Visibility of studies in social network analysis in South America: Its evolution and metrics from 1990 to 2013
Bibliographic record
Abstract
The aim of the study is to analyze the scientific productivity in South American countries related to Social Network Analysis in accordance with the representation of the countries, institutions, researchers and their theoretical references (citations used in these productions). The present study spans from 1990 to 2013 (31/05/2013). Bibliographical description was used to discover the status of Social Network Analysis in the scientific literature and the quantitative method to analyze publication and citation frequency data using Bibliometrics and Scientometrics. The data was collected from the Web of Science database, refining the data for the countries selected: Argentina n=166; Brazil n=775; Bolivia n=28; Chile n=179; n=78; Colombia n=78; Ecuador n=19; Paraguay n=8; Peru n=33; Uruguay n=21; Venezuela n=48 no articles were published from Guyana, Falkland Islands, Suriname, retrieving a total of 922 scientific articles. The Statistical Package for the Social Sciences, DetDraw, and CiteSpace were used for the treatment of data. Data showed that Brazil, Argentina, Chile, Venezuela and Peru maintained an especially close relationship with the United States of America. Among the South American countries, the centrality of the network consisted of Brazil, Argentina and Chile. The most outstanding universities were: Universidade de São Paulo, Universidade Federal de Minas Gerais, Universidad de Buenos Aires, Universidad Católica de Chile and Fundação Oswaldo Cruz, of which all focus on cooperation and enable studies of social network analysis to develop, with the main representatives being: Herrmann, HJ Eidgenoessische Technische Hochschule - Switzerland; Carrasco, JA Universidad de Concepción - Chile; Bastos, FI Fundação Oswaldo Cruz - Brazil; Costa, LD Universidade de São Paulo - Brazil; Moll, J Labs D'or Hospital Network - Brazil; Benevenuto, F Universidade Federal de Ouro Preto - Brazil; Gonzalez, MC Universidade Federal de São Paulo - Brazil; Miller, EJ University of Toronto - Canada; Zanette DH Centre Atómico Bariloche - Argentina. As for the citation network, the outstanding Latino scholars were Benevenuto, F, Castilian, C, Lancichinetti, A. However, the field counts on the great contributions of Freeman, LC, Granovetter M, Wasserman, S, Scott, J, Borgatti, SP and Burt, RS. In studies of social network analysis applied to bibliometrics and scientometrics authors who have published are not identified as the most constantly cited ones in the network. Social Network Analysis in South America directly deals with social network support, social capital, epidemiology, mental health, depression, violence. The studies are related to medicine and nursing, psychology, sociology, business and economics, physics and information science.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.013 | 0.021 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".