Important citations identification with semi-supervised classification model

Measuring security development in information technologies: A scientometric framework using arXiv e-prints

“…The empirical literature of these quantitative approaches uses different private-and open-source datasets to measure technological change. Some studies rely on indicators such as bibliometric analyses related to scientific publications (i.e., scientometrics) (Zhang et al, 2020b,a;Mayr et al, 2014;Dotsika and Watkins, 2017;Jaewoo and Woonsun, 2014;Rezaeian et al, 2017), patents (Hajikhani and Suominen, 2022;Choi et al, 2022;Chen et al, 2017;Golembiewski et al, 2015;Noh et al, 2016;An et al, 2018;Lee and Lee, 2019;Song et al, 2017), industrymarket indicators (job openings, trade registers, networks of authors and citations), or a combination of these (An et al, 2022;Xi et al, 2022;Ali et al, 2022;Daim et al, 2012;Lee et al, 2010). To analyze this data, text-mining methods (Chen et al, 2017;Choi and Hwang, 2014;Hao et al, 2014;Antons et al, 2020) and network analysis (Chen et al, 2022;Zhang et al, 2022;Li et al, 2019b;Mikheev, 2020;Feng et al, 2022;Hong et al, 2021) are particularly prolific.…”

A novel developmental trajectory discovery approach by integrating main path analysis and intermediacy

“…Jiang et al [16] developed a solution for the cycles in a citation network. It is well known that all references may not have the same value to an interested citing publication [17,18]. On the basis of full texts, Hao [19] armed the main path analysis with the ability of important citation identification.…”