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

Carlos Vílchez-Román, Joel Alhuay-Quispe

Research output: Contribution to conferenceConference Paper

3 Scopus citations

Abstract

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 terMEXt 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 openedended questions, and contributes with a quantitative approach to analyzing people's opinions.
Original languageAmerican English
Pages165-169
Number of pages5
StatePublished - 1 Jan 2016
EventCEUR Workshop Proceedings -
Duration: 1 Jan 2016 → …

Conference

ConferenceCEUR Workshop Proceedings
Period1/01/16 → …

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