Trends in scientific research on climate change in agriculture and forestry subject areas (2005-2014)

[EN] The term "Climate change" involves an alteration of the mean and variability of the climate properties. It implies unusual variations in the planet earth atmosphere, which causes related effect on other parts of the planet. The reduction in the land crops annual yield is derived from those alterations. The objective of this paper was to contribute to a better understanding of the scientific knowledge of climate change and its effect concerning agriculture and investigate its evolution through published papers. The items under study were obtained from the Web of Science (WOS) platform from Thomson Reuters. A bibliometric and social network analysis was performed to determine the indicators of scientific productivity, impact and collaboration between authors, institutions and countries. A subject analysis taking into account the key words assigned to papers and subject areas of journals was also carried out. A total of 1471 articles were included in the selected subject categories in WOS from 2005 until 2014. More than 50% of the papers were published in the last three years. The papers were published in 302 different journals. The United States Department of Agriculture (USDA) is the most productive institution (n = 70), followed by the Chinese Academy of Sciences (n = 58) and the Institut National de la Recherche Agronomique (INRA, France) (n = 47). The Canadian Forest Service has the most citations (n = 1456). The most frequent keywords were CO2, adaptation, model, temperature and impact. The network of collaboration between institutions and countries involve both centres from developed and developing countries and the central position of the United States, together with other leading countries, such as China, Canada, Australia, Germany, and the United Kingdom. Twenty papers received more than 100 citations, most of them concerned with emerging risks that climate change causes on forests, the impact on the forest ecosystems, the effect on plant diseases and adaptation options.Aleixandre-Benavent, R.; Aleixandre-Tudó, JL.; Castelló-Cogollos, L.; Aleixandre Benavent, JL. (2017). Trends in scientific research on climate change in agriculture and forestry subject areas (2005-2014). Journal of Cleaner Production. 147:406-418. https://doi.org/10.1016/j.jclepro.2017.01.112S40641814

Open availability of articles and raw research data in spanish pediatrics journals

[ES] [Introducción] La publicación en abierto de los artículos y de los datos brutos que han servido de soporte a la investigación permite su reutilización y mejoran el avance de la ciencia. El objetivo de este trabajo es identificar estas prácticas en las revistas pediátricas espanolas. [Método] Se han revisado las instrucciones de 13 revistas pediátricas espanolas, identificando su política sobre acceso abierto y depósito. [Resultados] Ocho revistas permiten el acceso abierto sin restricciones y 5 ofrecen indicaciones sobre la reutilización de los datos y el depósito en repositorios o páginas webs personales o institucionales. [Conclusiones] La mayor parte de las revistas son accesibles en abierto pero no promocionan el depósito de material suplementario ni de los artículos en repositorios institucionales o en páginas webs.[EN] [Introduction] The open Access to publications and the raw data allows its re-use and enhances the advancement of science. The aim of this paper is to identify these practices in Spanish pediatrics journals. [Method] We reviewed the author’s instructions in 13 Spanish pediatrics journals, identifying their open access and deposit policy. [Results] Eight journals allow open access without restriction, and 5 provide information on the ability to re-use and depositing data in repositories or websites. [Conclusions] Most ofthe journals have open access, but do not promote the deposit of additional material or articles in repositories or websites.Este trabajo se ha beneficiado de una ayuda del Plan Nacional de I + D + I del Ministerio de Economía y Competitividad (CSO2012-39632-C02-01) y de la Fundación MAPFRE (Convocatoria 2012).Aleixandre Benavent, R.; Vidal-Infer, A.; Alonso-Arroyo, A.; González De Dios, J.; Ferrer Sapena, A.; Peset Mancebo, MF. (2015). Disponibilidad en abierto de los artículos y de los datos brutos de investigación en las revistas pediátricas españolas. Anales de Pediatría. 82(1):90-94. https://doi.org/10.1016/j.anpedi.2013.11.014S909482

Global mapping of randomised trials related articles published in high-impact-factor medical journals: a cross-sectional analysis

BACKGROUND: Randomised controlled trials (RCTs) provide the most reliable information to inform clinical practice and patient care. We aimed to map global clinical research publication activity through RCT-related articles in high-impact-factor medical journals over the past five decades. METHODS: We conducted a cross-sectional analysis of articles published in the highest ranked medical journals with an impact factor > 10 (according to Journal Citation Reports published in 2017). We searched PubMed/MEDLINE (from inception to December 31, 2017) for all RCT-related articles (e.g. primary RCTs, secondary analyses and methodology papers) published in high-impact-factor medical journals. For each included article, raw metadata were abstracted from the Web of Science. A process of standardization was conducted to unify the different terms and grammatical variants and to remove typographical, transcription and/or indexing errors. Descriptive analyses were conducted (including the number of articles, citations, most prolific authors, countries, journals, funding sources and keywords). Network analyses of collaborations between countries and co-words are presented. RESULTS: We included 39,305 articles (for the period 1965-2017) published in forty journals. The Lancet (n = 3593; 9.1%), the Journal of Clinical Oncology (n = 3343; 8.5%) and The New England Journal of Medicine (n = 3275 articles; 8.3%) published the largest number of RCTs. A total of 154 countries were involved in the production of articles. The global productivity ranking was led by the United States (n = 18,393 articles), followed by the United Kingdom (n = 8028 articles), Canada (n = 4548 articles) and Germany (n = 4415 articles). Seventeen authors who had published 100 or more articles were identified; the most prolific authors were affiliated with Duke University (United States), Harvard University (United States) and McMaster University (Canada). The main funding institutions were the National Institutes of Health (United States), Hoffmann-La Roche (Switzerland), Pfizer (United States), Merck Sharp & Dohme (United States) and Novartis (Switzerland). The 100 most cited RCTs were published in nine journals, led by The New England Journal of Medicine (n = 78 articles), The Lancet (n = 9 articles) and JAMA (n = 7 articles). These landmark contributions focuse

Mathematical properties of weighted impact factors based on measures of prestige of the citing journals

The final publication is available at Springer via http://dx.doi.org/10.1007/s11192-015-1741-0An abstract construction for general weighted impact factors is introduced. We show that the classical weighted impact factors are particular cases of our model, but it can also be used for defining new impact measuring tools for other sources of information as repositories of datasets providing the mathematical support for a new family of altmet- rics. Our aim is to show the main mathematical properties of this class of impact measuring tools, that hold as consequences of their mathematical structure and does not depend on the definition of any given index nowadays in use. In order to show the power of our approach in a well-known setting, we apply our construction to analyze the stability of the ordering induced in a list of journals by the 2-year impact factor (IF2). We study the change of this ordering when the criterium to define it is given by the numerical value of a new weighted impact factor, in which IF2 is used for defining the weights. We prove that, if we assume that the weight associated to a citing journal increases with its IF2, then the ordering given in the list by the new weighted impact factor coincides with the order defined by the IF2. We give a quantitative bound for the errors committed. We also show two examples of weighted impact factors defined by weights associated to the prestige of the citing journal for the fields of MATHEMATICS and MEDICINE, GENERAL AND INTERNAL, checking if they satisfy the increasing behavior mentioned above.Ferrer Sapena, A.; Sánchez Pérez, EA.; González, LM.; Peset Mancebo, MF.; Aleixandre Benavent, R. (2015). Mathematical properties of weighted impact factors based on measures of prestige of the citing journals. Scientometrics. 105(3):2089-2108. https://doi.org/10.1007/s11192-015-1741-0S208921081053Ahlgren, P., & Waltman, L. (2014). The correlation between citation-based and expert-based assessments of publication channels: SNIP and SJR vs. Norwegian quality assessments. Journal of Informetrics, 8, 985–996.Aleixandre Benavent, R., Valderrama Zurián, J. C., & González Alcaide, G. (2007). Scientific journals impact factor: Limitations and alternative indicators. El Profesional de la Información, 16(1), 4–11.Altmann, K. G., & Gorman, G. E. (1998). The usefulness of impact factor in serial selection: A rank and mean analysis using ecology journals. Library Acquisitions-Practise and Theory, 22, 147–159.Arnold, D. N., & Fowler, K. K. (2011). Nefarious numbers. Notices of the American Mathematical Society, 58(3), 434–437.Beliakov, G., & James, S. (2012). Using linear programming for weights identification of generalized bonferroni means in R. In: Proceedings of MDAI 2012 modeling decisions for artificial intelligence. Lecture Notes in Computer Science, Vol. 7647, pp. 35–44.Beliakov, G., & James, S. (2011). Citation-based journal ranks: The use of fuzzy measures. Fuzzy Sets and Systems, 167, 101–119.Buela-Casal, G. (2003). Evaluating quality of articles and scientific journals. Proposal of weighted impact factor and a quality index. Psicothema, 15(1), 23–25.Dorta-Gonzalez, P., & Dorta-Gonzalez, M. I. (2013). Comparing journals from different fields of science and social science through a JCR subject categories normalized impact factor. Scientometrics, 95(2), 645–672.Dorta-Gonzalez, P., Dorta-Gonzalez, M. I., Santos-Penate, D. R., & Suarez-Vega, R. (2014). Journal topic citation potential and between-field comparisons: The topic normalized impact factor. Journal of Informetrics, 8(2), 406–418.Egghe, L., & Rousseau, R. (2002). A general frame-work for relative impact indicators. Canadian Journal of Information and Library Science, 27(1), 29–48.Gagolewski, M., & Mesiar, R. (2014). Monotone measures and universal integrals in a uniform framework for the scientific impact assessment problem. Information Sciences, 263, 166–174.Garfield, E. (2006). The history and meaning of the journal impact factor. JAMA, 295(1), 90–93.Habibzadeh, F., & Yadollahie, M. (2008). Journal weighted impact factor: A proposal. Journal of Informetrics, 2(2), 164–172.Klement, E., Mesiar, R., & Pap, E. (2010). A universal integral as common frame for Choquet and Sugeno integral. IEEE Transaction on Fuzzy System, 18, 178–187.Leydesdorff, L., & Opthof, T. (2010). Scopus’s source normalized impact per paper (SNIP) versus a journal impact factor based on fractional counting of citations. Journal of the American Society for Information Science and Technology, 61, 2365–2369.Li, Y. R., Radicchi, F., Castellano, C., & Ruiz-Castillo, J. (2013). Quantitative evaluation of alternative field normalization procedures. Journal of Informetrics, 7(3), 746–755.Moed, H. F. (2010). Measuring contextual citation impact of scientific journals. Journal of Informetrics, 4, 265–277.NISO. (2014). Alternative metrics initiative phase 1. White paper. http://www.niso.org/apps/group-public/download.php/13809/Altmetrics-project-phase1-white-paperOwlia, P., Vasei, M., Goliaei, B., & Nassiri, I. (2011). Normalized impact factor (NIF): An adjusted method for calculating the citation rate of biomedical journals. Journal of Biomedical Informatics, 44(2), 216–220.Pinski, G., & Narin, F. (1976). Citation influence for journal aggregates of scientific publications: Theory, with application to the literature of physics. Information Processing and Management, 12, 297–312.Pinto, A. C., & Andrade, J. B. (1999). Impact factor of scientific journals: What is the meaning of this parameter? Quimica Nova, 22, 448–453.Raghunathan, M. S., & Srinivas, V. (2001). Significance of impact factor with regard to mathematics journals. Current Science, 80(5), 605.Ruiz Castillo, J., & Waltman, L. (2015). Field-normalized citation impact indicators using algorithmically constructed classification systems of science. Journal of Informetrics, 9, 102–117.Saha, S., Saint, S., & Christakis, D. A. (2003). Impact factor: A valid measure of journal quality? Journal of the Medical Library Association, 91, 42–46.Torra, V., & Narukawa, Y. (2008). The h-index and the number of citations: Two fuzzy integrals. IEEE Transaction on Fuzzy System, 16, 795–797.Torres-Salinas, D., & Jimenez-Contreras, E. (2010). Introduction and comparative study of the new scientific journals citation indicators in journal citation reports and scopus. El Profesional de la Información, 19, 201–207.Waltman, L., & van Eck, N. J. (2008). Some comments on the journal weighted impact factor proposed by Habibzadeh and Yadollahie. Journal of Informetrics, 2(4), 369–372.Waltman, L., van Eck, N. J., van Leeuwen, T. N., & Visser, M. S. (2013). Some modifications to the SNIP journal impact indicator. Journal of Informetrics, 7, 272–285.Zitt, M. (2011). Behind citing-side normalization of citations: some properties of the journal impact factor. Scientometrics, 89, 329–344.Zitt, M., & Small, H. (2008). Modifying the journal impact factor by fractional citation weighting: The audience factor. Journal of the American Society for Information Science and Technology, 59, 1856–1860.Zyczkowski, K. (2010). Citation graph, weighted impact factors and performance indices. Scientometrics, 85(1), 301–315

Vector valued information measures and integration with respect to fuzzy vector capacities

[EN] Integration with respect to vector-valued fuzzy measures is used to define and study information measuring tools. Motivated by some current developments in Information Science, we apply the integration of scalar functions with respect to vector-valued fuzzy measures, also called vector capacities. Bartle-Dunford-Schwartz integration (for the additive case) and Choquet type integration (for the non-additive case) are considered, showing that these formalisms can be used to define and develop vector-valued impact measures. Examples related to existing bibliometric tools as well as to new measuring indices are given.The authors would like to thank both Prof. Dr. Olvido Delgado and the referee for their valuable comments and suggestions which helped to prepare the manuscript. The first author gratefully acknowledges the support of the Ministerio de Economia, Industria y Competitividad (Spain) under project MTM2016-77054-C2-1-P.Sánchez Pérez, EA.; Szwedek, R. (2019). Vector valued information measures and integration with respect to fuzzy vector capacities. Fuzzy Sets and Systems. 355:1-25. https://doi.org/10.1016/j.fss.2018.05.004S12535

Productivity trends and collaboration patterns: A diachronic study in the eating disorders field

[EN] Objective The present study seeks to extend previous bibliometric studies on eating disorders (EDs) by including a time-dependent analysis of the growth and evolution of multi-author collaborations and their correlation with ED publication trends from 1980 to 2014 (35 years). Methods Using standardized practices, we searched Web of Science (WoS) Core Collection (WoSCC) (indexes: Science Citation Index-Expanded [SCIE], & Social Science Citation Index [SSCI]) and Scopus (areas: Health Sciences, Life Sciences, & Social Sciences and Humanities) to identify a large sample of articles related to EDs. We then submitted our sample of articles to bibliometric and graph theory analyses to identify co-authorship and social network patterns. Results We present a large number of detailed findings, including a clear pattern of scientific growth measured as number of publications per five-year period or quinquennium (Q), a tremendous increase in the number of authors attracted by the ED subject, and a very high and steady growth in collaborative work. Conclusions We inferred that the noted publication growth was likely driven by the noted increase in the number of new authors per Q. Social network analyses suggested that collaborations within ED follow patters of interaction that are similar to well established and recognized disciplines, as indicated by the presence of a ¿giant cluster¿, high cluster density, and the replication of the ¿small world¿ phenomenon¿the principle that we are all linked by short chains of acquaintances.This work was performed with a subsidy from Universidad Catolica de Valencia "San Vicente Martir" to resarch group INDOTEI: Evaluacion de la Ciencia, for the years 2016-2017. This work is benefited from Spanish Government assistance through Government Delegation for the National Drugs Plan of the Ministry of Health, Social Services and Equality (project 2016/028); and National R+D+I (projects: CS02012-39632-C02-01 and CS02015-65594-C2-2-R) and 2015-Networks of Excellence Call (project CS02015-71867-REDT) of the Ministry of Economy and Competitiveness.Valderrama Zurian, JC.; Aguilar-Moya, R.; Cepeda-Benito, A.; Melero-Fuentes, D.; Navarro-Moreno, MÁ.; Gandía-Balaguer, A.; Aleixandre-Benavent, R. (2017). Productivity trends and collaboration patterns: A diachronic study in the eating disorders field. PLoS ONE. 12(8):1-17. https://doi.org/10.1371/journal.pone.0182760S117128McClelland, J., Bozhilova, N., Campbell, I., & Schmidt, U. (2013). A Systematic Review of the Effects of Neuromodulation on Eating and Body Weight: Evidence from Human and Animal Studies. 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The Validity and Clinical Utility of Binge Eating Disorder. FOCUS, 12(4), 489-505. doi:10.1176/appi.focus.120412Theander, S. S. (2002). Literature on eating disorders during 40 Years: increasing number of papers, emergence of bulimia nervosa. European Eating Disorders Review, 10(6), 386-398. doi:10.1002/erv.495Clinton, D. (2010). Towards an ecology of eating disorders: Creating sustainability through the integration of scientific research and clinical practice. European Eating Disorders Review, 18(1), 1-9. doi:10.1002/erv.986Soh, N. L.-W., & Walter, G. (2013). Publications on cross-cultural aspects of eating disorders. Journal of Eating Disorders, 1(1). doi:10.1186/2050-2974-1-4Wuchty, S., Jones, B. F., & Uzzi, B. (2007). The Increasing Dominance of Teams in Production of Knowledge. Science, 316(5827), 1036-1039. doi:10.1126/science.1136099Kumar, S. (2015). Co-authorship networks: a review of the literature. Aslib Journal of Information Management, 67(1), 55-73. doi:10.1108/ajim-09-2014-0116Barabási, A. ., Jeong, H., Néda, Z., Ravasz, E., Schubert, A., & Vicsek, T. (2002). Evolution of the social network of scientific collaborations. Physica A: Statistical Mechanics and its Applications, 311(3-4), 590-614. doi:10.1016/s0378-4371(02)00736-7Newman, M. E. J. (2004). Coauthorship networks and patterns of scientific collaboration. Proceedings of the National Academy of Sciences, 101(Supplement 1), 5200-5205. doi:10.1073/pnas.0307545100Aleixandre-Benavent, R., & Alonso-Arroyo, A. (2011). Indicadores bibliométricos, patología del aparato respiratorio y reducción del consumo de tabaco. Revista de Patología Respiratoria, 14(1), 1-3. doi:10.1016/s1576-9895(11)70095-9Pino-Díaz, J., Jiménez-Contreras, E., Ruíz-Baños, R., & Bailón-Moreno, R. (2011). Evaluación de redes tecnocientíficas: la red española sobre Áreas Protegidas, según la Web of Science. Revista española de Documentación Científica, 34(3), 301-333. doi:10.3989/redc.2011.3.804Valderrama-Zurián, J.-C., Aguilar-Moya, R., Melero-Fuentes, D., & Aleixandre-Benavent, R. (2015). A systematic analysis of duplicate records in Scopus. Journal of Informetrics, 9(3), 570-576. doi:10.1016/j.joi.2015.05.002Guardiola-Wanden-Berghe, R., Sanz-Valero, J., & Wanden-Berghe, C. (2012). Medical subject headings versus American Psychological Association Index Terms: indexing eating disorders. Scientometrics, 94(1), 305-311. doi:10.1007/s11192-012-0866-7Soh, N., Walter, G., Touyz, S., Russell, J., Malhi, G. S., & Hunt, G. E. (2012). Food for thought: Comparison of citations received from articles appearing in specialized eating disorder journals versus general psychiatry journals. International Journal of Eating Disorders, 45(8), 990-994. doi:10.1002/eat.22036Theander, S. S. (2004). Trends in the literature on eating disorders over 36 years(1965-2000): terminology, interpretation and treatment. European Eating Disorders Review, 12(1), 4-17. doi:10.1002/erv.559Kawamura, M., Thomas, C. D. L., Tsurumoto, A., Sasahara, H., & Kawaguchi, Y. (2000). Lotka’s law and productivity index of authors in a scientific journal. Journal of Oral Science, 42(2), 75-78. doi:10.2334/josnusd.42.75Lawani SM. Quality, collaboration and citations in cancer research: A bibliometric study. PhD thesis. Florida State University, Tallahassee. 1980.Watts, D. J., & Strogatz, S. H. (1998). Collective dynamics of ‘small-world’ networks. Nature, 393(6684), 440-442. doi:10.1038/30918Jacomy, M., Venturini, T., Heymann, S., & Bastian, M. (2014). ForceAtlas2, a Continuous Graph Layout Algorithm for Handy Network Visualization Designed for the Gephi Software. PLoS ONE, 9(6), e98679. doi:10.1371/journal.pone.0098679Pike, K. M., & Dunne, P. E. (2015). The rise of eating disorders in Asia: a review. Journal of Eating Disorders, 3(1). doi:10.1186/s40337-015-0070-2El Ghoch, M., Soave, F., Calugi, S., & Dalle Grave, R. (2013). Eating Disorders, Physical Fitness and Sport Performance: A Systematic Review. Nutrients, 5(12), 5140-5160. doi:10.3390/nu5125140Jones, A. W. (2007). The distribution of forensic journals, reflections on authorship practices, peer-review and role of the impact factor. Forensic Science International, 165(2-3), 115-128. doi:10.1016/j.forsciint.2006.05.013Baker, T., Hatsukami, D., Lerman, C., O’Malley, S., Shields, A., & Fiore, M. (2003). Transdisciplinary science applied to the evaluation of treatments for tobacco use. Nicotine & Tobacco Research, 5(6), 89-99. doi:10.1080/14622200310001625564González-Alcaide, G., Melero-Fuentes, D., Aleixandre-Benavent, R., & Valderrama-Zurián, J.-C. (2013). Productivity and Collaboration in Scientific Publications on Criminology. Journal of Criminal Justice Education, 24(1), 15-37. doi:10.1080/10511253.2012.664153López-Muñoz, F., Alamo, C., Rubio, G., García-García, P., Martín-Agueda, B., & Cuenca, E. (2003). Bibliometric analysis of biomedical publications on SSRI during 1980-2000. Depression and Anxiety, 18(2), 95-103. doi:10.1002/da.10121González-Alcaide, G., Aleixandre-Benavent, R., Navarro-Molina, C., & Valderrama-Zurián, J. C. (2008). Coauthorship networks and institutional collaboration patterns in reproductive biology. Fertility and Sterility, 90(4), 941-956. doi:10.1016/j.fertnstert.2007.07.1378González-Alcaide, G., Park, J., Huamaní, C., Belinchón, I., & Ramos, J. M. (2015). Evolution of Cooperation Patterns in Psoriasis Research: Co-Authorship Network Analysis of Papers in Medline (1942–2013). PLOS ONE, 10(12), e0144837. doi:10.1371/journal.pone.0144837Bordons, M., & Ángeles Zulueta, M. (2002). La interdisciplinariedad en los grupos españoles de investigación en el área cardiovascular. Revista Española de Cardiología, 55(9), 900-912. doi:10.1016/s0300-8932(02)76728-6Chan, H. F., Önder, A. S., & Torgler, B. (2015). The first cut is the deepest: repeated interactions of coauthorship and academic productivity in Nobel laureate teams. Scientometrics, 106(2), 509-524. doi:10.1007/s11192-015-1796-yBordons, M., Aparicio, J., González-Albo, B., & Díaz-Faes, A. A. (2015). The relationship between the research performance of scientists and their position in co-authorship networks in three fields. Journal of Informetrics, 9(1), 135-144. doi:10.1016/j.joi.2014.12.001Newman, M. E. J. (2001). The structure of scientific collaboration networks. Proceedings of the National Academy of Sciences, 98(2), 404-409. doi:10.1073/pnas.98.2.404Fatt, C. K., Ujum, E. A., & Ratnavelu, K. (2010). The structure of collaboration in the Journal of Finance. Scientometrics, 85(3), 849-860. doi:10.1007/s11192-010-0254-0Kretschmer, H. (2004). Author productivity and geodesic distance in bibliographic co-authorship networks, and visibility on the Web. Scientometrics, 60(3), 409-420. doi:10.1023/b:scie.0000034383.86665.22Yan, E., Ding, Y., & Zhu, Q. (2009). Mapping library and information science in China: a coauthorship network analysis. Scientometrics, 83(1), 115-131. doi:10.1007/s11192-009-0027-9Yin, L., Kretschmer, H., Hanneman, R. A., & Liu, Z. (2006). Connection and stratification in research collaboration: An analysis of the COLLNET network. Information Processing & Management, 42(6), 1599-1613. doi:10.1016/j.ipm.2006.03.021Lambiotte, R., & Panzarasa, P. (2009). Communities, knowledge creation, and information diffusion. Journal of Informetrics, 3(3), 180-190. doi:10.1016/j.joi.2009.03.007Leydesdorff, L. (2012). World shares of publications of the USA, EU-27, and China compared and predicted using the new Web of Science interface versus Scopus. 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Co-authorship Network Analysis: A Powerful Tool for Strategic Planning of Research, Development and Capacity Building Programs on Neglected Diseases

The selection and prioritization of research proposals is always a challenge, particularly when addressing neglected tropical diseases, as the scientific communities are relatively small, funding is usually limited and the disparity between the science and technology capacity of different countries and regions is enormous. When the Ministry of Health and the Ministry of Science and Technology of Brazil decided to launch an R&D program on neglected diseases for which at least 30% of the Program's resources were supposed to be invested in institutions and authors from the poorest regions of Brazil, it became clear to us that new strategies and approaches would be required. Social network analysis of co-authorship networks is one of the new approaches we are exploring to develop new tools to help policy-/decision-makers and academia jointly plan, implement, monitor and evaluate investments in this area. Publications retrieved from international databases provide the starting material. After standardization of names and addresses of authors and institutions with text mining tools, networks are assembled and visualized using social network analysis software. This study enabled the development of innovative criteria and parameters, allowing better strategic planning, smooth implementation and strong support and endorsement of the Program by key stakeholders

Chinese journals: a guide for epidemiologists.

Chinese journals in epidemiology, preventive medicine and public health contain much that is of potential international interest. However, few non-Chinese speakers are acquainted with this literature. This article therefore provides an overview of the contemporary scene in Chinese biomedical journal publication, Chinese bibliographic databases and Chinese journals in epidemiology, preventive medicine and public health. The challenge of switching to English as the medium of publication, the development of publishing bibliometric data from Chinese databases, the prospect of an Open Access publication model in China, the issue of language bias in literature reviews and the quality of Chinese journals are discussed. Epidemiologists are encouraged to search the Chinese bibliographic databases for Chinese journal articles.Published versio