Use of text mining for understanding Peruvian students and faculties’ perceptions on bibliometrics training

  • Descripción del artículo
  • Background: Studies on bibliometrics and informetrics training have focused on teachers and curricular experts’ opinion, only a few studies have examined undergraduate students and practitioners’ perceptions. Objective: To understand how librarianship students and professionals perceive the bibliome...

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Main Author: Vílchez‐Román, Carlos
Other Authors: Alhuay Quispe, Joel
Format: Objeto de conferencia
Language: eng
Published: 2016
Subjects:
Online Access: http://repositorio.usil.edu.pe/handle/USIL/1934
http://ceur-ws.org/Vol-1743/paper20.pdf
Summary:Background: Studies on bibliometrics and informetrics training have focused on teachers and curricular experts’ opinion, only a few studies have examined undergraduate students and practitioners’ perceptions. Objective: To understand how librarianship students and professionals perceive the bibliometrics and informetrics training delivered to them. Methods: For data collection, we used a survey with opened-ended questions, to know the genuine responses of the participants. After working with the automatic term extraction technique, for codifying the answers we employed a data dictionary for quantifying the frequency of occurrences. The software programs used at this stage were ter-MEXt and LWIC. Data analysis was carried out with statistics of mean difference and the correlation coefficient. Results: The output of statistical analysis lets us understood how students and practitioners perceive the bibliometrics and informetrics training delivered to them. Conclusion: Text mining techniques facilitates the processing of responses to opened-ended questions, and contributes with a quantitative approach to analyzing people’s opinions.

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