Big data y ciencias sociales. Una mirada comparativa a las publicaciones de antropología, sociología y trabajo social

Bibliographic References

• Abramson, Corey M. (y otros) 2018 “The promises of computational ethnography: improving transparency, replicability, and validity for realist approaches to ethnographic analysis”, Ethnography, nº 19 (2): 254-284. https://doi.org/10.1177/1466138117725340
• Ahajjam, Sara (y otros) 2018 “A new scalable leader-community detection approach for community detection in social networks”, Social Networks, nº 54: 41-49. https://doi.org/10.1016/j.socnet.2017.11.004
• Alvard, Michael (y David Carlson) 2020 “Identifying patch types using movement data from artisanal fishers from the commonwealth of dominica”, Current Anthropology, nº 61 (3): 380-387. https://www.journals.uchicago.edu/doi/abs/10.1086/708720?journalCode=ca
• Andreotta, Matthew (y otros) 2019 “Analyzing social media data: A mixed-methods framework combining computational and qualitative text analysis”, Behavior Research Methods, nº 51 (4): 1766-1781. https://doi.org/10.3758/s13428-019-01202-8
• Bartosik-Purgat, Malgorzata (y Milena Ratajczak-Mrożek) 2018 “Big data analysis as a source of companies’ competitive advantage: A review”, Entrepreneurial Business and Economics Review, nº 6 (4): 197. https://doi.org/10.15678/EBER.2018.060411
• Becerra, Gastón (y Cristian Rotovicius) 2022 “Social Sciences and Humanities on Big Data: a Bibliometric Analysis”, Journal of Information Systems and Technology Management, nº 19: e202219011. https://doi.org/10.4301/s1807-177520221901
• Bello-Orgaz, Gema (y otros) 2016 “Social big data: Recent achievements and new challenges”, Information Fusion, nº 28: 45-59. https://doi.org/10.1016/j.inffus.2015.08.005
• Berger, Jonah (y Grant Packard) 2021 “Using Natural Language Processing to Understand People and Culture”, American Psychologist, Advance online publication, nº 1: 13. http://dx.doi.org/10.1037/amp0000882
• Beyer, Mark (y Douglas Laney) 2012 “The Importance of “Big Data”: A Definition”, Gartner Research. https://www.gartner.com/en/documents/2057415/the-importance-of-big-data-a-definition
• Bird, Steven (y otros) 2009 Natural language processing with Python. O’Reilly.
• Bonacchi, Chiara (y otros) 2018 “The heritage of Brexit: Roles of the past in the construction of political identities through social media”, Journal of Social Archaeology, nº 18 (2): 174-192. https://doi.org/10.1177/1469605318759713
• Brownlie, Julie (y Frances Shaw) 2019 “Empathy rituals: Small conversations about emotional distress on Twitter”, Sociology, nº 53 (1): 104-122. https://doi.org/10.1177/0038038518767075
• Bulger, Monica (y otros) 2014 Engaging Complexity: Challenges and Opportunities of Big Data. London, NEMDOE.
• Caplan, Mary A. (y Gregory Purser) 2019 “Qualitative inquiry using social media: A field-tested example”, Qualitative Social Work, nº 18 (3): 417-435. https://doi.org/10.1177/1473325017725802
• Chaudhary, Mukesh 2020 “TF-IDF Vectorizer scikit-learn”. https://medium.com/@cmukesh8688/tf-idf-vectorizer-scikit-learn-dbc0244a911a
• Chung, Jae Young (y Sunbok Lee) 2019 “Dropout early warning systems for high school students using machine learning”, Children and Youth Services Review, nº 96: 346-353. https://doi.org/10.1016/j.childyouth.2018.11.030
• Del Vecchio, Pasquale (y otros) 2018 “Creating value from Social Big Data: Implications for Smart Tourism Destinations”, Information Processing & Management, nº 54 (5): 847-860. https://doi.org/10.1016/j.ipm.2017.10.006
• Edelmann, Achim (y otros) 2020 “Computational Social Science and Sociology”, Annual Review of Sociology, nº 46. https://doi.org/10.1146/annurev-soc-121919-054621
• Elgin, Dallas J. 2018 “Utilizing predictive modeling to enhance policy and practice through improved identification of at-risk clients: Predicting permanency for foster children”, Children and Youth Services Review, nº 91: 156-167. https://doi.org/10.1016/j.childyouth.2018.05.030
• Erikson, Susan L. 2018 “Cell phones≠ self and other problems with big data detection and containment during epidemics”, Medical Anthropology Quarterly, nº 32 (3): 315-339. https://doi.org/10.1111/maq.12440
• Escobar, Modesto (y otros) 2022 “Análisis de la dinámica, la estructura y el contenido de los mensajes de Twitter: violencia sexual en #Cuéntalo”, Empiria. Revista de metodología de Ciencias Sociales, nº 53: 89-119. https://doi.org/10.5944/empiria.53.2022.32614
• Evans, James (y Jacob G. Foster) 2019 “Computation and the Sociological Imagination”, Contexts, nº 18 (4): 10-15. https://doi:10.1177/1536504219883850
• Gillingham, Philip (y Timothy Graham) 2017 “Big data in social welfare: The development of a critical perspective on social work’s latest ‘electronic turn’”, Australian Social Work, nº 70 (2): 135-147. https://doi.org/10.1080/0312407X.2015.1134606
• Gillingham, Philip 2019 “Can predictive algorithms assist decision-making in social work with children and families?” Child abuse review, nº 28 (2): 114-126. https://doi.org/10.1002/car.2547
• Goldberg, Amir 2015 “In defense of forensic social science”, Big Data & Society, nº 2 (2): 2053951715601145. https://doi.org/10.1177/2053951715601145
• Golder, Scott A. (y Michael W. Macy) 2014 “Digital footprints: Opportunities and challenges for online social research”, Annual Review of Sociology, nº 40: 129-152. https://www.annualreviews.org/doi/abs/10.1146/annurev-soc-071913-043145
• Gualda, Estrella (y Carolina Rebollo) 2020, “Big data y Twitter para el estudio de procesos migratorios: Métodos, técnicas de investigación y software”, Empiria. Revista de metodología de Ciencias Sociales, nº 46: 147-177. https://doi.org/10.5944/empiria.46.2020.26970
• Gualda, Estrella 2022 “Social big data, sociología y ciencias sociales computacionales”, Empiria. Revista de metodología de Ciencias Sociales, nº 53: 147-177. https://doi.org/10.5944/empiria.53.2022.32631
• Gui, Yong (y otros) 2020 “Three faces of the online leftists: An exploratory study based on case observations and big-data analysis”, Chinese Journal of Sociology,nº 6 (1): 67-101. https://doi.org/10.1177/2057150X19896537
• Halavais, Alexander 2015 “Bigger sociological imaginations: Framing big social data theory and methods”, Information, Communication & Society, nº 18 (5): 583-594. https://doi.org/10.1080/1369118X.2015.1008543
• Hashema, Ibrahim Abaker Targio (y otros) 2015 “The rise of big data on cloud computing: review and open research issues”, Information Systems, nº 47: 98-115. https://doi.org/10.1016/j.is.2014.07.006
• James, Gareth (y otros) 2013 An Introduction to Statistical Learning (vol. 103). Springer New York. https://doi.org/10.1007/978-1-4614-7138-7
• Jin, Xiaolong (y otros) 2015 “Significance and Challenges of Big Data Research”, Big Data Research, nº 2: 59-64. https://doi.org/10.1016/j.bdr.2015.01.006
• Laney, Doug 2001 “3D Data Management: Controlling Data Volume, Velocity, and Variety”, Gartner, 6 febrero, nº 949. https://idoc.pub/documents/3d-data-management-controlling-data-volume-velocity-and-variety-546g5mg3ywn8
• Lynn, Freda B. (y otros) 2019 “A rare case of gender parity in academia”, Social Forces, nº 98 (2): 518-547. https://doi.org/10.1093/sf/soy126
• Manderson, Lenore (y otros) 2015 “On secrecy, disclosure, the public, and the private in anthropology: an introduction to supplement 12”, Current Anthropology, nº 56 (S12): S183-S190. https://www.journals.uchicago.edu/doi/full/10.1086/683302
• McFarland, Daniel A. (H. Richard McFarland) 2015 “Big data and the danger of being precisely inaccurate”, Big Data & Society, nº 2 (2): 2053951715602495. https://doi.org/10.1177/2053951715602495
• Monroe, Kristin V. 2017 “Tweets of surveillance: Traffic, Twitter, and securitization in Beirut, Lebanon”, Anthropological theory, nº 17 (3): 322-337. https://doi.org/10.1177/1463499617729296
• Müller, Andreas C. (y Sarah Guido) 2016 Introduction to machine learning with Python: A guide for data scientists. Sebastopol, CA, O’Reilly Media, Inc., 1ª edición.
• Mützel, Sophie 2015 “Facing big data: Making sociology relevant”, Big Data & Society, nº 2 (2): 2053951715599179. https://doi.org/10.1177/2053951715599179
• Nardulli, Peter F. (y otros) 2015 “A progressive supervised-learning approach to generating rich civil strife data”, Sociological methodology, nº 45 (1): 148-183. https://doi.org/10.1177/0081175015581378
• Nikunen, Kaarina 2021 “Ghosts of white methods? The challenges of Big Data research in exploring racism in digital context”, Big Data & Society, nº 8 (2): 205395172110489. https://doi.org/10.1177/20539517211048964
• Olshannikova, Ekaterina (y otros) 2017 “Conceptualizing Big Social Data”, Journal of Big Data, nº 4 (3). https://doi.org/10.1186/s40537-017-0063-x
• Patgiri, Ripon (y Arif Ahmed) 2016 “Big Data: The V’s of the Game Changer Paradigm”. 18th IEEE High Performance Computing and Communications, Sydney: 17-24. https://doi.org/10.1109/HPCC-SmartCity-DSS.2016.0014
• Philips, Susan 2013 “Method in anthropological discourse analysis: The comparison of units of interaction”, Journal of linguistic anthropology, nº 23 (1): 82-95. http://www.jstor.org/stable/43103109
• Pink, Sara (y Debora Lanzeni) 2018 “Future anthropology ethics and datafication: Temporality and responsibility in research”, Social Media+ Society, nº 4 (2):2056305118768298. https://doi.org/10.1177/2056305118768298
• Reyes, Ángela 2014 “Linguistic anthropology in 2013: Super‐new‐big”, American Anthropologist, nº 116 (2): 366-378. https://doi.org/10.1111/aman.12109
• Robles, Jose Manuel (y otros) 2020 “The polarization of ‘La Manada’: the public debate in Spain and the risks of digital political communication”, Tempo Social, nº 31: 193-216. https://doi.org/10.11606/0103-2070.TS.2019.159680
• Rona-Tas, Akos (y otros) 2019 “Enlisting Supervised Machine Learning in Mapping Scientific Uncertainty Expressed in Food Risk Analysis”, Sociological Methods & Research, nº 48 (3): 608-641. https://doi:10.1177/0049124117729701
• Rose, Jeremy (y Christian Lennerholt) 2017 “Low cost text mining as a strategy for qualitative researchers”, Electronic Journal on Business Research Methods, nº 15 (1): 2-16. https://academic-publishing.org/index.php/ejbrm/article/view/1352
• Ruckenstein, Minna (y Natasha Dow Schüll) 2017 “The datafication of health”, Annual Review of Anthropology, nº 46: 261-278. https://doi.org/10.1146/annurev-anthro-102116-041244
• Ruppert, Evelyn 2013 “Rethinking empirical social sciences”, Dialogues in Human Geography, nº 3 (3): 268-273. https://doi.org/10.1177/2043820613514321
• Schneider, Diana (y Udo Seelmeyer) 2019 “Challenges in using big data to develop decision support systems for social work in Germany”, Journal of Technology in Human Services, nº 37 (2-3): 113-128. https://doi.org/10.1080/15228835.2019.1614513
• Tinati, Ramine (y otros) 2014 “Big data: methodological challenges and approaches for sociological analysis”, Sociology, nº 48 (4): 663-681. https://doi.org/10.1177/0038038513511561
• Wainer, Howard (y otros) 1974 “Trebig: A 360/75 Fortran program for three-mode factor analysts designed for big data sets”, Behavior Research Methods & Instrumentation, nº 6 (1): 53-54. https://doi.org/10.3758/BF03200290