Citation metric: a) A numerical measure of the influence of a journal or journal article based on the number of citations.
b) An simplistic way of evaluating the value of research based on flawed numbers, that fails to take into account the actual complexities involved in evaluation, but is still seen as being valuable because it provides a clear numerical way to rank things, as the people doing the evaluation very often have neither the time nor the background to evaluate the research personally.
In this post, we’ll look at the most basic citation metric of all: citation counts. Simply put, a citation count is a count of citations that have been made to <something>. The <something> could be a book, a book chapter or essay, a journal article, a white paper, a technical report, a conference paper, a video, a webpage, a blog, a newspaper article, a magazine article, a preprint, a dataset, a patent, an unpublished communication, a corporate research report, a standard, an image, a performance, and so on and so forth.
The citation could also appear in almost any one of those (though perhaps not an image!).
Where to find citation counts
It seems simple enough. We have Article A, written by one of our many notable faculty. How many times has it been cited? But of course, not all citations are equal! If we want to evaluate Professor A’s work, we only want citations made by people who are peers of Professor A; fellow researchers, academics, or professionals. We also only want citations that appear in proper research, academic, or professional publications, not popular magazines, newspapers, and the ilk, since we want to evaluate what impact Professor A’s research has had on their field.
To that end, the Library offers two commercial tools , and one free one.
Web of Knowledge (also know as the Web of Science, the Science (or Social Science or Arts and Humanities) Citation Index. The oldest source of citation data (besides counting it yourself), with data going back to the 1970s in some disciplines It has a fairly narrow focus, and only indexes citation made in what they consider the significant journals in particular fields. It doesn’t count citations made in anything that isn’t one of the significant journals. So if your article was cited in a book, a patent, a journal the WoK doesn’t consider significant, etc. the WoK doesn’t know about it.
Scopus. A newer database that has citation data for citations made in a selection of journal and conference papers published from 1996 onward. It covers quite a bit more journals than WoK, and does cover some conference proceedings, but it focuses a bit more on science, technology, and engineering disciplines. It does include some coverage of the social sciences (business and psychology predominately), and the arts and humanities, but those aren’t its strengths. Like the WoK, it doesn’t cover books, and doesn’t cover all journals.
Google Scholar. Google’s attempt to index all of the scholarly material on the Internet. It can generate citation counts, but it has a tendency to list duplicates if a particular research article is posted in multiple places, which throws off citation counts, and it can only index citations made in material that is a) on the Internet (it connects to Google Books so it’s one of the few places to find citations in books) and b) that allows Google to index the full text (or otherwise makes the list of references in an article available). The main drawback to Google Scholar is that, because it depends on publicly available data, it can be easy for the unscrupulous to manipulate.
The problems with citation counts
The core problem with citation counts is that assumption upon which it depends for value, is not entirely true. The assumption is that a work is cited because it is a worthwhile piece of research.
There are many reasons why an author may choose to cite a particular article that have nothing to do with approving of the article being cited.
Consider Fleischmann, Martin; Pons, Stanley (1989), “Electrochemically induced nuclear fusion of deuterium.” J. Electroanalytical Chemistry 261 (2A): 301–30. This article has, according to the Web of Knowledge, received over 790 citations. A naive reading of the citation count would lead one to declare that this must be a very influential article. And, in a sense, that’s correct; except for the fact that it’s one of the more famous cases of science performed badly, and that most of the citations are articles stating that they can’t duplicate the results, or that the results are wrong, or writing about it as an example of science done wrong.
Even if an article isn’t fraudulent, or wrong for more innocent reasons, there are plenty of reasons that a citing article may cite an article in order to disagree with its conclusions, particularly in the social science and humanities. These negative citations don’t necessarily diminish the worth of the article in question, but they don’t really support the idea of citation counts as a measure of worth.
There can also be political, or social reasons to cite an article, that have nothing to do with its value as a piece of research. Perhaps the author is a friend that is applying for tenure. Perhaps they did a favor for the author, and now the author is repaying them. Perhaps they want to borrow the legitimacy of a more famous author by citing them in their own work, even if it’s not particularly relevant. Perhaps they’re a grad student, and it’s been “suggested” that they cite some papers written by their advisor.
Sometimes the journals you’re publishing in can get in on the act. There are some less-than-scrupulous journals that, in order to boost their prestige, encourage authors to cite other articles within the same journal, or within another journal from the same publisher. Others inadvertently stumble into the same patterns of distortion without intending to (particularly in very niche research areas where there may only be a few people worldwide writing on the topic).
Other issues with citation counts can be more systematic. A article written for a small, niche, audience will be cited less than one written for a broad audience, but may be (within that context) a very important, influential, article. A review article (one summing up the current state of research on a topic) will usually be cited many more times than an average original research article. Obviously, self-citations by any author on a paper should be discounted (but aren’t by any of the tools listed above). Sometimes authors will cite an article incorrectly (getting the pages wrong is common, but sometimes they get something as basic as the journal wrong!), which means that, unless you catch that, it won’t get counted.
Using citation counts
So, we’ve covered the trust part of citation counts, which leaves us with the hard task of verifying them. Or, in other words, how do we use these flawed, easily misinterpreted numbers?
The answer is to not treat them as simple numbers with simple, obvious, meaning. There are no shortcuts when it comes to evaluating a work, whether it’s an article, or a book, or something else.
You can use the tools above to get the basic citation count for an article, but once you’ve done that, you have more work to do. You’ll need to look at the citing articles and see how they used the cited article, and then decide whether to count them. You’ll have to look at where the cited article, and the citing articles were published, their acceptance policies, and other factors. You’ll have to see what a typical citation count is for articles on the same (or similar) topic to make sure you’re correctly comparing it to its peers.
Or, you can use them without all of the supplemental analysis, but with an understanding that they are not error free, and that they have fairly large error bars. How large are those error bars? It’s difficult to estimate.
Ultimately, the most accurate way to evaluate an article, or book, or whatever, is to have someone you trust (or yourself), who understands the subject material and methodology, read the article and give their opinion. Citation counts can act as a very crude filter to find works that may be significant, but in the end, you have to dig deeper.