Abdalsamad Keramatfar

University of Qom, Academic Center for Education, Culture and Research

Papers

Total Citations

104

H-Index

About

Abdalsamad Keramatfar is a researcher whose work sits at the intersection of bibliometrics and cutting-edge artificial intelligence. His primary research areas include sentiment analysis, graph neural networks (GNNs), and the quantitative evaluation of scientific literature. Keramatfar’s most influential contribution is his comprehensive bibliometric study of sentiment analysis literature, which has garnered 88 citations. This work systematically mapped the research landscape up to 2016, identifying key trends, subject categories, and publication patterns that have served as a foundational reference for scholars in natural language processing. More recently, he has turned his attention to the rapidly evolving field of graph neural networks, producing a Scopus-based bibliometric overview that traces GNN research from its inception in 2004. This 2022 paper, with 16 citations, provides a crucial quantitative and qualitative assessment of GNN trends, helping researchers navigate this complex domain. By applying rigorous bibliometric methods to two of the most dynamic areas in computer science, Keramatfar has established himself as a valuable chronicler of scientific progress, offering clear roadmaps for future research directions.