmosis and become good at picking
out and reading papers themselves.

If you're not going to grad school yourself, you'll have to recreate this
process of slowly building expertise in a field by reading papers and
comprehending them and trying to implement and recreate them. The key word is
slowly because you're not going to become an expert in a day, or even a month.
You'll have to keep going for a year or two and slowly you'll feel like a
blind man who can see more and more of his surroundings everyday.

------
papercruncher
The linked page on the tweet offers great advice, the only two things I can
add are:

* Take a sheet of paper and write down all definitions for easy reference

* If you are planning to use the learning from the paper in a production system, make sure you fully understand all stated (and unstated) assumptions the researchers made when presenting their results.

------
threatofrain
It depends on the difficulty of the field, but I think on average it takes
about 30-80 articles to get into a divergent field. Review articles can help a
lot, but you don't always get them for hotly moving fields.

I also think it helps a lot to be aware of popular experimental designs and
statistical techniques.

------
JamesWT
Has anyone looked at ReadCube? I found it when searching for software to help
manage research papers I needed to read. You can download papers through their
client, annotate and get analysis on papers.
[https://www.readcube.com/](https://www.readcube.com/)

------
IndianAstronaut
Like I am dating them. Visit them again and again to learn more about them and
what makes them tick.

------
luckydude
I've read thousands of papers. I read the abstract and the summary. Those tell
me if I want to read the paper.

They also tell me how to write a paper because everyone else is doing the same
thing. Tease in the abstract, please in the summary.

------
stewbrew
I think most people forget the first step: decide whether it's really worth
reading the paper. Don't spend too much time on weak papers that won't get you
anywhere. Unfortunately, most papers are "weak".

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Havoc
I don't for the most part. Don't want to deal with the paywalls and the
content i need is generally also available in a more digested format already.
i.e. My job doesn't require reading raw papers

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mad44
How I read a research paper:

[http://muratbuffalo.blogspot.com/2013/07/how-i-read-
research...](http://muratbuffalo.blogspot.com/2013/07/how-i-read-research-
paper.html)

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iskander
With other people! Impenetrably obscure papers really unravel in a journal
club. You can understand the main thrust of a paper much faster if you find a
social setting for talking about it.

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brudgers
Reading is a skill. It improves with practice. Breadth helps with depth. It's
ok not to grok things in their entirety. Enjoy what is grokked and the process
of grilling.

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jamesjardine
First a disclaimer: I am the founder of Qiqqa.com, which I wrote while doing
my PhD at the University of Cambridge, and without which, I quite literally
would have failed to complete my PhD.

I believe the key statement that has been iterated over and over here is that
only 10% of scientific papers are ever worth reading. And probably only 10% of
the text of those 10% are worth reading. They are they 1%.

This means that you end up with hundreds (if not thousands) of papers that you
think you might have to read, but have no way of knowing whether or not you
should until you have read them. Chicken meet egg.

I built Qiqqa (and wrote a PhD) to solve this from two broad directions: using
human intelligence and using artificial intelligence.

USING HUMAN INTELLIGENCE: While a load of people recommend printing out a
paper to read it, I believe that that course leads to a lot of future pain.
Highlighting and annotating while you read is absolutely important. It allows
you to skim through a paper and highlight only the important stuff. Then you
can come back later to properly read the important papers – only once you have
skimmed enough papers to get a more general sense of the domain you are
exploring. If you have printed out papers, it is very difficult to quickly
regroup and reread your annotated papers. However, if you have highlighted
your papers on your computer, laptop, tablet (or even phone while travelling
from Cambridge to London), free products like Qiqqa (or www.pdfhighlights.com)
offers you a simple annotation report to pull out all your annotations to not
only remind you of what and where the important fact are, but also to let to
jump straight to them to get reading immediately.

USING ARTIFICIAL INTELLIGENCE: An interesting side effect of reading more
scientific research is that the more you read, the more you have left to read.
Every paper you end up reading will make reference to another few papers that
you probably should read; like The Magic Porridge Pot. To solve the problem of
‘what should I read next’ (the working title of my PhD), I built into Qiqqa
the capability for it to ‘automatically read the papers for you’ using machine
learning. To this end, when reading a paper, Qiqqa can recommend to you the
most relevant papers to read using something called Topical PageRank which
calculates the relevance of a paper to what you are reading not only by its
similarity to what you are reading, but also by how well received (cited) that
paper is in your community. Think of it as having your own personal Google
where it biases results to satisfy your personal predilections. You can read
about how it works at [http://aclanthology.info/papers/topical-pagerank-a-
model-of-...](http://aclanthology.info/papers/topical-pagerank-a-model-of-
scientific-expertise-for-bibliographic-search).

Good luck with your research! Jimme

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dpeck
angrily while wondering why the two column style persists when most of the
reading is being down on wide screen monitors.

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lukeatuke
I need a guide on how to read textbooks.

