In rough terms, the journal impact factor can give you a roughan idea of how many citations you can expect to receive per year for a given article. Note that this is based on the relevant database. Google Scholar citation counts tend to be two or three times larger from my experience. Note also that the distribution of article citation counts are highly skewed. So many will get fewer citations, but hopefully as you aggregate over a body of work, central limit theorem will kick in. So it's a reasonable guide to a benchmark how many citations you should expect over the body of your work.
- Mean impact factor: Based on your stated quartile impact factors, I'm going to guess that your average impact factor per article is around 0.8 (e.g., top quartile is around 2+;2 or 3+; second quartile is around 1.5; third quartile is around 0.5, based on discipline it could be different).
- Mean time since publication: I'll guess 1.5 years. I.e., half-way between 0 and 3 years.
- Discounting self-citations: Impact factor does not discount self-citations, but you have. So let's say 20% of citations are self-citations, especially early on in an articles life.
- Number of articles: you say 17
expected citations = mean IF * mean time since publication *
self-citation discount * number of articles
= 0.8 * 1.5 * 0.8 * 17
= 16.32 (i.e., 16 articlescitations)
Of course, if you are using Google Scholar as your metric, then you should multiply expectations by a factor 2 or 3 (so that gives you somewhere around 32 and 39). You could also get a more refined estimate if you calculated expectations for each article separately and then summed the expectations. Note also, that there is quite a bit of uncertainty about the timing issue. For example, with impact factor, the firstA few months often don't count for the clock or the citations.caveats:
- If you are using Google Scholar as your metric, then you should multiply expectations by a factor 2 or 3 (so that gives you an expected citation count somewhere around 32 and 39).
- You could get a more refined estimate if you calculated expectations for each article separately and then summed the expectations.
- There is quite a bit of uncertainty about the timing issue. For example, with impact factor, the first few months often don't count and sometimes differences between accepted versus online access versus published with page numbers might make a difference.
Also, note that in theory, you could stop doing research today, and the formula would predict that 15 years, you could expect about 160 citations. As with all things, this depends on various assumptions. But if you are comparing your citation count to senior researchers who have been publishing for 20 years, then you need to really understand the fundamental role of time passing in generating citations.
More generally, citation counts per article and even on aggregate can be quite noisy and the underlying distribution can be heavily skewed. So the difference between being above or below expectations may be whether you have one or two articles that have really taken off in terms of citations.
Other options that can may may or may not go into grey territory:
- Self-cite where appropriate. Some citations will come from others seeing how your work is being cited. By self-citing, you are providing a template, and further secondary exposure to your work.
- Collaborate and co-author papers with leading figures in your field. When they publish without you, they may cite your co-authored work.
- Think about what topics receive more citations and do work on that. Important review articles, meta-analyses, methodological papers with a clear recommendation, etc.
