TELS: Evolution patterns of research keywords from the evidence of PNAS Social Sciences topics - Liu, Bing; Shi, Mengfan; Kuang, Yi; Jiang, Xin (Frontiers in Big Data, 2022)
By reviewing scientific literature, researchers may obtain a comprehensive understanding of field developments, keeping abreast of the current research status and hotspot shifts. The evolution pattern of keywords is supposed to be an efficient indicator in revealing the shifting and sustainability configuration of scientific concepts, ideas, and research hotspots. Here we take an extensive investigation of the evolution of keywords among all publications in PNAS Social Sciences Topic from 1990 to 2021. Statistical tests show a universal clustering of the keyword-mentioned time series, accompanied by the emergence of a log-normal distribution of the most mentioned keywords. Based on this, we introduce a novel schema of four patterns (TELS), which are Transient impact type, Explosive impact type, Large impact type, and Small impact type respectively, to illustrate the evolution of keywords. The TELS schema can be used to capture the whole life circle feature of any proposed keyword, from a pool of candidates. By dividing the entire time into four periods, we also introduce the concept of elite keywords to reveal the temporal feature of social science focus. An explicit transition from anthropology and evolution research to neuroscience and social problems research can be observed from the evolution diagram. We argue that the proposed method is of general sense and might be applicable to other fields of science.