Stability and change in public health studies in Colombia and Mexico: an exploratory approach based on co-word analysis

Abstract

Review Suggested citationVílchez-Román C, Quiliano-Terreros R. Stability and change in public health studies in Colombia and Mexico: an exploratory approach based on co-word analysis. Rev Panam Salud Publica. 2018;42:e35. https://doi.org/10.26633/RPSP.2018.35 The World Health Organization defines the concept of public health as, "all organized measures (whether public or private) to prevent disease, promote health, and prolong life among the population as a whole…to provide conditions in which people can be healthy, and focus on entire populations, not on individual patients or diseases"(1). Countries of Latin America and the Caribbean have undertaken significant advances in reducing mortality and morbidity rates by applying effective strategies for improving public health (2 -4). However, significant challenges remain due to the increasing prevalence 2005 -2007, 2008 -2010, and 2011 -2013 2005 -2010, as evidenced by the correlation coefficients for two of the 3-year periods, 2005 and 2008-2010: 0.545 for RSP and 0.593 for SPM. However, in 2008-2013, more keywords remained constant from one period to the next, given the size of the correlation coefficients for the last 3-year periods: 2008 -2010 and 2011 -2013: 0.727 . Co-word analysis was used to examine keywords extracted. Textual information was analyzed using centrality measures (inbetweenness and closeness). The hypothesis of stability/change of thematic coverage was tested using the Spearman's rho correlation coefficient. VOSviewer was used to visualize the co-word maps. Results. A moderate level of change in thematic coverage was observed in

Applied bibliometrics and information visualization for decision-making processes in higher education institutions

“…This kind of automatically generated content analysis requires structured text to produce an understandable output; therefore, most of the studies that used text mining tools for analysing scientific publications utilized multidisciplinary databases such as Google Scholar, Web of Science (WoS) and Microsoft Academic. Regarding specific text mining tools, some studies have used co-word analysis (Cho, 2014; Surjandari et al , 2015;Vílchez-Román and Quiliano-Terreros, 2017), automatic term extraction algorithms (Rubtsova, 2014; Verbene et al , 2016; Vílchez-Román and Alhuay-Quispe, 2016), while others have worked with clustering and visualization algorithms (Pinto, 2015; Poreau, 2015; Zhu et al , 2013).…”