Reflecting the trends in the academic landscape of special education using probabilistic dynamic topic modeling

Abstract

PurposeSpecial education is the education segment that deals with the students facing hurdles in the traditional education system. Research data have evolved in the domain of special education due to scientific advances. The present study aims to employ text mining to extract the latent patterns from the scientific data.Design/methodology/approachThis study examined the 12,781 Scopus-indexed titles, abstracts and keywords published from 1987 to 2021 through an integrated text-mining and topic modeling approach. It combines dynamic topic models with highly cited reviews of this domain. It facilitates the extraction of topic clusters and communities in the topic network.FindingsThis methodology discovered children’s communication and speech using gaming techniques, mental retardation, cost effect on infant birth, involvement of special education children and their families, assistive technology information for special education, syndrome epilepsy and the impact of group study on skill development peers or self as the hottest topic of research in this domain. In addition to finding research hotspots, it further explores annual topic proportion trends, topic correlations and intertopic research areas.Originality/valueThe results provide a comprehensive summary of the popularity of research topics in special education in the past 34 years, and the results can provide useful insights and implications, and it could be used as a guide for contributors in special education form a structured view of past research and plan future research directions.