Citation Metrics & Research Impact

Citation metrics quantify the impact of research by measuring how often it is cited by other researchers. They are used by researchers (to track their own impact and that of others), by institutions (in hiring, tenure, and promotion decisions), by funders (in grant evaluation), and by journals (to demonstrate their reach and influence). While metrics are useful for these purposes, they are also frequently misused — applied inappropriately, given excessive weight, or used as a substitute for actual reading and evaluation of the work. Understanding what metrics measure — and what they do not — is essential for their responsible use.

No single metric captures the full impact of research. Different metrics emphasize different aspects: citation counts measure total influence; citation rates measure influence per paper; journal-level metrics measure the average citation rate of the journal; author-level metrics measure cumulative productivity and impact; alternative metrics (altmetrics) measure attention outside traditional citation channels. Each has limitations and is appropriate for different purposes. The San Francisco Declaration on Research Assessment (DORA) emphasizes that research should be evaluated on its own merits, with metrics as supporting information rather than as the primary basis for evaluation.

Hrisana Journal tracks standard citation metrics for our published articles and journals. As a relatively new journal, our metrics are still developing, and we are working towards indexing in major databases (Scopus, Web of Science) that will enable standardized metric tracking. We are committed to the responsible use of metrics in our editorial decisions and in our communications with authors and readers.

Article-level metrics measure the impact of individual articles. The most basic is total citation count — how many times the article has been cited by other indexed publications. Citation counts can be obtained from Google Scholar (which has broad coverage but includes some non-peer-reviewed sources), Scopus, Web of Science, and PubMed (for biomedical research). Citation counts should be interpreted in the context of the field (citation practices vary widely), the year of publication (older articles have had more time to accumulate citations), and the article type (reviews typically receive more citations than original research).

Field-weighted citation metrics (such as the FWCI from Scopus) normalize for these factors, providing a measure of relative citation impact: an FWCI of 1.0 means the article has been cited at the average rate for its field, document type, and publication year. FWCI values above 1.0 indicate above-average citation impact. These normalized metrics enable more meaningful comparisons across fields and time periods than raw citation counts.

Journal-level metrics include the Journal Impact Factor (JIF), CiteScore, and SCImago Journal Rank (SJR). The JIF, calculated annually by Clarivate Analytics, is the average number of citations in a given year to articles published in the journal in the previous two years. It is widely used but has significant limitations: it is a journal-level average that does not reflect individual article impact (most articles in a journal receive fewer citations than the JIF, with a long tail of highly-cited articles pulling up the average); it can be manipulated by editorial practices; and it varies substantially across fields. CiteScore and SJR use similar but slightly different methodologies. These metrics should be used cautiously and never as the sole basis for evaluating research or researchers.

The h-index, proposed by physicist Jorge Hirsch in 2005, is the most widely used author-level metric. A researcher with an h-index of h has published at least h papers that have each been cited at least h times. The h-index attempts to balance productivity (number of papers) and impact (citations per paper), avoiding the distortion that a single highly-cited paper can introduce in total citation counts. However, the h-index also has limitations: it is field-dependent (different fields have different citation practices), it favours researchers with longer careers (h-index can only increase over time), and it does not account for the position of the author in the author list (which indicates contribution level in many fields).

Variations on the h-index attempt to address some of these limitations. The g-index gives more weight to highly-cited papers. The m-index is the h-index divided by years since first publication, normalizing for career length. The i10-index (used by Google Scholar) counts the number of papers with at least 10 citations. Each captures a slightly different aspect of publication record, and none is universally superior. For early-career researchers, all of these metrics should be interpreted cautiously, as they have not had time to accumulate.

Beyond quantitative metrics, author impact is best assessed by reading the work, considering the breadth and depth of contributions, evaluating the researcher's role in the field (invited talks, editorial roles, professional service), and seeking input from peers who can evaluate the work in its full context. Metrics can supplement but cannot replace this qualitative evaluation. Institutions and funders increasingly recognize the limitations of metrics and are moving towards more holistic evaluation processes, as encouraged by DORA and the Leiden Manifesto for research metrics.

Altmetrics (alternative metrics) measure attention to research outside traditional citation channels: mentions in news media, shares on social media, bookmarks in reference managers, views and downloads, policy mentions, and other forms of engagement. Altmetrics capture immediate attention (citations take years to accumulate; altmetrics can appear within days of publication) and reach beyond academia (citation metrics only capture academic impact). They are particularly valuable for research that has policy, practice, or public engagement implications.

Altmetrics also have limitations. They can be manipulated (artificially inflating social media mentions, for example). They may reflect attention that is negative (criticism rather than endorsement) rather than positive. They are biased towards research that is "shareable" — surprising, controversial, or accessible — and may undervalue technically important work that is less accessible to broad audiences. They are also field-dependent, with some fields generating more social media attention than others. Altmetrics should be interpreted as a complement to, not a replacement for, citation metrics and qualitative evaluation.

For researchers interested in maximizing the broader impact of their work, several strategies can help. Writing accessible summaries of research findings (for press releases, blog posts, social media) extends reach beyond the immediate field. Engaging with journalists and providing clear explanations of research significance can lead to media coverage. Depositing publications in open repositories (green OA) and publishing in open-access journals (gold OA) removes access barriers. Presenting at conferences, participating in policy discussions, and engaging with practitioner communities all extend the reach and influence of research.

The responsible use of research metrics is a shared responsibility. The San Francisco Declaration on Research Assessment (DORA), signed by thousands of individuals and organizations, articulates key principles: do not use journal-based metrics (like JIF) as a proxy for the quality of individual research articles; be explicit about the criteria used in evaluation; consider the value of all research outputs (not just articles), including datasets, software, and other products; and when using metrics, use a range of metrics appropriate to the evaluation. The Leiden Manifesto for research metrics provides ten principles for the responsible use of metrics, complementing DORA with practical guidance.

For researchers, responsible use means understanding the limitations of metrics when interpreting your own performance and the performance of others. For evaluators (hiring committees, promotion committees, grant review panels), it means using metrics as one input among many, with primary weight on qualitative evaluation of the actual research. For journals, it means being transparent about how metrics are used in editorial decisions and avoiding practices that artificially inflate metrics. Hrisana Journal is committed to these principles and does not use journal-level metrics in editorial decisions about individual manuscripts.

As a researcher publishing with Hrisana Journal, your work will be openly available, maximizing its potential for citation and broader impact. Our standard citation tracking (once we are indexed in major databases) will provide article-level citation data. Our open-access model supports broad dissemination, and our commitment to responsible metrics ensures that your work is evaluated on its scientific merits. Visit our Submit Manuscript page to begin your submission, or review our Author Guidelines for preparation requirements.