Bibliometrics and data science: an example search and analysis of scientific information from the Web of Science (WoS)

• Autor(a) principal: Moraes, Lena Lúcia de
• Data de Publicação: 2020
• Outros Autores: Kafure, Ivette
• Tipo de documento: Artigo
• Idioma: por; eng
• Título da fonte: Revista Brasileira de Direito Civil (Online)
• Texto Completo: https://periodicos.sbu.unicamp.br/ojs/index.php/rdbci/article/view/8658521
• topic: Pesquisas bibliográficas; Bibliometria; Análise de redes; Bibliographic searches; Bibliometrics; Network analysis

This practical study shows how an academic can use the techniques and tools of Bibliometry, Data Science, Network Science and Big Data to carry out a bibliographic survey of research. From the problem situation of a student who needs to do a bibliographic survey of the subjects: study of users and emotions involved in episodes of interaction with information systems, the study is developed. It seeks to answer questions such as: (i) what are the keywords that most occur and how are they related? (ii) who are the most cited authors in the study area? (iii) what are the references shared by the authors of the documents? (iv) what are the main sources of the documents? Based on the subjects, the initial bibliographic survey and consultation on Google Books Ngram Viewer, a set of terms used in the search tools was determined: “information science”, “user study”, “user experience”, “user emotion” and "User affect". These terms were used to consult scientific: Web Of Science (WoS), Scopus, PubMed and SciELO. Through the empirical analysis of 2,198 documents retrieved from WoS in the VOSviewer tool, the words network (in English) and the co-citation networks of authors, references and sources were constructed and examined. The results of the analysis of the networks facilitate the combination of elements for understanding information and knowledge of the studied area. It provides an overview of the area, as well as the exploration of specific contexts. Finally, it facilitates and directs the delimitation of research, minimizing information anxiety.