Thesis Chapters by Bartosz Paszcza
The project aims to study the Microsoft Academic Graph, a scholarly citation database, by compari... more The project aims to study the Microsoft Academic Graph, a scholarly citation database, by comparison with three competitors in the field: Web of Science, Scopus, and Google Scholar. Openness, transparency of data gathering and processing, and completeness of data including the global unique identifiers has been researched in each of the four datasets. The analysis has been conducted using a set of 75 institutional affiliations, 6 randomly selected authors from the and 639 documents published by these authors. The coverage of total research output in MAG of the six selected authors had reached 76.0%, hence being on-par with coverage of Google Scholar (76.2%) and significantly better than that of Scopus (66.5%) and Web of Science (58.8%). The overall results indicate that Microsoft Academic Graph can be an interesting source of information for bibliometric or scientometric analysis. However, no definite conclusions regarding the scope of MAG can be drawn due to the small size of the sample. Furthermore, problems with affiliation and author disambiguation in MAG have been highlighted. Finally, studies focusing on the disciplinary coverage of the datasets in greater detail are proposed.
Papers by Bartosz Paszcza
The project aims to study the Microsoft Academic Graph, a scholarly citation database, by compari... more The project aims to study the Microsoft Academic Graph, a scholarly citation database, by comparison with three competitors in the field: Web of Science, Scopus, and Google Scholar. Openness, transparency of data gathering and processing, and completeness of data including the global unique identifiers has been researched in each of the four datasets. The analysis has been conducted using a set of 75 institutional affiliations, 6 randomly selected authors from the and 639 documents published by these authors. The coverage of total research output in MAG of the six selected authors had reached 76.0%, hence being on-par with coverage of Google Scholar (76.2%) and significantly better than that of Scopus (66.5%) and Web of Science (58.8%). The overall results indicate that Microsoft Academic Graph can be an interesting source of information for bibliometric or scientometric analysis. However, no definite conclusions regarding the scope of MAG can be drawn due to the small size of the sample. Furthermore, problems with affiliation and author disambiguation in MAG have been highlighted. Finally, studies focusing on the disciplinary coverage of the datasets in greater detail are proposed.
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Thesis Chapters by Bartosz Paszcza
Papers by Bartosz Paszcza