Altmetrics for the identification of scientific controversiesThe case of NeuroGenderings and neurosexism

  1. María Aguilar-Soto 1
  2. Nicolás Robinson-García 1
  3. Benjamín Vargas-Quesada 1
  1. 1 Universidad de Granada
    info

    Universidad de Granada

    Granada, España

    ROR https://ror.org/04njjy449

Revista:
El profesional de la información

ISSN: 1386-6710,  1699-2407

Año de publicación: 2023

Título del ejemplar: Political polarization

Volumen: 32

Número: 6

Tipo: Artículo

DOI: 10.3145/EPI.2023.NOV.10 DIALNET GOOGLE SCHOLAR lock_openAcceso abierto editor

Otras publicaciones en: El profesional de la información

Resumen

Este trabajo plantea una propuesta metodológica para el análisis de controversias sociales relacionadas con la biblio-grafía científica. Esta metodología consta de tres partes claramente diferenciadas. Primero, identificamos la estructura cognitiva de un conjunto de trabajos científicos. Para ello, se crea un historiograma a través del análisis de las referencias emitidas por los trabajos seminales. Esto permite ampliar el set de trabajos sobre los que trabajar para posteriormente hacer un análisis de co-palabras que permita identificar la estructura cognitiva del ámbito científico a explorar. En segundo lugar, obtenemos menciones sociales a esta bibliografía científica haciendo uso de las denominadas altmétricas. Esto nos permite extraer para documento científico las menciones que se hacen al mismo desde entornos no académicos. Finalmente, aplicamos la técnica de análisis de sentimiento a las menciones para poder identificar focos de menciones de carácter negativo. Testeamos esta metodología sobre el caso de estudio de NeuroGenderings, un movimiento del ámbito de la neurociencia que denuncia la falta de evidencia científica en los trabajos que señalan la existencia de diferencias cerebrales motivadas por el sexo biológico de los sujetos. Nuestros resultados confirman la viabilidad de este tipo de aproximaciones que permiten identificar las líneas de investigación en las que se produce mayor controversia. Aunque nuestro estudio se circunscribe al análisis de controversias en noticias, blogs, Facebook, Wikipedia y Reddit, la metodología es exportable a otros ámbitos y plataformas sociales.

Referencias bibliográficas

  • Arroyo-Machado, Wenceslao (2023). “La gran apuesta, ¿cuánto afectan los cambios de Twitter a la comunicación científica?”. Anuario ThinkEPI, v. 17. https://doi.org/10.3145/thinkepi.2023.e17a16
  • Arroyo-Machado, Wenceslao; Torres-Salinas, Daniel; Costas, Rodrigo (2022). “Wikinformetrics: Construction and description of an open Wikipedia knowledge graph data set for informetric purposes”. Quantitative science studies, v. 3, n. 4, pp. 931-952. https://doi.org/10.1162/qss_a_00226
  • Boyack, Kevin W.; Börner, Katy; Klavans, Richard (2009). “Mapping the structure and evolution of chemistry research”. Scientometrics, v. 79, n. 1, pp. 45-60. https://doi.org/10.1007/s11192-009-0403-5
  • Butler, Judith (1990). Gender Trouble: Feminism and the subversion of identity. New York: Routledge. ISBN: 0415389550
  • Butler, Judith (1993). Bodies that matter: On the discursive limits of “sex”. New York, London: Routledge. ISBN: 978 0 203760079
  • Callon, Michel; Courtial, Jean-Pierre; Turner, William A.; Bauin, Serge (1983). “From translations to problematic networks: An introduction to co-word analysis”. Social science information, v. 22, n. 2, pp. 191-235. https://doi.org/10.1177/053901883022002003
  • Choudhury, Suparna; Nagel, Saska-Kathi; Slaby, Jan (2009). “Critical neuroscience: Linking neuroscience and society through critical practice”. BioSocieties, v. 4, n. 1, pp. 61-77. https://doi.org/10.1017/S1745855209006437
  • Cole, Stephen (1983). “The hierarchy of the sciences?” American journal of sociology, v. 89, n. 1, pp. 111-139. https://doi.org/10.1086/227835
  • Fanelli, Danielle; Glänzel, Wolfgang (2013). “Bibliometric evidence for a hierarchy of the sciences”. PLoS one, v. 8, n. 6, e66938. https://doi.org/10.1371/journal.pone.0066938
  • Fine, Cordelia (2010). Delusions of gender: how our minds, society, and neurosexism create difference. Norton & Company. ISBN: 0393340244
  • Friedrich, Natalie; Bowman, Timothy D.; Stock, Wolfgang G.; Haustein, Stefanie (2015). “Adapting sentiment analysis for tweets linking to scientific papers”. In: Salah, A. A.; Y. Tonta; A.A. Akdag Salah; C. Sugimoto; U. Al (eds.). Proceedings of ISSI 2015 Istanbul: 15th International Society for Scientometrics and Informetrics Conference. Istambul (Turkey), 29 June - 3 July, Bogaziçi University Printhouse, pp. 107-108. https://www.issi-society.org/proceedings/issi_2015/0107.pdf
  • Griffin, Andrew (2008). New strategies for reputation management: gaining control of issues, crises & corporate social repsonsibility. London: Kogan Page Publishers. ISBN: 978 0 749450076
  • Hassan, Saaed-Ul; Saleem; Aneela; Soroya, Saira Hanif; Sader, Iqra; Iqbal, Sehrish; Jamil, Saqib; Bukhari, Faisal; Aljohani, Naif Radi; Nawaz, Raheel (2021). “Sentiment analysis of tweets through Altmetrics: A machine learning approach”. Journal of information science, v. 47, n. 6, pp. 712-726. https://doi.org/10.1177/0165551520930917
  • Hyde, Janet-Shibley (2005). “The gender similarities hypothesis”. American psychologist, v. 60, n. 6, pp. 581-592. https://doi.org/10.1037/0003-066X.60.6.581
  • Hyde, Janet-Shibley (2014). “Gender similarities and differences”. Annual review of psychology, v. 65, pp. 373-398. https://doi.org/10.1146/annurev-psych-010213-115057
  • Jordan-Young, Rebecca; Rumiati, Raffaella. I. (2012). “Hardwired for sexism? Approaches to sex/gender in neuroscience”. Neuroethics, v. 5, n. 3, pp. 305-315. https://doi.org/10.1007/s12152-011-9134-4
  • Kaiser, Anelis (2012). “Re-conceptualizing ‘sex’ and ‘gender’ in the human brain”. Zeitschrift fur Psychologie / Journal of psychology, v. 220, n. 2, pp. 130-136. https://doi.org/10.1027/2151-2604/a000104
  • Kaiser, Anelis; Haller, Sven; Schmitz, Sigrid; Nitsch, Cordula (2009). “On sex/gender related similarities and differences in fMRI language research”. Brain research reviews, v. 61, n. 2, pp. 49-59. https://doi.org/10.1016/j.brainresrev.2009.03.005
  • Kostoff, Ronald; Shlesinger, Michael F. (2005). “CAB: Citation-assisted-background”. Scientometrics, v. 62, n. 2, pp. 199-212. https://doi.org/10.1007/s11192-005-0014-8
  • Kuhn, Thomas S. (1962). The structure of scientific revolutions. Chicago: University of Chicago Press. ISBN: 978 0 226458113
  • Lamers, Wout S.; Boyack, Kevin; Larivière, Vincent; Sugimoto, Cassidy R.; van Eck, Nees Jan; Waltman, Ludo; Murray, Dakota (2021). “Meta-research: Investigating disagreement in the scientific literature”. eLife, v. 10, e72737. https://doi.org/10.7554/eLife.72737
  • Levay, Simon (1991). “A difference in hypothalmic structure between heterosexual and homosexual men”. Science, v. 253, pp. 1034-1037. https://doi.org/10.1126/science.1887219
  • Leydesdorff, Loet; Ràfols, Ismael (2012). “Interactive overlays: A new method for generating global journal maps from Web-of-Science data”. Journal of informetrics, v. 6, n. 3, pp. 318-332. https://doi.org/10.1016/j.joi.2011.11.003
  • Muñoz-Écija, Teresa; Vargas-Quesada, Benjamín; Chinchilla-Rodríguez, Zaida (2017). “Identification and visualization of the intellectual structure and the main research lines in nanoscience and nanotechnology at the worldwide level”. Journal of nanoparticle research, v. 19, n. 2. https://doi.org/10.1007/s11051-016-3732-3
  • Muñoz-Écija, Teresa; Vargas-Quesada, Benjamín; Chinchilla-Rodríguez, Zaida (2019). “Coping with methods for delineating emerging fields: Nanoscience and nanotechnology as a case study”. Journal of informetrics, v. 13, n. 4, 100976. https://doi.org/10.1016/j.joi.2019.100976
  • Muñoz-Écija, Teresa; Vargas-Quesada, Benjamin; Chinchilla-Rodríguez, Zaida (2022). “Unveiling cognitive structure and comparative advantages of countries in knowledge domains”. Journal of information science. https://doi.org/10.1177/01655515221084607
  • Nane, Gabriela F.; Van-Schalkwyk, François; Dudek, Jonathan; Torres-Salinas, Daniel; Costas, Rodrigo; Robinson-García, Nicolás (2021). “The role of scientific output in public debates in times of crisis: A case study of the reopening of schools during the Covid-19 pandemic”. In: Berube, D. M. (ed.). Pandemic communication and resilience. Risk, systems and decisions. Cham: Springer. ISBN: 978 3 030773441
  • Nicholson, Josh M.; Mordaunt, Milo; Lopez, Patrice; Uppala, Ashish; Rosati, Domenic; Rodrigues, Neves P.; Grabitz, Peter; Rife, Sean C. (2021). “Scite: A smart citation index that displays the context of citations and classifies their intent using deep learning”. Quantitative science studies, v. 2, n. 3, pp. 882-898. https://doi.org/10.1162/qss_a_00146
  • North, Anna (2019). “‘I am a woman and I am fast’: what Caster Semenya’s story says about gender and race in sports”. Vox. https://www.vox.com/identities/2019/5/3/18526723/caster-semenya-800-gender-race-intersex-athletes
  • Phoenix, Charles H.; Goy, Robert W.; Gerall, Arnold A.; Young, William C. (1959). “Organizing action of prenatally administered testosterone propionate on the tissues mediating mating behaviour in the female guinea pig”. Endocrinology, v. 65, n. 3, pp. 369-382. https://doi.org/10.1210/endo-65-3-369
  • Popper, Karl (2002). The logic of scientific discovery. London: Routledge. ISBN: 978 0 203994627
  • Priem, Jason; Taraborelli, Dario; Groth, Paul; Neylon, Cameron (2010), Altmetrics: A manifesto, 26 October 2010. http://altmetrics.org/manifesto
  • Proellochis, Nicolas; Feuerriegel, Stefan (2021). “Sentiment analysis: Dictionary-based sentiment analysis”. R package version 1.3-4. https://CRAN.R-project.org/package=SentimentAnalysis
  • R Core Team (2023). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org
  • Reverter-Bañón, Sonia (2017). “El neurofeminismo frente a la investigación sobre la diferencia sexual”. Daimon, v. 72, pp. 95-110. https://doi.org/10.6018/daimon/291561
  • Rippon, Gina; Jordan-Young, Rebecca; Kaiser, Anelis; Fine, Cordelia (2014). “Recommendations for sex/gender neuroimaging research: Key principles and implications for research design, analysis, and interpretation”. Frontiers in human neuroscience, v. 8. https://doi.org/10.3389/fnhum.2014.00650
  • Rippon, Gina; Jordan-Young, Rebecca; Kaiser, Anelis; Joel, Daphna; Fine, Cordelia (2017). “Journal of neuroscience research policy on addressing sex as a biological variable: Comments, clarifications, and elaborations”. Journal of Neuroscience Research, v. 95, n. 7, pp. 1357-1359. https://doi.org/10.1002/jnr.24045
  • Robinson-García, Nicolás; Ràfols, Ismael; Van-Leeuwen, Thed N. (2018). “Using altmetrics for contextualised mapping of societal impact: From hits to networks”. Science and public policy, v. 45, n. 6, pp. 815-826. https://doi.org/10.1093/scipol/scy024
  • Robinson-García, Nicolás; Torres-Salinas, Daniel; Zahedi, Zohreh; Costas, Rodrigo (2014). “New data, new possibilities: Exploring the insides of Altmetric.com”. El profesional de la información, v. 24, n. 4, pp. 359-366. https://10.3145/epi.2014.jul.03
  • Scott, John (1988). “Social network analysis”. Sociology, v. 22, n. 1, pp. 109-127. https://doi.org/10.1177/0038038588022001007
  • Thelwall, Mike (2020). “Measuring societal impacts of research with altmetrics? Common problems and mistakes”. Journal of economic surveys, v. 35, n. 5, pp. 1302-1314. https://doi.org/10.1111/joes.12381
  • Torres-Salinas, Daniel; Cabezas-Clavijo, Álvaro; Jiménez-Contreras, Evaristo (2013). “Altmetrics: nuevos indicadores para la comunicación científica en la Web 2.0”. Comunicar, v. 41. https://doi.org/10.3916/C41-2013-05
  • Torres-Salinas, Daniel; Docampo, Domingo; Arroyo-Machado, Wenceslao; Robinson-García, Nicolás (2023). The many publics of science: Using altmetrics to identify common communication channels by scientific field. https://doi.org/10.5281/zenodo.7817445
  • Traag, Vincent A.; Waltman, Ludo; Van-Eck, Nees-Jan (2019). “From Louvain to Leiden: guaranteeing well-connected communities”. Scientific reports, v. 9, 5233. https://10.1038/s41598-019-41695-z
  • Van-Eck, Nees-Jan; Waltman, Ludo (2010). “Software survey: VOSviewer, a computer program for bibliometric mapping”. Scientometrics, v. 84, n. 2, pp. 523-538. https://doi.org/10.1007/s11192-009-0146-3
  • Van-Eck, Nees-Jan; Waltman, Ludo (2014). “CitNetExplorer: A new software tool for analyzing and visualizing citation networks”. Journal of informetrics, v. 8, n. 4, pp. 802-823. https://doi.org/10.1016/j.joi.2014.07.006
  • Van-Schalkwyk, François; Dudek, Jonathan; Costas, Rodrigo (2020) “Communities of shared interests and cognitive bridges: the case of the anti-vaccination movement on Twitter”. Scientometrics, v. 125, pp. 1499-1516. https://doi.org/10.1007/s11192-020-03551-0
  • Vargas-Quesada, Benjamín; Chinchilla-Rodríguez, Zaida; Rodríguez, Noel (2017). “Identification and visualization of the intellectual structure in graphene research”. Frontiers in research metrics and analytics, v. 2. https://doi.org/10.3389/frma.2017.00007
  • Vargas-Quesada, Benjamín; De-Moya-Anegón, Félix (2007). Visualizing the structure of science. Springer. ISBN: 3540697276
  • Vargas-Quesada, Benjamín; De-Moya-Anegón, Félix; Chinchilla-Rodríguez, Zaida; González-Molina, Antonio (2010). “Showing the essential science structure of a scientific domain and its evolution”. Information visualization, v. 9, n. 4, pp. 288-300. https://doi.org/10.1057/ivs.2009.33
  • Wasserman, Stanley; Faust, Katherine (1998). Social network analysis: methods and applications. Cambridge: Cambridge University Press. ISBN: 978 0 511815478
  • Zumbach, David; Bauer, Paul C. (2022). “deeplr: Interface to the ‘DeepL’ translation API”. R package version 2.0.0. https://CRAN.R-project.org/package=deeplr
Fuente de los datos: Dialnet