This study will focus on investigating longitudinal trends of e-learning research. Text mining techniques will be used to extract implicit, hidden knowledge from the open source global e-learning research literature. An extensive e-learning focused query will be applied to the Social Science Citation Index (SSCI) and ED/IT-Lib database. The taxonomies of e-learning articles will be grouped into clusters by analyzing abstract with text mining techniques. The results will provide aggregate e-learning research time trends, aggregate e-learning article bibliometrics, and overall research themes based on total e-learning article retrieved.