Analyzing Evolution in Citation Pattern within an Emerging Subfield of Control Science and Technology

Citation analysis is a bibliometric research method that utilizes mathematical, statistical, and logical approaches to analyze citation patterns in scientific journals, papers, and authors. This study employs citation analysis to investigate the emerging subfield of Affective Computing in control science and technology. Beginning with the leading journal in this field, IEEE Transactions on Affective Computing, 15 important journals were identified to map the research landscape. Furthermore, it reveals an overall upward trend in the impact factors of journals within this field from 2013 to 2022. Through the use of the Web of Science database, an automated data retrieval program was developed to collect and process a large amount of empirical data, addressing any anomalies within the dataset. Statistical analysis and examination of empirical data were conducted to observe the evolution of citation pattern among scholars in the field and investigate the relationship between this evolution and the widespread increase in journal impact factors. The research findings indicate that the citation time patterns among scholars remain stable with no significant changes, while the average number of references per article has shown a notable increase.