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Teaching GuideTerm Faculty of Humanities |
| Grao en Xestión Dixital de Información e Documentación |
 Subjects |
| Metric Studies of Information |
| Contents |
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| Identifying Data | 2022/23 | |||||||||||||
| Subject | Metric Studies of Information | Code | 710G04027 | |||||||||||
| Study programme |
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| Descriptors | Cycle | Period | Year | Type | Credits | |||||||||
| Graduate | 1st four-month period |
Third | Obligatory | 6 | ||||||||||
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| Topic | Sub-topic |
| Introduction to information metric studies. | Preliminary concepts, historical evolution, objectives and relevance. Informetrics, Bibliometrics, Scientometrics and Altmetrics. |
| Sources of bibliometric information. | Web of Science and the Journal Citation Report. Scopus. Google Scholar. Other sources of bibliometric information. Case studies. |
| Informatics indicators and software for statistical analysis. |
Indicators calculated from the number of publications and/or citations, journal indicators, patent indicators, webometric indicators, economic indicators, indicators of the reputation of institutions and researchers, indicators of scientific collaboration. Software for statistical analysis in Bibliometrics, Scientometrics, Informetrics and Altmetrics. Case studies. |
| Multivariate statistical methods for analysis in Bibliometrics, Scientometrics, Informetrics and Altmetrics. | Descriptive statistical analysis in Bibliometrics, Scientometrics, Informetrics and Altmetrics. Study of the relationship between bibliometric variables. Correspondence analysis. Cluster analysis in Informetrics. Introduction to network analysis and scientific maps. Case studies with R. |
| Rankings of higher education institutions. |
Introduction and objectives. National rankings. International rankings. Case studies with R. |
| Bibliometric laws and estimation of regression models |
Preliminary concepts. Regression model fitting. Bibliometric laws: Price, Lotka, Zipf. Case studies with R. |
| Statistical quality control in libraries, science and information systems. |
Library databases. Six Sigma methodology. Basic tools of statistical quality control. Practical cases with R. |
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