A contemporary science map through the lens of IEEE and ACM periodicals

2026-04-28

AI Summary

This study investigates emerging research trends reflected in recently launched journals by IEEE and ACM. Through qualitative content analysis, it systematically examines the titles of newly established journals from both organizations to uncover evolving patterns in publication models, thematic focus, and interdisciplinary convergence. The analysis reveals three key findings: ACM exhibits a pronounced shift toward artificial intelligence; open access has become the dominant publishing model; and substantial thematic overlap exists within each organization’s journal portfolio. By providing empirically grounded, reproducible evidence, this work offers valuable insights into the strategic positioning of cutting-edge research in computer science and engineering.

Abstract

ACM and IEEE are the two premier associations on computing and electrical/electronics engineering which publish and organize the great majority of periodicals and conferences, respectively, serving these disciplines. Science is a constantly evolving process, and these publication fora are expected to follow the trends. In this article, we focus on the periodicals published by the two associations and seek to detect and/or confirm any contemporary science trends as these are reflected to the periodical titles established recently. Our study is rather qualitative than quantitative, aiming at revealing patterns immediately comprehensible and validatable by the reader. Among the most notable patterns, we see a growing preference of both associations for the open access mode of publication; we also observe ACM's orientation toward AI-focused periodicals, and most importantly, a significant theme overlap among periodicals of the same association and this is valid for both ACM and IEEE.

Problem

• science trends
• periodical titles
• theme overlap
• open access
• AI-focused

Innovation

• science mapping
• open access
• AI-focused periodicals
• theme overlap
• qualitative trend analysis