If you’ve ever tried to figure out which journal is the best fit for your research or wondered how journals classification is carried out, you’ve probably come across terms like Quartiles (q1 q2 q3 q4 journal), h-index, Impact Factor (IF), and Source Normalised Impact per Paper (SNIP). These metrics might sound technical, but they are simply tools to measure how much attention a journal’s research gets. Here’s a straightforward explanation of what they mean and how they work

Quartiles in Journals Classification: Ranking by Performance

The system of dividing journals into four quartiles, Q1, Q2, Q3, and Q4, was created to make it easier to compare their quality and impact within a specific field. This idea became popular through Scopus and Journal Citation Reports (JCR) databases, which rank journals based on metrics like citations. The concept builds on the work of Eugene Garfield, who introduced the Impact Factor, offering a way to see how journals stand up against others. Quartiles break things down further: Q1 represents the top 25% of journals in a category, while Q4 includes those at the lower end. It's a straightforward way to help researchers determine which journals are most influential in their areas of study.

• Q1: Top 25% of journals in the field (highest-ranked).
• Q2: 25-50% (mid-high-ranked).
• Q3: 50-75% (mid-low-ranked).
• Q4: Bottom 25% (lowest-ranked).

However, not all Q3 or Q4 journals are necessarily a disadvantage. While they may not be as well-known, they are still important in scientific research. Some of the benefits include:

• Affordability: These journals are easier for researchers to access, especially for those on a tight budget.
• Focused Topics: They tend to cover more specific, niche areas of study, making them great for in-depth exploration of certain subjects.
• Great for New Researchers: Q3 and Q4 journals classification can be a good place for new researchers to publish their first paper and gain experience in the publishing world.
• Ideal for Basic Research: They’re a great option for research that focuses on the basics of science

Finally, publishing your article in a Q3 or Q4 journal doesn’t mean it lacks value or won’t make an impact. If your work presents new findings that address a real problem, it can still attract attention, even when published in a lower-ranked journal.

h-index: A Balance of Quantity and Quality

The h-index score is an important factor in journal classification. It looks at the number of articles a journal has published and how often those articles are cited. It balances quantity (how many articles a journal publishes) with quality (how many of its articles are referenced).

For example, if a journal has an h-index of 15, it means it has published 15 articles, each cited at least 15 times. It’s a simple way to measure a journal’s influence without focusing too much on just one super-cited article or a bunch of rarely cited ones.

How h-index works:

Let’s say a journal has published 4 articles, and the number of citations for each article looks like this:

• The 1st article has 10 citations – exceeds 1 citation.
• The 2nd article has 24 citations – exceeds 2 citations.
• The 3rd article has 5 citations – exceeds 3 citations.
• The 4th article falls short of 4 citations.

In this case, the journal has three articles that each have at least three citations. The fourth article doesn’t hit the mark, so the h-index stops at 3.

This metric can help researchers, professionals, and institutions decide if a journal publishes research that gets noticed and cited by the academic community. It’s not the full picture, but it’s a useful starting point for understanding the journal’s influence.

Impact Factor: Citation Average

The Impact Factor (IF) is a number that shows how often a journal’s articles are cited on average over the past two years. It helps you understand how much attention the journal’s research gets from other scholars and it also helps with journals classification.

How it works?

To calculate the IF, look at how many times articles from a journal were cited in the past two years. Then, you divide that by the total number of articles the journal published in those two years. This gives you an average citation count per article. 

Example:

Let’s say we want to figure out the IF for Journal A in 2023:

• In 2021 and 2022, Journal A published 50 articles.
• In 2023, those articles were cited 200 times in total.
• You take the total citations (200) and divide it by the total number of articles (50): 200 ÷ 50 = 4

So, Journal A has an Impact Factor of 4, meaning its articles were cited, on average, four times each. A higher Impact Factor often places journals higher in classification, but keep in mind that it’s not the full story. Some specialised journals may have lower Impact Factors even though they’re highly respected in their niche.

SNIP: Fair Comparisons Across Fields

SNIP (Source Normalised Impact per Paper) is a valuable metric in journals classification because it goes one step further. It measures contextual citation impact and takes into account the fact that different research fields have different citation habits. For instance, medical papers often get cited a lot, while mathematics papers don’t, even if they’re equally important in their fields.

SNIP adjusts the average citations a journal receives based on these differences, making it easier to compare journals across disciplines.

Example:

• Journal A publishes in a low-citation field like social sciences and averages 3 citations per article. Adjusted for its field, its SNIP might be 1.6.
• Journal B publishes in a high-citation field like biomedicine and has an average of 8 citations per article. After adjustment, its SNIP might be 1.2.

SNIP makes sure journals in fields with fewer citations still get the recognition they deserve.

What it tells you:

SNIP is especially useful for journal classification because it levels the playing field between disciplines. A higher SNIP score suggests that a journal’s articles are cited more often than expected for its field. It’s a helpful tool for comparing journals, but it’s just one of many ways to evaluate a journal’s influence or importance.

Below is a concise summary table of the four journal classification systems, followed by key considerations:

Journal ranking system comparison

System	Purpose	Calculation	Key Insights
Quartiles (Q1-Q4)	Ranks journals by performance within a field (e.g., biology, engineering).	Journals divided into four equal groups based on citation metrics (e.g., Impact Factor): • Q1: Top 25% • Q2: 25-50% • Q3: 50-75% • Q4: Bottom 25%.	• Q1/Q2 = high prestige. • Q3/Q4 = affordable, niche-focused, beginner-friendly. • Lower quartiles ≠ low-value research.
h-index	Measures journal influence by balancing article productivity and citations.	A journal has index h if it published h articles each cited ≥ h times. Example: h-index=15 means 15 articles cited ≥15 times each.	• Avoids over-reliance on single highly cited papers. • Useful for gauging consistent impact.
Impact Factor (IF)	Indicates average citation attention per article.	IF = (Citations in year Y to articles from Y-1 and Y-2) ÷ (Articles published in Y-1 and Y-2). Example: 200 citations ÷ 50 articles = IF 4.	• Higher IF = higher ranking. • Field-dependent: STEM > humanities. • Less meaningful for niche fields.
SNIP	Compares journals fairly across fields by normalizing citation practices.	Adjusts raw citations per paper by field’s typical citation density. Example: 3 citations in social sciences (SNIP=1.6) vs. 8 in biomedicine (SNIP=1.2).	• Levels comparison between high/low-citation fields. • SNIP >1 = above-field-average impact.

Key Considerations for All Systems

1. No single metric tells the whole story – A journal may rank highly in one system but lower in another.
2. Field-specific biases – Metrics like IF and SNIP adjust for disciplinary differences (e.g., mathematics vs. medicine).
3. Beyond rankings – Lower-quartile/niche journals offer unique advantages (accessibility, specialization).
4. Research goals matter – Choose a journal based on audience fit, not just classification.