TY - JOUR
T1 - Applied bibliometrics and information visualization for decision-making processes in higher education institutions
AU - Vílchez-Román, Carlos
AU - Sanguinetti, Sol
AU - Mauricio-Salas, Mariela
N1 - Publisher Copyright:
© 2020, Emerald Publishing Limited.
PY - 2021/2/23
Y1 - 2021/2/23
N2 - Purpose: The purpose of this paper is to analyse how using bibliometrics and information visualization can provide a “picture at glance” from which decision-makers can structure processes, thus organizing outputs/outcomes from inception. Design/methodology/approach: This study carried out a bibliometric-oriented review on studies on higher education students' retention; 1,962 records were downloaded from Scopus and grouped into three five-year intervals: 2002–2006 (n = 236), 2007–2011 (n = 584) and 2012–2016 (n = 1,142). Centrality measures and text-mining techniques were used to analyse data. Findings: Clusters of academic networks were identified by using co-citation analysis. Also, terms with high semantic value were ranked and grouped by using automatic term extraction and co-word analysis. Practical implications: The bibliometric approach used in this study identifies clusters of authors specialized in student retention, as well as detects the primary terms within this research field. Originality/value: This paper provides evidence that a bibliometric approach in conjunction with data visualization can be a valuable complement to in-depth literature reviews for the decision-making process.
AB - Purpose: The purpose of this paper is to analyse how using bibliometrics and information visualization can provide a “picture at glance” from which decision-makers can structure processes, thus organizing outputs/outcomes from inception. Design/methodology/approach: This study carried out a bibliometric-oriented review on studies on higher education students' retention; 1,962 records were downloaded from Scopus and grouped into three five-year intervals: 2002–2006 (n = 236), 2007–2011 (n = 584) and 2012–2016 (n = 1,142). Centrality measures and text-mining techniques were used to analyse data. Findings: Clusters of academic networks were identified by using co-citation analysis. Also, terms with high semantic value were ranked and grouped by using automatic term extraction and co-word analysis. Practical implications: The bibliometric approach used in this study identifies clusters of authors specialized in student retention, as well as detects the primary terms within this research field. Originality/value: This paper provides evidence that a bibliometric approach in conjunction with data visualization can be a valuable complement to in-depth literature reviews for the decision-making process.
KW - Bibliometrics
KW - Decision-making for higher education
KW - nformation visualization
UR - http://www.scopus.com/inward/record.url?scp=85085922128&partnerID=8YFLogxK
U2 - 10.1108/LHT-10-2019-0209
DO - 10.1108/LHT-10-2019-0209
M3 - Artículo
AN - SCOPUS:85085922128
VL - 39
SP - 263
EP - 283
JO - Library Hi Tech
JF - Library Hi Tech
SN - 0737-8831
IS - 1
ER -