Culture & History Digital Journal, Vol 7, No 2 (2018)

Digital sources: a case study of the analysis of the Recovery of Historical Memory in Spain on the social network Twitter


https://doi.org/10.3989/chdj.2018.015

Mariluz Congosto
Universidad Carlos III, Spain
orcid http://orcid.org/0000-0002-8826-729X

Abstract


The incorporation of digital sources from online social media into historical research brings great opportunities, although it is not without technological challenges. The huge amount of information that can be obtained from these platforms obliges us to resort to the use of quantitative methodologies in which algorithms have special relevance, especially regarding network analysis and data mining. The Recovery of Historical Memory in Spain on the social network Twitter will be analysed in this article. An open-code tool called T-Hoarder was used; it is based on objectivity, transparency and knowledge-sharing. It has been in use since 2012.

Keywords


Methodology; Data mining; Networks analysis; History; Twitter

Full Text:


HTML PDF XML

References


Aragón, P. et al. (2017) "Online network organization of Barcelona en Comú, an emergent movement-party". Computational Social Networks, 4(1), p.8. Available at: http://computationalsocialnetworks.springeropen.com/articles/10.1186/s40649-017-0044-4. https://doi.org/10.1186/s40649-017-0044-4

Barberá, P. & Rivero, G. (2012) "Desigualdad en la discusión política en Twitter". Congreso ALICE.

Bessi, A. & Ferrara, E. (2016) "Social Bots Distort the 2016 US Presidential Election Online Discussion". First Monday, 21(11), pp.1–15. https://doi.org/10.5210/fm.v21i11.7090

Blondel, V.D. et al. (2008) "Fast unfolding of communities in large networks". Journal of Statistical Mechanics: Theory and Experiment, p.6. Available at: http://arxiv.org/abs/0803.0476 [Accessed July 10, 2014]. https://doi.org/10.1088/1742-5468/2008/10/P10008

Castells, M. (2009) Comunicación y Poder Alianza Editorial, ed., Alianza Editorial.

Congosto, M. (2015) "Elecciones Europeas 2014 : Viralidad de los mensajes en Twitter". Revista redes, 26, pp.23–52. https://doi.org/10.5565/rev/redes.529

Congosto, M., Basanta-Val, P. & Sanchez-Fernandez, L. (2017) "T-Hoarder: A framework to process Twitter data streams". Journal of Network and Computer Applications, 83(August 2016), pp.28–39. Available at: http://linkinghub.elsevier.com/retrieve/pii/S1084804517300486. https://doi.org/10.1016/j.jnca.2017.01.029

Congosto, M.L. (2016) Caracterización de usuarios y propagación de mensajes en twitter en el entorno de temas sociales. Universidad Carlos III. Available at: http://e-archivo.uc3m.es/bitstream/handle/10016/22826/tesis_maria-luz_congosto_martinez_2016.pdf?sequence=1.

Conover, M.D. et al. (2010) Political "Polarization on Twitter". Networks, pp.89–96.

Ferrara, E. (2017) "Disinformation and social bot operations in the run up to the 2017 french presidential election". First Monday, 22(8). https://doi.org/10.5210/fm.v22i8.8005

Ferrara, E. et al. (2016) "The Rise of Social Bots". Communications of the ACM, 59(7), pp. 96-104. Available at: http://arxiv.org/abs/1407.5225%0A. https://doi.org/10.1145/2818717

Fletcher, R. et al. (2018) "Measuring the reach of fake news and online disinformation in Europe". Factsheets Reuters Institute (February), pp.1–10. Available at: https://reutersinstitute.politics.ox.ac.uk/sites/default/files/2018-02/Measuring%20the%20reach%20of%20

Gayo-Avello, D. (2011) "Don't turn social media into another "Literary Digest" poll". Communications of the ACM, 54(10), pp.121–128. Available at: http://dl.acm.org/citation.cfm?doid=2001269.2001297 [Accessed March 1, 2012]. https://doi.org/10.1145/2001269.2001297

González-Bailón, S., Borge-Holthoefer, J. & Moreno, Y. (2013) "Broadcasters and Hidden Influentials in Online Protest Diffusion". American Behavioral Scientist, (0).

Grabowicz, P. a et al. (2012) "Social features of online networks: the strength of intermediary ties in online social media". PloS one, 7(1), p.e29358. Available at: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3256152&tool=pmcentrez&rendertype=abstract [Accessed March 2, 2012].

Hanna, A. et al. (2011) "Mapping the Political Twitterverse : Candidates and Their Followers in the Midterms". Artificial Intelligence, pp.510–513.

Hanneman, R. a. & Riddle, M. (2005) "Introduction to Social Network Methods: Table of Contents". Riverside, CA: University of California, Riverside ( published in digital form at http://faculty.ucr.edu/~hanneman/ ), 13(October). Available at: http://www.faculty.ucr.edu/~hanneman/nettext/.

Hirsch, J.E. (2005) "An index to quantify an individual's scentific research output". Proc Natl Acad Sci U S A, 102(46), pp.16569–16572. Available at: http://www.ncbi.nlm.nih.gov/pubmed/16275915. https://doi.org/10.1073/pnas.0507655102 PMid:16275915 PMCid:PMC1283832

Huberman, B.A., Romero, D.M. & Wu, F. (2009) "Social networks that matter : Twitter under the microscope". First Monday 14(1). Available at SSRN: http://ssrn.com/abstract=1313405.

Iacus, S.M. (2015) "Automated Data Collection with R - A Practical Guide to Web Scraping and Text Mining". Journal of Statistical Software, 68(Book Review 3). Available at: http://www.jstatsoft.org/v68/b03/.

Jungherr, A., Jurgens, P. & Schoen, H. (2011) "Why the Pirate Party Won the German Election of 2009 or The Trouble With Predictions: A Response to Tumasjan, A., Sprenger, T. O., Sander, P. G., & Welpe, I. M. 'Predicting Elections With Twitter: What 140 Characters Reveal About Political Sentiment'." Social Science Computer Review. Available at: http://ssc.sagepub.com/cgi/doi/10.1177/0894439311404119 [Accessed April 11, 2012].

Leskovec, J., Lang, K.J. & Mahoney, M. (2010) "Empirical comparison of algorithms for network community detection". Proceedings of the 19th international conference on World wide web - WWW '10, p.631. Available at: http://portal.acm.org/citation.cfm?doid=1772690.1772755. https://doi.org/10.1145/1772690.1772755

Livne, A. et al. (2010) "The Party is Over Here : Structure and Content in the 2010 Election". Proceedings of the Fifth International AAAI Conference on Weblogs and Social Media, pp.201–208.

Morales, A. J. et al. (2015) "Measuring political polarization: Twitter shows the two sides of Venezuela". Chaos: An Interdisciplinary Journal of Nonlinear Science, 25, p.33114. Available at: http://scitation.aip.org/content/aip/journal/chaos/25/3/10.1063/1.4913758. https://doi.org/10.1063/1.4913758

Newman, M.E.J. (2005) "Power laws, Pareto distributions andZipf's law". Contemporary physics, 46(5), pp.323–351. Available at: http://arxiv.org/abs/cond-mat/0412004. https://doi.org/10.1080/00107510500052444

Newman, M.E.J. & Girvan, M. (2004) "Finding and evaluating community structure in networks". Physical Review E, 69(2), pp.1– 16. Available at: http://arxiv.org/abs/cond-mat/0308217%0A. https://doi.org/10.1103/PhysRevE.69.026113 PMid:14995526

Noelle-Neumann, E. (1995) "La Espiral del silencio: opinión pública: nuestra piel social". Paidós comunicación, 62, p.331. Available at: http://biblioteca.uoc.edu/llibres/19198.htm.

Page, L. et al. (1998) "The PageRank Citation Ranking: Bringing Order to the Web". World Wide Web Internet And Web Information Systems, 54(1999–66), pp.1–17. Available at: http://ilpubs.stanford.edu:8090/422.

Pe-a-López, I., Congosto, M. & Aragón, P. (2014) "Spanish Indignados and the evolution of the 15M movement on Twitter: towards networked para-institutions". Journal of Spanish Cultural Studies, 15(1–2), pp.189–216. https://doi.org/10.1080/14636204.2014.931678

Romero, D.M. & Huberman, B.A. (2011) "Influence and Passivity in Social Media". In Machine learning and knowledge discovery in databases. Springer Berlin Heidelberg, pp. 18–33. https://doi.org/10.1145/1963192.1963250

Stella, M., Ferrara, E. & De Domenico, M. (2018) Bots sustain and inflate striking opposition in online social systems, pp.1–10. Available at: http://arxiv.org/abs/1802.07292.

Toret, J., Calleja, A., Miró, Ó. M., Aragón, P., Aguilera, M., & Lumbreras, A. (2013) Tecnopolítica: la potencia de las multitudes conectadas. El sistema red 15M , un nuevo paradigma de la política distribuida. Universitat Oberta de Catalunya, Internet Interdisciplinary Institute, Working Paper Series RR13-001.

Wang, Y., Li, Y. & Luo, J. (2016) "Deciphering the 2016 U.S. Presidential Campaign in the Twitter Sphere: A Comparison of the Trumpists and Clintonists". Proceedings of the Tenth International AAAI Conference on Web and Social Media (ICWSM), (Icwsm), pp.723–726. Available at: http://arxiv.org/abs/1603.03097.




Copyright (c) 2019 Consejo Superior de Investigaciones Científicas (CSIC)

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.


Contact: historia.digital@cchs.csic.es

Technical support: soporte.tecnico.revistas@csic.es