The effect of social media knowledge cascade: an analysis of scientific papers diffusion

• Published in: Scientometrics 2023-09, Vol.128 (9), p.5169-5195
• Main Authors: Hou, Jianhua, Yang, Xiucai, Zhang, Yang
• Format: Article
• Language: English
• Subjects: Biology; Bursts; Computer Science; Diffusion; Digital media; Indicators; Information Storage and Retrieval; Knowledge; Library Science; Life cycles; Social networks; Trajectory analysis
• ISSN: 0138-9130; 1588-2861
• DOI: 10.1007/s11192-023-04785-4

Our goal is to reveal the social media knowledge cascade (SMKC) of the diffusion of scientific papers. PLoS Biology , one of the prestigious and influential open-access journals under PLoS, has received much attention from researchers. Using papers published in PLoS Biology as sample, we use the citation indicators and social media indicators of scientific papers to establish an SMKC network model that measures the relationship between the citation diffusion trajectory of scientific papers and their social media diffusion trajectory through knowledge bursts. Based on the number and type of knowledge bursts, we have identified three types of SMKCs: Social media and SMKC (S–S knowledge cascade), Citation and citation knowledge cascade (C–C knowledge cascade), and Social media and citation knowledge cascade (S–C knowledge cascade). Specifically, we focus on studying the S–C knowledge cascade type in SMKC. We explored the relationship between social media diffusion trajectory knowledge bursts and citation diffusion trajectory knowledge bursts, the prompting effect of S–C knowledge cascades on paper's citation and the pivot node characteristics of the paper S–C knowledge cascade. Our research found that, in the S–C knowledge cascade papers the knowledge burst of the paper on the social media diffusion trajectory is the decisive factor for the knowledge burst in the citation diffusion trajectory. Only part of the knowledge burst in the citation diffusion trajectory will immediately cause the social media diffusion trajectory knowledge bursts. The stronger a paper's SMKC, the easier it is to become a highly cited paper. The type of pivot node is more inclined to the burst of knowledge on the trajectory of social media diffusion. We analyzed the trajectory of knowledge dissemination in the life cycle of scientific papers from a dynamic perspective. We revealed the general features of SMKCs in the process of scientific paper diffusion.