Analyzing Paper Citation Trend of Popular Research Fields
Clicks: 1
ID: 313109
2024
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
0.0
/100
1 views
0 readers
AI Quality Assessment
Not analyzed
Readership in this journal
Ranked #558 of 705 articles by views in Journal of Computing & Biomedical Informatics
Most read
Least read
Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 705 in total.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
The ever-expanding volume and diversity of scientific literature pose a significant challenge for researchers in detecting emerging, current, and future research trends. A trend represents the prevailing direction of research within a defined timeframe. Detecting trends involves identifying areas of growing interest over time, while trend analysis involves gathering data and discerning patterns. Despite the utilization of diverse methods for analyzing and identifying trends in scientific research, there remains a lack of comprehensive understanding regarding the significance of following research trends for citation of research papers. The objective of this research is to examine the significance of monitoring trends in Computer Science (CS) research, the influence of aligning with these trends on paper citations, and the correlation in citation patterns among papers within the CS domain. We analyze trends in CS conference papers and the evolution of research fields from 1985 to 2017 using the Microsoft Academic Graph (MAG) dataset of CS papers in the L1 field of study (FoS). Our experimental findings reveal that Data Mining, Artificial Intelligence, Computer Vision, Machine Learning, and Database research exhibit the highest publication trends. Additionally, our results suggest that papers within the same field demonstrate similar citation trends.
| Reference Key |
imported_1777059109_69ebc525ead77
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | Sheeraz Ahmed |
| Journal | Journal of Computing & Biomedical Informatics |
| Year | 2024 |
| DOI |
DOI not found
|
| URL | |
| Keywords | Keywords not found |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.