شناسایی خوشه‌های مفهومی و بازیگران اصلی در پژوهش‌های سنجش توجه: تحلیل شبکه‌های هم‌نویسندگی و هم‌رخدادی کلیدواژه‌ها

Abstract
Purpose: This research aims to explore and analyze research trends in the field of studies related to "attention measurement." Specifically, this study examines the co-occurrence patterns of keywords as well as the co-authorship of authors in this area.
Methodology: The present research method is documentary and specifically utilizes a bibliometric analysis approach. The data used in this study have been extracted from the reputable and comprehensive Web of Science database, covering the period from 2000 to 2025. For data analysis and the extraction of patterns related to the research topic, specialized bibliometric software such as VOSviewer and Biblioshiny has been employed.
Findings: In this study, 1,519 documents with an average age of 8.75 years are included across 474 publications. Each document has been cited an average of 30.61 times, and 5,652 authors have contributed to their production. The results indicate that research in this field is expanding. Studies in Iran began in 2016 and peaked in 2024, reflecting the interest of domestic researchers in this research area within the country. The top five countries in publishing these documents are the United States, China, Germany, Australia, and the United Kingdom, with Iran ranking 15th with 39 articles. The most significant international collaborations are associated with China, the United States, Germany, the United Kingdom, and Australia. Of the 1519 studies conducted between 2000 and 2025, the majority of documents are in four main research areas: psychiatry, neuroscience, clinical neurology, and psychology. The top authors in terms of the number of articles are affiliated with the University of Wollongong and the University of London, and they have published most of their work in the journals of Clinical Neurophysiology and the International Journal of Psychophysiology. In terms of the frequency of vocabulary, the methods of measurement, electroencephalography, brain modeling, event-related potentials, brain-computer interfaces, deep learning, continuous performance tests, convolutional neural networks, and neuropsychology, have been the most frequently mentioned. This indicates the researchers' use of these methods for their studies and their reliability in these methods. The emergence of terms such as "deep learning," "machine learning","convolutional neural networks," and "binary neural networks" reflects the recent global trend in research focusing on deep learning and machine learning.
Conclusion: Based on the clustering extracted from the keywords, nine different conceptual categories of documents were identified, which include concepts related to attention measurement and neuroscience, computational models of the brain and cognition, behavioral and cognitive studies, neuro-cognitive assessments, attention deficit/hyperactivity disorder, executive functions and attention, cognitive functions and emotions, auditory attention, and neurocognitive disorders. The most frequently repeated keywords include terms that refer to measurement methods and tests in the fields of cognition and attention, which, in terms of frequency, include electroencephalography, brain modeling, event-related potentials, brain-computer interfaces, deep learning, continuous performance tests, convolutional neural networks, and neuropsychology. Recent studies show a global shift in research focus towards deep learning and machine learning, highlighted by the rise of terms such as "deep learning","machine learning","convolutional neural networks" and "binary neural networks". The research suggests that Iranian researchers should collaborate with international experts in attention assessment to enhance research quality and global impact. This partnership would allow them to learn new methods, utilize advanced equipment, and access extensive data, ultimately improving their scientific advancement and credibility. Policymakers and scientific managers should assess the strengths and weaknesses of attention assessment research to develop fair policies that support researchers. These policies should offer material and moral support to outstanding researchers, boost research impact, and enhance the country's scientific reputation by encouraging publication in reputable journals and fostering international collaborations. Future research should evaluate Iran's scientific productivity, competence, and network analyses in attention assessment, comparing it with developed and regional countries using citation databases such as Scopus and PubMed. Using co-word analysis methods, the intellectual structure of the attention assessment field should be examined and compared with two types of keywords: abstract keywords and keywords. The effective factors and barriers to scientific collaboration among Iranian researchers in the field of attention assessment should be investigated. The co-citation networks of Iranian researchers in attention assessment need to be analyzed, and the scientific outputs related to attention measurement tools should be reviewed in citation databases. The examination of scientific outputs in citation databases should focus on influential factors affecting attention and on outputs related to attention disorders. Moreover, the impact of social and cultural factors on research design helps adapt methods to different groups and reveals cultural diversity. Investigating ethical issues in research promotes responsible practices and the creation of ethical guidelines. Additionally, understanding genetic factors related to attention and its disorders provides insights into their genetic causes, with relevant keywords aiding in the comparison of research findings.