Abstract
Evolution is a central concept that unifies all areas of life sciences. Despite longstanding scientific efforts in science education, the public's scientific awareness of evolution still needs to improve. Furthermore, teaching evolution is subject to recurring controversy. This study aimed to investigate the gap between public understanding of evolution seen through online spaces and contents in a school curriculum and explore its reasons. A content analysis was conducted using data mining on a major online portal in Korea. It examined the characteristics of creating and consuming content on evolution through the online portal service based on analyzing the number of posts related to biological evolution and active participants. It also discussed the feasibility of automatic document classification to distinguish between scientific understanding and non-scientific beliefs on the evolution and related online circulating contents. The results show that there are tactics for public exposure and dissemination of creationism through online discussions. Keywords: automated classification, machine learning, network analysis, public understanding of evolution
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