Purpose: The KIEAE Journal has offered a platform where scholars and practitioners discuss research issues andexplore resolutions concerning sustainable environment and ecological architecture for last two decades. Uponpublishing the 100th volume, the editorial board of the KIEAE Journal initiated analyzing the research trends of theKIEAE Journal to reorganize and modify the existing research area structure and to rebuild research informationsystem to further enclose a wider spectrum of current research issues and case studies concerning sustainable cityand architecture. Method: First this study performed desriptive statistical analysis of articles per each research area,and then used a text mining technique, A priori algorithm, to capture causality and latent coherence betweenkeywords. Result: The analysis suggests that the research areas for which only a few manuscripts were publishedcan be restructured. Also it suggests integrating research areas that have similar titles and/or whose actual researchcontents and methods are not much distinguished from each other. Unfortunately, text mining that intended tocapture the keyword causality was not successful, because too many and diverse keywords may degrade learningeffectiveness of the A priori algorithm. This study suggests using a group of predefined standard keywords, suchthat authors can pick up useful keywords out of the keyword pool.