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I am currently writing a paper in which I have many topics to describe. It would not be productive to read and cite papers or even books on the topics because I just have to describe them very briefly as an introduction to some follow up topics.

For "private" use I would just use the corresponding Wikipedia articles but that is considered bad practice in academic papers.

So do you have any tips how to get credible definitions of and/or short introductions into (in my case computer science) topics without searching through dozens of papers/books for some useful/credible parts?

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  • You did check sources besides Wikipedia, right? You are not looking for things to cite blindly?
    – Raphael
    Jul 22, 2014 at 7:12
  • What I am looking for are resources that are as easily accessable and extensive as wikipedia but considered credible. For Example: If you want to present some tools in your paper which you used for static code analysis you want to give the reader a short introduction into what static code analysis is. But you don´t want to spend the whole day looking for that information so Wikipedia would be perfect.
    – asquared
    Jul 22, 2014 at 8:06
  • There's a reason why Wikipedia is not considered a citeable reference for research articles; any similar collection would share the same fate. Peer reviewed articles and textbooks are the answer, as others have noted. Yes, you have to look into them. Yes, that's work. It's also the way it is, and probably has to be.
    – Raphael
    Jul 22, 2014 at 8:08
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    Most schools have access to a fairly extensive electronic library full of articles. I have also used scholar.google.com to find sources acceptable for academic papers.
    – Josh
    Jul 22, 2014 at 16:04
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    It would not be productive to read and cite papers or even books on the topics because... — [citation needed]
    – JeffE
    Jul 22, 2014 at 22:56

5 Answers 5

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I tend to use books for this sort of thing. For example, if I need a definition of "data mining", I do a Google Books search for that term. A book about "data mining" is going to define the term in the introduction or first chapter, so it will usually be in the pages that are part of the free preview.

Another option is to look at the citations used in the Wikipedia article itself, and then look up those articles. Wikipedia tends to be pretty good at citing the key article(s) for a particular subject.

Also, it's helpful to know a few online cite-worthy dictionaries that you can search for common definitions. For example, The Stanford Encyclopedia of Philosophy is useful for philosophical terms.

There's also Scholarpedia, which is a peer-reviewed online encyclopedia. It's not as extensive as Wikipedia. However, in my field at least, the articles tend to be written by well-known names.

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    +1 for Wiki citations. I often check those when trying to learn something new.
    – Kimball
    Jul 21, 2014 at 18:24
  • To @Kimball +1 for Wiki too. Wikipedia is often a fantastic source of general information. You can use the cited sources to expand your understanding of the topic. I would warn that the Wikipedia pages are crowd sourced and I've found a citation to a source which wouldn't qualify as peer-reviewed, thus probably not acceptable by academic institutions.
    – Josh
    Jul 22, 2014 at 16:02
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Consider:

  • textbooks on a given subject,
  • review (rather than research) articles on a given subject,
  • key papers (e.g. the one where a given subject was introduced for the first time).

Good places to start:

  • http://scholar.google.com/ and look for general and (typically) highly cited books or papers,
  • the references sections on Wikipedia.
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I agree with the idea of referencing books. You may not want to buy a book for each topic.

I suggest using libraries. Most people writing papers have access to a university or other reference library. Many will let you go in and read books there, even if you are not affiliated with the university.

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I read abstracts of journal articles I can find on JSTOR. Abstracts generally serve as concise summaries of entire papers. They're also written by the author(s) of the article, so you know the emphasis will be on the core of the topic, not on side-note information.

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You need not discard a Wikipedia definition if it is one that you like. Print sources can be equally sketchy as anyone can print books (cf. "Fart Proudly", by Ben Franklin). It sounds like you merely want correctness, not sources of definitions anyway.

As long as the definition is fairly accurate, just cite it as you would a print source, but (like with all internet resources) give the date and time along with your citation, since the Internet can change out from under you.

In any case, it's not really academics who have a problem with Wikipedia, it's the publishers and ever since the printing press, they've spent a good while curating influence on the minds of the Establishment. But obviously, with the Internet, it all needs re-addressed.

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  • The credibility of Wikipedia is not the subject of this question; you might want to move this answer to this question, where that is the subject of the question.
    – ff524
    Jul 21, 2014 at 20:33
  • Note: A democratic form of reputation ranking and a unified data store where academics can pull information off of the internet to store a source as they found it, is a project I'm currently working on to make the right solution in the Internet Age. (see also hypothes.is)
    – Marxos
    Jul 21, 2014 at 20:43
  • @ff524: The OP makes the claim that it is "bad practice" and I'm disputing that view, but will edit to make it more clear.
    – Marxos
    Jul 21, 2014 at 20:44
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    Actually, the OP claims that citing Wikipedia for definitions is considered bad practice by academics, not necessarily that it is objectively bad practice. If you have evidence that it is not generally considered bad practice by academics, that could be more relevant :)
    – ff524
    Jul 21, 2014 at 20:53
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    In any case, it's not really academics who have a problem with Wikipedia — [citation needed] :-)
    – JeffE
    Jul 22, 2014 at 22:58

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