International Journal of Artificial Intelligence SJR 2023-2024

International Journal of Artificial Intelligence - SJR - Journals are important tools for disseminating knowledge but not every journal is equal. A journal that is better metric-wise is considered to have better scientific quality. One of the measures to rank journals is SCImago Journal Ranking. Evaluating scientific quality is a very tough problem that has not easy to get to answer. SJR provides some sort of relief for that tough problem. Using Scopus data, SCImago Journal Rank (SJR) offers metrics that are the average number of weighted citations received in a year over the number of documents published in the previous three years. Citations are weighted depending on the source that they come from (subject field, quality, the reputation of the journal, etc.) With SJR, the subject field, quality, and reputation of the journal has a direct impact on the power of a citation. SJR scores are available from the two databases listed below: SCIMago Journal and Country Rank. SJR of International Journal of Artificial Intelligence is freely accessible from the SCImago website.

What is SJR?

The SCImago Journal Rank (SJR) indicator is a standard of the scientific impact of scholarly journals that considers both the number of citations received by a journal and the value or prestige of the journals where the citations are received from. SJR is a portal that consists of the journals and specific scientific indicators of the country they originate in which are developed from the crucial information contained in the Scopus database (Elsevier). It is also a measure of prestige based on the idea that "all citations are not created equal." So SJR will help you know how prestigious International Journal of Artificial Intelligence is in comparison to other journals.

In simple terms, SJR is a standard that measures the scientific influence and impact of journals that considers both the number of citations obtained by a journal and the prestige of the journals to which such citations belong. It studies the scientific power of the average article in a journal, it demonstrates how important to the global scientific discussion an average article of the particular journal is.

International Journal of Artificial Intelligence SJR Year Wise

Note : This information is taken from the SCIMago.

Note : This information is taken from the SCIMago.

How is SJR calculated?

SJR scores are computed using network analysis of citations received by journals. The methodology considers both the number of citations as well as the source of citations, with citations from journals with high prestige having more value than those from journals with lower prestige. The prestige worth depends on the field, quality, and reputation of the journals that the citations were sourced from. Scimago uses the Scopus database and journal classification scheme to rank journals by quartiles across subject areas. Citation data is created from more than 34,000+ titles from over 5,000 international publishers and country-specific performance metrics from around 240 countries worldwide. Computation of SJR is an iterative process that distributes prestige values among the journals until a steady-state solution is reached, similar to the methodology used for Google PageRank. The average SJR value for all journals in Scopus is 1.0. So in order to know the SJR rating International Journal of Artificial Intelligence must be indexed in the Scopus database.

Strengths and Limitations of SJR

The strengths of SJR includes -

• Assigns Higher Value/Weight To Citations Form More Prestigious Journals
• Compensates For Differences In Field, Type And Age
• Meaningful Benchmark Is Built In – 1 Is Average For A Subject

SJR drawbacks include -

• Absence Of Construct Definition
• Lack Of Data Coherence
• Gaps In Journals Coverage And Comparative Purposes
• Issues Related To Comparability Of Citation Networks
• Lack Of Ordinal Position Of Ranking Journals
• Use Of Retrospective Data Backups And Stability
• Methodological Issues In Quartile Construction
• Comparatively Low Discriminative Indicator Capacity
• Issues Related To Parameter Fixing Procedures

It can be concluded that, even though the idea behind SJR is commendable and the indicator is an improved and sophisticated alternative to other indicators of quality. It still omits a large amount of data, forcing into question its transparency, reliability, and suitability for analytical purposes in its current stage, although most of the problems that have been identified can be solved and in the future it might be improved.

Even if SJR has flaws it still is one of the best tools out there to measure the prestige of International Journal of Artificial Intelligence as researchers and organisations still depend on it.