Journal Metrics - FAQs

Get involved

CiteScore 2016 values are here!

CiteScore metrics from Scopus are comprehensive, transparent, current and free metrics for serial titles in Scopus.

Read more

Search or filter below to find the sources of interest and see the associated metrics. Report using these annual metrics and track the progress of 2017 metrics with CiteScore Tracker 2017.

Be sure to use qualitative as well as the below quantitative inputs when presenting your research impact, and always use more than one metric for the quantitative part.

1. About CiteScore and its derivative metrics

CiteScore is a simple way of measuring the citation impact of serial titles such as journals. Serial titles are defined as titles which publish on a regular basis (i.e. one or more volumes per year).

CiteScore calculates the average number of citations received in a calendar year by all items published in that journal in the preceding three years. The calendar year to which a serial title's issues are assigned is determined by their cover dates, and not the dates that the serial issues were made available online. The method of calculation for CiteScore 2016 is illustrated below.

Graph

Articles-in-press are indexed in Scopus for some publishers, but are not included in the CiteScore calculation.

Articles-in-press in Scopus are not processed in the same way as regular Scopus items. For example, in Scopus the cited reference list is not available for articles-in-press and therefore they do not contribute citations to other documents in the same way as regular Scopus articles. Also, Scopus does not receive articles-in-press from all serial titles and publishers.

We therefore exclude articles-in-press from the CiteScore calculation to offer consistency and avoid bias between serial titles and publishers.

Abstracts are not indexed in Scopus and are not included in the denominator of the CiteScore calculation.

Citations to abstracts from other indexed papers are also not to be included in the numerator of the CiteScore calculation. There is no possibility of inconsistency in the types of documents included in the numerator and denominator in CiteScore.

All documents that are covered by Scopus as an integral part of the serial title are included in the CiteScore calculation.

CiteScore metrics (not CiteScore Tracker metrics) are reported once per year, and do not change, so they are suitable for reporting the citation impact of a serial title. Scopus.com is a dynamic database and changes daily.

The CiteScore metrics are created from a snapshot of Scopus, and represent the relative performance of serial titles at that point in time. The metrics for 2011 - 2015 have been calculated by recreating the Scopus database as it was at that time. The 2016 CiteScore metrics were calculated on 23 May 2017 using a data cut taken approximately 2 weeks earlier.

CiteScore Tracker is calculated in the same way as CiteScore, but for the current year rather than previous, complete years. The CiteScore Tracker calculation is updated every month, as a current indication of a title's performance.

The numerator (citation count) of the current year's metric builds up every month as additional citations are received, so that the construction is consistent with the construction of the complete year CiteScore. CiteScore Tracker is not based on a rolling 12 month window.

The metric values will be fixed in the spring, and then the Tracker will be calculated for the subsequent year. For example, CiteScore 2016 will be complete and fixed in the spring, when CiteScore Tracker 2017 will start to be displayed in Scopus.com.

CiteScore metrics are calculated from Scopus data. They are calculated from the same version of Scopus.com that users have access to, without any modifications being applied.

In comparison, the Impact Factor is generated from the Journal Citation Reports [JCR], and not from the Web of Science. As explained in this paper, the JCR links citations to the journal level, and is different from the Web of Science which links citations to the individual article level; it is not always possible to link a citation to the individual article, but it may still be possible to link it to the journal. The JCR database, from which the Impact Factor is calculated, is not available to users.

Scopus help functionality is available for both subscribers and guest users.

Corrections to Scopus content can be requested via the in-product support function, or by using this direct link to the feedback form: https://service.elsevier.com/app/answers/detail/a_id/14837/supporthub/scopus/. Approved corrections to the Scopus database will be incorporated into CiteScore Tracker at the next monthly refresh.

If you have calculated the CiteScore Tracker value yourself, the difference is due to the currency of CiteScore Tracker lagging behind that of the Scopus database. CiteScore Tracker is updated every month, and Scopus data are updated every day.

If you have calculated CiteScore for a complete year, such as CiteScore 2015 or CiteScore 2011, the difference is due to these metrics representing a snapshot in time of the Scopus database (Scopus) that is updated daily. These metrics represent CiteScore metrics as it was on the date of calculation, and ongoing improvements to Scopus data may have resulted in changes to the count of citations or documents. These improvements may be due to:

  1. Content initiatives, such as the addition of books, proceedings, and citations back to 1970: https://www.elsevier.com/solutions/scopus/content
  2. Addition of newly accepted titles. Find out more about title submission here: https://www.elsevier.com/solutions/scopus/content/content-policy-and-selection
  3. Error correction, such as filling occasional gaps in indexing and correcting links between citations and the document it is citing. Find out more about content coverage here: https://www.elsevier.com/__data/assets/pdf_file/0007/69451/scopus_content_coverage_guide.pdf

CiteScore metrics don't cost anything. They are free, just like the other journal metrics, SNIP and SJR, which we provide.

Yes, you can download a spreadsheet of all CiteScore metrics from journalmetrics.scopus.com.

CiteScore metrics are available for all serial titles in the Scopus April 2017 title list that have enough data available to calculate the metric. The types of serial titles available are journals, conference proceedings, book series, and trade journals.

Journals that are newly indexed in Scopus receive a version of CiteScore metrics as quickly as possible. A new serial will have CiteScore metrics in the year following the first year of indexing. The first CiteScore metrics will be based on a partial year of citations (A in this example), and part of a year of publications (B in this example).

This is one of the benefits of updating CiteScore Tracker monthly.

For example, a title that starts publishing in 2016 will receive a CiteScore Tracker 2017 around June 2017 and its first annual CiteScore 2017 metrics around June 2018.

  • The title may not be a serial title. A serial title is defined as one which publishes on a regular basis (i.e. one or more volumes per year). Stand-alone books do not have CiteScore metrics
  • If the title is a serial, it cannot have CiteScore metrics if there are not enough data. The minimum data needed to calculate CiteScore metrics are a partial year of citations (A in this example), and part of a year of publications (B in this example). There may not be enough data if the serial title is newly indexed, or has been discontinued in Scopus
  • Only serial titles that are being actively indexed in Scopus, and qualify for a 2015 CiteScore metrics and/or 2016 CiteScore Tracker metrics, received CiteScore metrics at launch. As new titles are added to Scopus, they will receive CiteScore metrics as explained in point 1.9
  • At launch (December 2016), serial titles that were covered in the May 2016 title may have CiteScore metrics. Titles that were added to the title list up to April 2017 are considered for CiteScore 2016 metrics. Titles added after April 2017 will not receive an annual CiteScore value until June 2018, but may receive a CiteScore Tracker 2017 if they have documents from 2014 – 2016.

There are two methodological differences from the Impact Factor, relating to the numerator (A) and denominator (B) of the calculation. Let's consider CiteScore 2016 for Forensic Science International.

For both CiteScore and Impact Factor, the numerator, A, is the number of citations received by Forensic Science International in 2016, but:

  • For CiteScore, A is the number of citations received in 2016 by any of the content it published in the 3 previous years, 2013, 2014 and 2015
  • For the Impact Factor, A is the number of citations received in 2016 by any of the content it published in the 2 previous years, 2014 and 2015. There is also a version of the Impact Factor which considers content in the previous 5 years. A detailed discussion of the Impact Factor numerator is available here.

This table gives some examples of citations which are and are not included in CiteScore. Citations not included in CiteScore will be counted by some other metrics – one reason why a basket of metrics is important.

Citation made to Forensic Science International in year Publication year of the document in Forensic Science International that was cited Will citation be counted
2016 2014 Yes
2016 2016 No
2016 2013 Yes
2017 2016 No (but it will be included in CiteScore 2017)
2014 2013 No (but it was included in CiteScore 2015)

The denominator, B, is a count of documents published in the 3 (CiteScore), or 2 or 5 (Impact Factor) previous years.

  • For CiteScore, B is all documents indexed in Scopus in these years, which includes original research articles, reviews, conference papers, letters, editorials, errata, and so on
    • Abstracts are not indexed in Scopus and so are not counted in the denominator
    • Citations to abstracts from other indexed papers are also not be included in the numerator of the CiteScore calculation. There is no possibility of inconsistency in the types of documents included in the numerator and denominator in CiteScore
  • For Impact Factor, B is the "citable items" indexed
    • Traditionally, Clarivate Analytics (previously Thomson Reuters) count all Research Articles, Notes (including Short Communications), Reviews (including Mini-Reviews), and full-length Proceedings Papers as source items. Other articles types are traditionally non-citable e.g. short abstracts, letters to the editor, news items, and editorials are always non-citable
    • But, if a "non-citable" type begins to show the characteristics of a research article, as described in this paper, there is a strong chance that it will be considered "citable". Case reports, predominantly found in medical literature, are a good example of this because there are so many types; the decision is made on a journal-by-journal basis, so a case study in one journal may be "citable" but a case study in another journal may not be
  • CiteScore counts all documents since they all have the potential to attract citations, and the Impact Factor counts the documents considered most likely to attract citations. CiteScore is independent of the document-type classification

Serials that publish a lot of documents that are not considered to be "citable" according to the Impact Factor calculation will most likely have a lower CiteScore than Impact Factor. This is because the denominator in the CiteScore calculation counts all items indexed in Scopus, whereas the Impact Factor considers only "citable items", generally taken to be articles and reviews.

Scopus has a broader coverage than the Journal Citation Reports, so that the amount of citations captured per serial title is on average around 10% higher. Serial titles that publish only or almost exclusively "citable items", generally taken to be articles and reviews, will benefit from the increase in the numerator of CiteScore relative to the Impact Factor while not being affected by the increase in the denominator due to all document types being counted.

A rank may be different because the ranks are calculated from a different database than the Impact Factor, using a different metric and a different subject classification.

Scopus has a more comprehensive coverage of serial titles than the Journal Citation Reports from which the Impact Factor is calculated, with around twice as many titles. The additional titles are also ranked amongst the titles which are ranked with the Impact Factor, and so can affect their position.

The subject classification used in Scopus is different from the subject classification used in the Journal Citation Reports. The different groupings of titles can also affect the rank.

The aim of the publication window is to capture a representative amount of a serial title's cited content, while at the same time making sure that that content is recent enough to reflect strategic changes in the serial title. The time window that is chosen for a metric calculated for all serial titles in a multi-disciplinary database like Scopus should be a compromise that is the best fit across all subject areas.

Research shows that a 3-year publication window is the best compromise, as reported in this paper. As shown in the chart below, 3 years is long enough to capture the citation peak of the majority of disciplines.

A shorter time window, such as 2 years, is unfair to slower moving fields such as Physics and Astronomy. A longer time window, such as 5 years, is unfair to more rapidly moving fields such as Biochemistry and Molecular Biology.

Graph

There are three reasons for this:

  • Recognizing the total influence of a serial title on the scholarly community
  • Reducing the ease of manipulation of the metric
  • Disagreements over document type classification

Recognizing the total influence of a serial title on the scholarly community

CiteScore credits a serial title for all citations that it receives, regardless of the type of document that receives the citations. A citation received by a letter indicates influence on the scholarly community just as much as a citation received by a research article, and CiteScore recognizes all of these citations.

Reducing the ease of manipulation of the metric

Crediting a serial title for citations received by all document types means that all document types must also be counted in the denominator so that the metric is fair. In other words, a serial title pays a cost in its CiteScore for every document it publishes that is indexed in Scopus (except articles-in-press, and abstracts which are not indexed by Scopus), since every document has the chance to contribute citations.

Consistency in document types between the numerator and denominator makes it more difficult to manipulate CiteScore. If the denominator counted a limited set of document types while the numerator considered citations received by all document types, then editors and / or publishers of serial titles could assign documents to a type that is not counted in the denominator. These "invisible" document types could still credit the numerator if they received citations, but would not be counted in the denominator, meaning that their citation contribution would be artificially inflated.

Disagreements over document type classification

Metrics that depend on document type classification will always be open to discussion and interpretation. Scopus has "style sheets" for each document type, and we match the publisher-provided document classification to the Scopus definition of document-type. Some serial titles may have unusual document-types that it is not straightforward to assign.

CiteScore is independent of document-types, so that interpretation and opinion in this classification does not affect the metric value.

You should not compare between subject fields using CiteScore. This metric is not field-normalized, and different publication and citation behavior of researchers in different fields affects the values, as well as differences in performance.

You can compare between subject fields in any of the following three ways:

  • Using the CiteScore percentile within a subject field. Journals that are in the top 10% of distinct fields have a similar citation impact on that field, even though this percentile is based on a CiteScore with a different absolute value
  • Use SNIP, which is a field-normalized metric
  • Use SJR, which is a field-normalized metric

The meaning of a CiteScore of 3.64 differs per subject field, because researchers in different subject fields behave differently, and there are different levels of citations.

CiteScore Percentile serves as the baseline to understand what a CiteScore value means. CiteScore Percentile compares the CiteScore of a serial title to that of others in the same subject field, and indicates the relative position of the serial title. For example, a serial title might have a CiteScore of 3.64 and a high CiteScore Percentile in its field of 93%, or a CiteScore of 3.64 and a low CiteScore Percentile in its field of 34%.

The definition of self-citations that is relevant for CiteScore metrics is citations made by documents published in the serial title to other documents published in the same serial title. In almost all cases, these citations are a responsible and useful behavior to indicate related documents to readers; it is reasonable to expect related papers to be published in the same serial title. Consequently, journal self-citations are included in CiteScore metrics.

The following pieces of information should be given when quoting a CiteScore metric value: name of metric; value of metric; year to which metric refers; currency of data from which metric was calculated; data source; serial title that the metric refers to. You should also include a url or link to the source of the metrics. This will have the format: www.scopus.com/sourceid/xxxxxxx

It is also good practice to quote the subject category within which a metric is calculated for CiteScore Percentile, Rank, and Quartile 2.

The minimum information you should provide is the metric name and year. A link into Scopus and the context of the metric (e.g. on a journal home page) will provide the rest of the information.

Examples of how to refer textually to a CiteScore metric value quoted for a particular serial title are:

  1. CiteScore™ 2013 for Journal A. Calculated by Scopus on 31 May 2014. Available from
    www.scopus.com/sourceid/xxxxxxx
  2. CiteScore™ Tracker 2016. Calculated by Scopus on 15 November 2016. Available from
    www.scopus.com/sourceid/xxxxxxx
  3. CiteScore™ Percentile 2015. Calculated by Scopus on 31 May 2016 for biomedical sciences. Available from
    www.scopus.com/sourceid/xxxxxxx

2. The journal "basket of metrics"

One of the "Golden Rules" of using research metrics is that quantitative input should always be based on at least 2 metrics; this helps to prevent bias, and to prevent driving undesired changes in behaviour. This Golden Rule requires a "basket of metrics" with different characteristics from which metrics appropriate to the question can be selected. The basket needs to contain metrics that measure different ways of being excellent, and also a combination of straightforward and more complex metrics, as discussed here.

The basket of citation metrics offered by Scopus for serial titles has contained SNIP and SJR since 2010. These metrics remain a valuable part of Scopus' metrics offering for serial titles, but user feedback showed that there was still a gap. There was no simple citation metric, that users could validate themselves, to complement the more complex SNIP and SJR. Scopus has therefore filled this gap by adding CiteScore metrics.

Each of the metrics for serial titles in the Scopus basket of metrics measures a different type of performance of serial titles. CiteScore and IPP (Impact per Publication) both measure citations per document, and so we decided to retain only CiteScore so that we could provide:

  • Increased transparency for Scopus users
    • CiteScore is calculated from same version of Scopus.com that our users see
    • IPP calculated from a version of Scopus.com that is customized by CWTS
  • Regular updates
    • CiteScore is calculated by Scopus, and can be generated quickly and regularly
    • IPP is calculated by CWTS by a more time-consuming process, so monthly updates are not possible
  • Independence from document type classification
    • CiteScore is based on all document-types
    • IPP uses only articles, reviews and conference papers

IPP continues to be freely available from CWTS.

A serial title metric can be used by:

  • Researchers to help to determine which serial titles to read, where to publish their research, and to showcase their research outputs
  • Librarians and information professionals to help to decide which serial titles to subscribe to
  • Research performance managers to help to analyze their organization's publication strategy, and to encourage researchers to publish in serial titles that are aligned with institutional strategy
  • Tenure and promotion committees to help to evaluate the impact of the outlets that a researcher's outputs are published in
  • Publishers and editors to help to establish and monitor publication strategies

Your selection should partly be based on your preferences, and partly on the characteristics the metric needs to have to help you to answer your question. The table below will help you to make your selection.

CiteScore CiteScore Percentile SNIP SJR
Measures Citations per document Relative position within subject field based on CiteScore Relative citations per document Prestige of citing sources
Open to validation in Scopus? Yes Yes No No
Size-normalized? Yes Yes Yes Yes
Subject field-normalized? No Yes Yes Yes
Communicate magnitude Yes No No No
Update frequency Annually, and CiteScore Tracker metrics monthly Annually Annually

For example:

  • If your question is about which serial title within a subject field has the highest citation impact, and you prefer to use a straightforward metric that you can validate yourself, then you could use CiteScore or CiteScore Percentile
  • If you want to compare citation impact between journals in different fields, and you prefer a straightforward metric, then you should use CiteScore Percentile, but not CiteScore
  • If you need to compare citation impact between journals in different fields, and are happy using a complex metric, then you could use SNIP or SJR as well as CiteScore Percentile
  • If you want to compare the citation performance of a set of serial titles that were recently accepted for indexing by Scopus, then you could use CiteScore or CiteScore Percentile

CiteScore 2016, CiteScore 2015 and so on are static metrics and do not change. They can be used for reporting purposes, such as for showcasing the citation impact of a particular serial title.

CiteScore Tracker is a dynamic metric. It is calculated for the current year and is updated every month to provide an up-to-date view on performance of each journal title.

You should avoid using a metric for serial titles when your question is specifically about the impact of anything that is not a serial title. For example:

  • If you want to know the citation impact of a particular document, then a metric for serial titles is only suitable under some conditions
    • Say a document has been published in a serial title whose CiteScore is 2.45. It is incorrect to say that the document's citation impact is 2.45; you should use the metrics about that particular document, so that you can say, for example, that it has received 12 citations and 2 mentions in mass media
    • It is correct to state that the document has been published in a serial title whose CiteScore is 2.45
  • If you want to know the citation impact of a researcher, then a metric for serial titles is only suitable under some conditions
    • Say a researcher has published an article in a journal whose CiteScore is 7.64. It is incorrect to say that the researcher's citation impact is 7.64; you should use metrics about that researcher, so that you can say their output of 6 documents has been cited 57 times, and viewed 163 times, in total
    • It is correct to state that the researcher has published an article in a serial title whose CiteScore is 7.64

Journalmetrics.scopus.com is designed to allow you to create sets of serial titles, and to look at their performance relative to each other according to the family of CiteScore metrics, SNIP and SJR. You can, for example, look at serial titles that are members of the same subject category, that are provided by the same publisher, or that are larger than a particular minimum size.

Scopus.com is designed to allow you to see the details of a single serial title, and to investigate the documents that underpin the metrics.

SNIP and SJR are calculated by CWTS and Scimago Research Group, respectively, from a set of Scopus data that Elsevier provides to these groups. The time taken to ship the data, for CWTS and Scimago Research Group to customize the data sets and calculate the metrics, and for the metrics to be returned to Scopus and incorporated into Scopus' workflows, is too long to enable an update every month.

CiteScore's monthly update offers several benefits, and if these are important to help you to answer your question, then this is a reason to select CiteScore from Scopus journal basket of metrics.

CiteScore Percentile indicates the relative standing of a serial title in its subject field. Each subject field is divided into 100 equal-sized percentiles based on the number of serial titles, and a serial title is assigned to a percentile based on its CiteScore. A serial that has a CiteScore Percentile of 96% is ranked according to CiteScore as high or higher than 96% of serial titles in that category.

CiteScore Percentile is calculated by taking all serial titles with CiteScores in a particular subject field, and ordering them by their CiteScore from high to low. CiteScore Percentile for a serial title S, is calculated by applying the equation:

CiteScore Percentile of S = [ (L + (0.5 x S) ) / N ] x 100

Where

  • L = number of serial titles in subject field with a CiteScore lower than X
  • S = number of serial titles in the subject field with CiteScore X
  • N = total number of serial titles in the subject field with any CiteScore
       

This method does not give a 100th percentile rank. Scopus rounds down to the nearest whole figure in displaying these percentiles, in line with the spirit of this calculation method.

Consider the fictional example illustrated in the table below. The serial titles in this subject field have been ranked from high to low according to their CiteScores.

  • For Proceedings C:
    • CiteScore = 1.79
    • L = 26 (there are 26 serials with a CiteScore lower than 1.79)
    • S = 1 (only Proceedings C in this subject field has a CiteScore of 1.79)
    • N = 29 (there are 29 serials in this subject area)
    • CiteScore Percentile Rank of Proceedings C = [ (26 + (0.5 x 1)) / 29 ] x 100 = 91%
  • For Journal X:
    • CiteScore = 0.39
    • L = 5 (there are 5 serials with a CiteScore lower than 0.39)
    • S = 2 (Journal W in this subject field also has the same CiteScore of 0.39)
    • N = 29 (there are 29 serials in this subject area)
    • CiteScore Percentile Rank of Journal X = [ (5 + (0.5 x 2)) / 29 ] x 100 = 20% 
Serial title CiteScore Rank CiteScore Percentile
Proceedings A 2.14 1 98%
Journal B 1.87 2 94%
Proceedings C 1.79 3 91%
Journal D 1.53 4 87%
Journal E 1.51 5 84%
Journal F 1.45 6 81%
Journal G 1.39 7 77%
Journal H 1.38 8 74%
Journal I 1.35 9 70%
Journal J 1.29 10 67%
Proceedings K 0.99 11 63%
Proceedings L 0.97 12 60%
Proceedings M 0.94 13 56%
Journal N 0.89 14 53%
Journal O 0.72 15 50%
Journal P 0.68 16 46%
Journal Q 0.59 17 43%
Journal R 0.57 18 39%
Journal S 0.52 19 36%
Proceedings T 0.51 20 32%
Journal U 0.46 21 29%
Proceedings V 0.42 22 25%
Journal W 0.39 23 20%
Journal X 0.39 23 20%
Journal Y 0.36 25 15%
Journal Z 0.32 26 10%
Proceedings A1 0.32 26 10%
Journal B1 0.15 28 5%
Journal C1 0.00 29 0%

Note that a journal has one CiteScore, but a different CiteScore Percentile for each subject field it is indexed in. The highest CiteScore Percentile is shown for a serial title by default, and you can investigate a serial title's relative position in the various subject fields it is part of in Scopus.com.

Note that there is an alternative and slightly simpler method that does not use the value S. It indicates the percentage of scores that fall below a given score, rather than the percentage of scores that fall at and below a given score, as implemented here. The results differ only for tied titles.

Document Count is one of CiteScore's associated metrics. Document Count displayed in the context of CiteScore is the denominator of the CiteScore calculation; it is the sum of documents published in the serial title in the 3 years prior to the year the metric is calculated for (B in this example). It is shown as part of the serial basket of metrics because:

  • Document Count helps to provide transparency on CiteScore
  • Document Count is a valuable research metric in its own right. The size of a serial title, and whether it is growing year on year, is an indication of the raw scale of a serial title within the research community
  • Document Count is a Snowball Metric (Scholarly Output), which has been endorsed by research-focused institutions as important in benchmarking performance

Citation Count is one of CiteScore's associated metrics. Citation Count displayed in the context of CiteScore is the numerator of the CiteScore calculation; it is the sum of citations received in one year by documents published in the 3 previous years (A in this example). It is shown as part of the serial basket of metrics because:

  • Citation Count helps to provide transparency on CiteScore
  • Citation Count is a valuable research metric in its own right. The citations received by a serial title is an indication of the raw impact of a journal on the research community
  • Citation Count is a Snowball Metric, which has been endorsed by research-focused institutions as important in benchmarking performance

% Cited is one of CiteScore's associated metrics. % Cited displayed in the context of CiteScore is the proportion of the documents considered in the denominator of the CiteScore calculation (B in this example) that have received at least 1 citation in the CiteScore's numerator (A in this example). For this metric, it does not matter whether one of the documents in B has received 1 or 101 citations in A; it only matters that it has been cited at least once. It is shown as part of the serial basket of metrics because:

  • % Cited helps to provide transparency on the proportion of a serial title's content that is responsible for its CiteScore
  • % Cited is a valuable research metric in its own right. It indicates the consistency with which a serial title's contents are reliably cited, regardless of the number of citations received (use Citation Count if this is important)

Quartiles are bands of serial titles that have been grouped together because they occupy a similar position within their subject categories. The quartiles are:

  • Quartile 1: serial titles in 99-75th percentiles
  • Quartile 2: serial titles in 74-50th percentiles
  • Quartile 3: serial titles in 49-25th percentiles
  • Quartile 4: serial titles in 24-0th percentiles

A title might have a different quartile within each different subject area it is included in. For example, Serial Title A might be categorized in "Oncology", with a CiteScore percentile of 84%, and "Cancer Research", with a CiteScore percentile of 73%. These percentiles equate to Quartile 1 and Quartile 2 respectively.

The Top 10% of serial titles can also be viewed.

3. Scopus and CiteScore metrics

There are two reasons for this:

  1. CiteScore Tracker is updated every month, but the link to the citing documents is generated via a live search which is updated every day. You may notice some differences due to the currency of CiteScore Tracker generally being behind the currency of Scopus.com
  2. Each citing document may cite multiple documents from the serial title whose CiteScore metrics you are looking at, so the number of citing documents may be lower than the number of citations

CiteScore Tracker is updated every month, but the link to the citing documents is generated via a live search which is updated every day. You may notice some differences due to the currency of CiteScore Tracker generally being behind the currency of Scopus.com.

Scopus subscribers can see all documents underlying the numerator and denominator for both the annual CiteScore values and the CiteScore Tracker. Guest users of Scopus are able to see the most recent 20 documents within CiteScore Tracker and all documents when they register for a free in Scopus.

Scopus uses a different classification system (the All Science Journal Classification, or ASJC) from ones you might be used to. The assignment of serial titles to subject classifications is done manually, and a serial title can belong to multiple categories.

Improvements that you would like to see can be fed back for consideration via Scopus. https://service.elsevier.com/app/answers/detail/a_id/14837/supporthub/scopus/. Scopus has already made a number of subject area changes as a result of customer feedback..

Scopus coverage represents substantial publisher activity from all regions in the world. It is the most globally representative commercial abstracting and indexing database available.

Many major scientific publishers are located in North America and Western Europe, and therefore Scopus covers many titles from publishers located in these geographical areas. However, Scopus covers content from publishers located in more than 120 different countries from all continents.

A complete overview of the titles covered by Scopus, and their publishers, can be found in the Scopus Source List: https://www.elsevier.com/solutions/scopus/content.

Please note that the publisher name used on the journalmetrics.scopus.com site is based upon current information and not a title's history. For example if Journal A moves from Publisher X to Publisher Y in 2016, we will update that title's information to show Publisher Y for all available CiteScore years.

There is no bias towards any publisher with respect to the priority of processing their content. However, the different ways of sourcing content from publishers impact on the time it takes to receive and process the content.

Content is sourced from the publisher in different ways, depending on the format that is available from the publisher. Direct electronic feeds are setup wherever possible which enables fast processing of the content. Content that is not available in electronic format may be sourced from paper.

The Journal Citation Reports, which hosts the Impact Factor, includes about 12,000 titles covered in Web of Science Core Collection. These are largely all also covered by Scopus. There are around 50 titles that are not indexed in Scopus either because they are in process of being added, or because there are business reasons not to cover them such as discontinuation of coverage.

Serial titles are classified using the ASJC (All Science Journal Classification) scheme. This is done by in-house experts at the moment the serial title is set up for Scopus coverage; the classification is based on the aims and scope of the title, and on the content it publishes.

A complete overview of the ASJC classification scheme and serial title classifications can be found in the Scopus Source List and more information about classification can be found in the content coverage guide: https://www.elsevier.com/solutions/scopus/content.

To better reflect their areas of research, the Scopus team have updated the subject classifications given to over 150 titles. This was done through a combination of publisher feedback and proactive re-evaluation. These new subject areas are reflected in their 2016 annual CiteScore metrics and CiteScore Tracker 2017 values, but not in the 2011 – 2015 metrics. As a result you may find a difference between the subject areas used in the 2011 – 2015 metrics and the 2016 metric values.

The subject areas visible at the top of a title's Scopus source page, always reflects the most recently allocated classification.