What is Impact Factor?
The Impact Factor (IF) is a measure of the frequency with which the average article in a journal has been cited in a specific year. It is used to measure the importance or rank of a journal by calculating the times its articles are cited. The Impact Factor is considered the number one ranking value for scientific journals. Impact Factors are a benchmark of a journal’s reputation and reflect how frequently peer-reviewed journals are cited by other researchers in a particular year. The Impact Factor helps to evaluate a journal’s relative importance, especially when compared with others in the same field.
One journal’s impact factor on its own doesn’t mean much. Instead, it’s important to look at impact factors of multiple journals in the same subject area. This way, one can determine if the impact factor of the journal of interest is high or low compared to other journals in a subject area.
Impact factor calculation
What is a good impact factor? Calculating impact factor of a journal is simple. Just average number of times that a journal’s articles are cited over the past 2 years. That is; in any given year, the impact factor of a journal is the number of citations received in that year by articles published in that journal during the two preceding years, divided by the total number of articles published in that journal during the two preceding years.
A = number of times articles published in 2015 and 2016 were cited during 2017
B = the total number of citable items published in 2015 and 2016
A/B = 2017 impact factor
2017 IF= (Citations 2016+ Citations 2015) / (Publications 2016+ Publications 2015)
New journals, which are indexed from their first published issue, will receive an impact factor after two years of indexing; in this case, the citations to the year prior to Volume 1, and the number of articles published in the year prior to Volume 1 are known zero values. Some journals which commenced with a volume other than the first volume won’t get an impact factor until they have been indexed for 3 years.
How to find the Impact Factor of a Journal?
If you want to find impact factor of any article, you can use the above Impact Factor formula and manually calculate the IF.
What is a good journal impact factor?
There is no good score that shows the quality of a journal because the IF varies significantly among discipline, field, and topics. If you start analysing what is a good journal impact factor, then, you should keep this thought in mind. “It is something better than nothing”. So, having impact factor of 1 is always better than having no impact factor. There is nothing like high impact factor. It is just a basic correlation measure on the number of publications and citations for the articles in the journal.
For instance, Nature reports an Impact factor of 41.5 for Nature Biotechnology, whereas Nature Genetics has an IF of just 29.4. There is a huge difference between both these ranks; however you need to evaluate those numbers in the appropriate context. Among all journals in the category of Genetics and Heredity (167), only one has an IF greater than Nature Genetics. Correspondingly, Nature Biotechnology’s IF is the second-highest in the category Biotechnology and Applied Microbiology (N = 162). So regardless of the great difference in IF’s, both journals are Number 2, in their respective fields.
Why not to believe Journal Impact factors? [CASE STUDY]
It is a common myth that researchers should publish their works in the Journal indexed by brands like Scopus or Thomson Reuters (yet not restricted to). Because these Journal Indexing organizations provide Impact factors which are treated as prestige of technical journals for the last 2 decades. But, don’t you think they are still private operators giving ranks for research works? Don’t you think they could change the ranking framework that favours them get more business and benefit? Yes, that is reason Journal’s impact factor is expelled by many scientists as useless or even destructive to the mainstream researchers.
ScienceMag, in this article has clearly explained why we should not always trust Impact factors. According to their report, we have to examine 2 different things on the metrics used for calculating Impact factor.
- Average number of citations are misinterpreted
- IF calculations are always opaque
Let’s examine the first part. In any given journal, the small fraction of papers gets most citations, whereas the vast majority of papers get very very few citations. That is 80% of the citations are received by only 20% papers, which mean all the papers published in the journal cannot be considered of same quality. So, the average number of citations is often highly misleading. This makes the predictive measure useless, meaning that publishing a paper in a high-impact journal does not necessarily mean that it is more likely to be cited. Next is, these private companies doing Impact factor calculation can change their database ranking algorithm as per their desire. The citation data these organization curate are not open to public.
Image Source: Nature
The above sample is a data set from Nature, Science & PLOSone publications. It is evident that, up to 75% of articles in any given journal had lower citation counts than the journal’s average number. So attempting to use a journal’s IF to forecast the impact of any specific paper is close to guesswork. It indirectly states that the no single number can capture the worth of a scientist’s work. Journal’s IF isn’t the issue but it’s the way we think about scholarly progress that needs the work.