Fake news y coronavirus: detección de los principales actores y tendencias a través del análisis de las conversaciones en Twitter

Autores/as

DOI:

https://doi.org/10.3145/epi.2020.may.08

Palabras clave:

Coronavirus, Covid-19, Pandemias, Salud, Crisis sanitarias, Información de salud, Noticias falsas, Difusión de información, Desinformación, Conversación, Comunicación polí­tica, Medios sociales, Análisis de redes sociales, Twitter, NodeXL, Donald Trump.

Resumen

La crisis sanitaria global surgida por la expansión del Covid-19 ha llevado a la OMS a acuñar el término infodemia para definir una situación de miedo e inseguridad en la que la difusión de información falsa se ha generalizado. Estos bulos se aprovechan de este tipo de emociones para propagarse más rápido que el propio coronavirus, generando a su paso temor y desconfianza en la población. La difusión de estas mentiras, parte de las cuales circula por las redes sociales, resulta peligrosa porque afecta a la salud y puede hacer que se agrave el contagio y provocar la muerte de personas. Esta investigación tiene como objetivo analizar y visualizar la red tejida alrededor de las noticias falsas que circulan en Twitter sobre la pandemia del coronavirus mediante la técnica del análisis de redes sociales. Se ha empleado el software NodeXL Pro. Se han utilizado varias medidas de centralidad para generar la red de conexiones entre los usuarios, representar sus patrones de interacción e identificar los actores clave dentro de la estructura. Además, también se ha creado una red semántica para descubrir las diferencias en la forma en que los grupos de personas hablan sobre el tema. Los resultados muestran que la situación en EUA domina la conversación, pese a que en ese momento apenas registraba casos y Europa se habí­a convertido en el epicentro global del Covid-19. A pesar de las acusaciones de inacción de periodistas y crí­ticos del gobierno de Trump, se observan varias semanas en las que la desinformación distrae de tomar medidas más eficaces y prevenir verdaderamente el contagio. Además, entre los actores con posiciones más destacadas en la red se constata la escasa presencia de cientí­ficos e instituciones que ayuden a desmentir los bulos y expliquen las medidas de higiene. 

Descargas

Los datos de descargas todavía no están disponibles.

Biografía del autor/a

Jesus-Angel Pérez-Dasilva, Universidad del Paí­s Vasco

Licenciado (1998) y doctor (2006) en Periodismo por la UPV/EHU, donde ejerce de profesor desde 2001. Ha sido vicedecano de la Facultad de Ciencias Sociales y de la Comunicación (2009-2012), director del Máster de Comunicación Social (2016-2018) y miembro de la Comisión Universitaria de Evaluación Docente (2016-2019).

Es miembro el grupo de investigación Gureiker (grupo A del sistema universitario vasco). Ha sido profesor visitante en la Universidad de Cambridge (UK, 2012) y en la Universidad de Sevilla (2010). Ha participado en el programa Erasmus+ para la movilidad del profesorado en las siguientes universidades: Universidad de Trieste (Italia, 2011), Universidad de Beira interior (Portugal, 2013), Universidad de Oporto (Portugal, 2015), Universidad do Minho (Portugal, 2016), Universidad de Wroclaw (Polonia, 2017 y 2019).

Ha participado en 20 proyectos de investigación siendo en 5 de ellos el investigador principal. Es coautor de 46 artí­culos cientí­ficos, 32 capí­tulos de libro y de 70 contribuciones en congresos nacionales e internacionales. Cuenta con 2 sexenios reconocidos por la CNEAI. Sus lí­neas de investigación se centran en la transformación digital del periodismo. Sus últimos trabajos están relacionados con la audiencia, la interactividad y las redes sociales

Koldobika Meso-Ayerdi, Universidad del Paí­s Vasco

Es profesor titular y director del Departamento de Periodismo II de la Universidad del Paí­s Vasco (UPV/EHU). Es doctor en Periodismo por la misma universidad. Miembro de los grupos de investigación: Gureiker (UPV/EHU) e Infotendencias (financiado por el Micinn), participa en varios proyectos nacionales e internacionales, en los que estudia la transformación del periodismo en el entorno digital. Su principal interés de investigación es la audiencia y la interactividad.

Terese Mendiguren-Galdospí­n, Universidad del Paí­s Vasco

Es profesora en el Departamento de Periodismo II de la Universidad del Paí­s Vasco (UPV/EHU). Autora de trabajos sobre ciberperiodismo, investiga tendencias del periodismo contemporáneo como el periodismo ciudadano o el empleo de las redes sociales en la difusión de la información. Es miembro del grupo consolidado Gureiker.

Citas

Adajar, Aaron (2020). Aaron Adajar on Twitter: «Isa sa pinakamaganda mong maa-ambag about Covid-19 outbreak ay "pananahimik" Stop spreading fake news and do research first before posting something online. And also, Wash your hands intensely. Avoid touching your face. Pray. Pray. Pray». Twitter, March 9. https://twitter.com/aaronadajar/status/1237029903112888321

Aguilar-Gallegos, Norman; Martí­nez-González, Enrique-Genaro; Aguilar-Ávila, Jorge; Santoyo-Cortés, Horacio; Muñoz-Rodrí­guez, Manrrubio; Garcí­a-Sánchez, Edgar-Iván (2016). "Análisis de redes sociales para catalizar la innovación agrí­cola: De los ví­nculos directos a la integración y radialidad". Estudios gerenciales, v. 32, n. 140, pp. 197-207. https://doi.org/10.1016/j.estger.2016.06.006

Ahmed, Wasim; Lugovic, Sergej (2019). "Social media analytics: Analysis and visualisation of news diffusion using NodeXL. Online information review", v. 43, n. 1, pp. 149-160. https://doi.org/10.1108/OIR-03-2018-0093

Albalawi, Yahya; Nikolov, Nikola S.; Buckley, Jim (2019). "Trustworthy health-related tweets on social media in Saudi Arabia: Tweet metadata analysis". Journal of medical internet research, v. 21, n. 10, e14731. https://doi.org/10.2196/14731

Allcott, Hunt; Gentzkow, Matthew (2017). "Social media and fake news in the 2016 election". Journal of economic perspectives, v. 31, n. 2, pp. 211-236. https://doi.org/10.1257/jep.31.2.211

Araujo, Matheus; Mejova, Yelena; Weber, Ingmar; Benevenuto, Fabrizio (2017). "Using Facebook ads audiences for global lifestyle disease surveillance: Promises and limitations". In: Proceedings of the 2017 ACM on Web science conference, pp. 253-257. https://doi.org/10.1145/3091478.3091513

Bae, Ka-Ryeong; Kwon, Sunyoung; Cho, Juhee (2019). "What cancer survivors are discussing on the internet about returning to work: A social network analysis". Asian oncology nursing, v. 19, n. 1, pp. 37-46. https://doi.org/10.5388/aon.2019.19.1.37

Bakal, Gotkhan; Kavuluru, Ramakanth (2017). "On quantifying diffusion of health information on Twitter". 2017 IEEE EMBS International conference on biomedical & health informatics (BHI), pp. 485-488. https://doi.org/10.1109/BHI.2017.7897311

Bakshy, Eytan; Hofman, Jake M.; Mason, Winter A.; Watts, Duncan J. (2011). "Everyone´s an influencer: Quantifying influence on Twitter". Proceedings of the Fourth ACM International conference on web search and data mining - WSDM ´11, pp. 65-74. https://doi.org/10.1145/1935826.1935845

Benson, Phil (2016). The discourse of YouTube: Multimodal text in a global context. Routledge. https://doi.org/10.4324/9781315646473

Berkowitz, Dan; Schwartz, David-Asa (2016). "Miley, CNN and The Onion: When fake news becomes realer than real". Journalism practice, v. 10, n. 1, pp. 1-17. https://doi.org/10.1080/17512786.2015.1006933

Borgatti, Stephen P.; Mehra, Ajay; Brass, Daniel J.; Labianca, Giuseppe (2009). "Network analysis in the social sciences". Science, v. 323, n. 5916, pp. 892-895. https://doi.org/10.1126/science.1165821

Boyd, Michael S. (2014). "(New) participatory framework on YouTube? Commenter interaction in US political speeches". Journal of pragmatics, v. 72, pp. 46-58. https://doi.org/10.1016/j.pragma.2014.03.002

Broniatowski, David A.; Jamison, Amelia M.; Qi, Sihua; AlKulaib, Lulwah; Chen, Tao; Benton, Adrian; Quinn, Sandra C.; Dredze, Mark (2018). "Weaponized health communication: Twitter bots and Russian trolls amplify the vaccine debate". American journal of public health, v. 108, n. 10, pp. 1378-1384. https://doi.org/10.2105/AJPH.2018.304567

Brubaker, Pamela-Jo; Wilson, Christopher (2018). "Let´s give them something to talk about: Global brands´ use of visual content to drive engagement and build relationships". Public relations review, v. 44, n. 3, pp. 342-352. https://doi.org/10.1016/j.pubrev.2018.04.010

Cheng, Tiffany Yi-Mei; Liu, Lisa; Woo, Benjamin K. (2018). "Analyzing Twitter as a platform for Alzheimer-related dementia awareness: Thematic analyses of tweets". JMIR aging, v. 1, n. 2, e11542. https://doi.org/10.2196/11542

Chu, Zi; Gianvecchio, Steven; Wang, Haining; Jajodia, Sushil (2012). "Detecting automation of Twitter accounts: Are you a human, bot, or cyborg?". IEEE Transactions on dependable and secure computing, v. 9, n. 6, pp. 811-824. https://doi.org/10.1109/TDSC.2012.75

Chung, Chia-Fang; Agapie, Elena; Schroeder, Jessica; Mishra, Sonali; Fogarty, James; Munson, Sean A. (2017). "When personal tracking becomes social: Examining the use of Instagram for healthy eating". Proceedings of the 2017 CHI Conference on human factors in computing systems, pp. 1674-1687. https://doi.org/10.1145/3025453.3025747

Clauset, Aaron; Newman, Mark E. J.; Moore, Cristopher (2004). "Finding community structure in very large networks". Physical review E, v. 70, n. 6, pp. 66-111. https://doi.org/10.1103/PhysRevE.70.066111

Cosentino, Gabriele (2020). "Polarize and conquer: Russian influence operations in the United States". In: Cosentino, Gabriele. Social media and the post-truth world order. Springer International Publishing, pp. 33-57. ISBN: 978 3 030430054 https://doi.org/10.1007/978-3-030-43005-4_2

Currie-Sivek, Susan; Bloyd-Peshkin, Sharon (2018). "Where do facts matter?: The digital paradox in magazines´ fact-checking practices". Journalism practice, v. 12, n. 4, pp. 400-421. https://doi.org/10.1080/17512786.2017.1307694

Dossis, Michael; Amanatidis, Dimitrios; Mylona, Ifigeneia (2015). "Mining Twitter data: Case studies with trending hashtags". In: Proceedings in ARSA-Advanced research in scientific areas, 4th Virtual international conference on advanced research in scientific areas (ARSA), Slovakia, pp. 242-246. https://doi.org/10.18638/arsa.2015.4.1.751

Dredze, Mark; Broniatowski, David A.; Hilyard, Karen M. (2016). "Zika vaccine misconceptions: A social media analysis". Vaccine, v. 34, n. 30, pp. 3441-3442. https://doi.org/10.1016/j.vaccine.2016.05.008

Eichenwald, Kurt (2020). Kurt Eichenwald on Twitter: "...It is almost incomprehensible that the second stupidest man in the world is leading the Covid-19 team for the American government, while reporting to the stupidest man in the world who tells everyone it isn´t real, it isn´t bad, go to work, fake news, hoax, fake numbers, etc.". Twitter, March 7. https://twitter.com/kurteichenwald/status/1236068998883741696

Evans, Matt (2016). "Information dissemination in new media: YouTube and the Israeli-Palestinian conflict". Media, war & conflict, v. 9, n. 3, pp. 325-343. https://doi.org/10.1177/1750635216643113

Fernández, Deborah (2019). "Análisis de grafos en redes sociales: Medidas de centralidad". Datahack, 19 agosto. https://www.datahack.es/grafos-redes-sociales-centralidad

Fox, Susannah (2011). "The social life of health information, 2011". Pew Research Center: Internet, science & tech, 12 May. https://www.pewresearch.org/internet/2011/05/12/the-social-life-of-health-information-2011

Freeman, Linton C. (2004). "The development of social network analysis". A study in the sociology of science, v. 1, p. 687. ISBN: 978 1 594577147

Frish, Yael; Greenbaum, Dov (2017). "Is social media a cesspool of misinformation? Clearing a path for patient-friendly safe spaces online". The American journal of bioethics, v. 17, n. 3, pp. 19-21. https://doi.org/10.1080/15265161.2016.1274795

Ghenai, Amira; Mejova, Yelena (2017). "Catching Zika fever: Application of crowdsourcing and machine learning for tracking health misinformation on Twitter". 2017 IEEE International conference on healthcare informatics (ICHI), pp. 518-518. https://doi.org/10.1109/ICHI.2017.58

Ghenai, Amira; Mejova, Yelena (2018). "Fake cures: User-centric modeling of health misinformation in social media". Proceedings of the ACM on human-computer interaction, 2 (CSCW), pp. 1-20. https://doi.org/10.1145/3274327

Gibbs, William J.; McKendrick, Joseph (eds.). (2015). Contemporary research methods and data analytics in the news industry. Hershey, PA: IGI Global. https://doi.org/10.4018/978-1-4666-8580-2

Goní§alves-Sá, Joana (2020). "In the fight against the new coronavirus outbreak, we must also struggle with human bias". Nature medicine, v. 26, n. 3, pp. 305-305. https://doi.org/10.1038/s41591-020-0802-y

Gu, Rui; Hong, Yili-Kevin (2019). "Addressing health misinformation dissemination on mobile social media". In: 2019 ICIS Conference. https://aisel.aisnet.org/icis2019/is_health/is_health/29

Gueham, Farid (2017). Le fact-checking: une réponse à la crise de l´information et de la démocratie. Paris: Fondation pour l´innovation politique. http://www.fondapol.org/wp-content/uploads/2017/07/1110-Fact-checking_2017-07-10_web.pdf

Guidry, Jeanine P. D.; Jin, Yan; Orr, Caroline A.; Messner, Marcus; Meganck, Shana (2017). "Ebola on Instagram and Twitter: How health organizations address the health crisis in their social media engagement". Public relations review, v. 43, n. 3, pp. 477-486. https://doi.org/10.1016/j.pubrev.2017.04.009

Hansen, Derek; Shneiderman, Ben; Smith, Marc A. (2010). Analyzing social media networks with NodeXL: Insights from a connected world. Morgan Kaufmann. ISBN: 978 0 123822291

Harel, David; Koren, Yehuda (2000). "A fast multi-scale method for drawing large graphs". Proceedings of the Working conference on advanced visual interfaces - AVI´00, pp. 282-285. https://doi.org/10.1145/345513.345353

Harper, Rob (2020). @robjh1: The Conservative Black Cowboy on Twitter: "Rush Limbaugh and AG Bill Barr call out the left wing media. The left wing media has become agents of division and anarchy. Instead of informing they seek to attack and destroy with fake news. ##FakeNewsMedia #coronavirus". Twitter. https://twitter.com/robjh1/status/1233266971237593088

Hasting, Carl (2020). Carl Hasting on Twitter: "I passed someone from an adjacent office today and said, "Are you following this Coronavirus situation? Scary." She replied, "Fake news!" And there you have the danger of Trump and Fox ignorantly downplaying a world crisis and blaming it on the Dems". Twitter, February 27. https://twitter.com/67jewelcdh/status/1232885944623063040

Herchel-Thaddeus, Machacon (2016). "A topological data analysis approach to visualizing Ebola tweets". Japan journal for medical informatics, v. 36, n. 5, pp. 253-269. https://doi.org/10.14948/jami.36.253

Himelboim, Itai; Han, Jeong-Yeob (2014). "Cancer talk on Twitter: Community structure and information sources in breast and prostate cancer social networks". Journal of health communication, v. 19, n. 2, pp. 210-225. https://doi.org/10.1080/10810730.2013.811321

Hou, Rui; Pérez-Rosas, Verónica; Loeb, Stacy; Mihalcea, Rada (2019). "Towards automatic detection of misinformation in online medical videos". In: 2019 International conference on multimodal interaction, pp. 235-243. https://arxiv.org/abs/1909.01543

Jamison, Amelia M.; Broniatowski, David A.; Quinn, Sandra-Crouse (2019). "Malicious actors on Twitter: A guide for public health researchers". American journal of public health, v. 109, n. 5, pp. 688-692. https://doi.org/10.2105/AJPH.2019.304969

Javanainen, Petra-Marika (2020). The role of social media in attitudes towards vaccinations: Social media as a tool in vaccination movements.

http://www.theseus.fi/handle/10024/334093

Jones, Sarah (2020). Sarah Reese Jones on Twitter: "That Vanity Fair story Trump doesn´t want you to read... "Publicly, he sees it as yet another («Fake news») media war; privately, he worries about virus-carrying journalists on Air Force One" "He´s Definitely Melting Down Over This". Twitter, March 11. https://twitter.com/politicussarah/status/1237778298530344961

Kaleel, Shakira-Banu; Abhari, Abdolreza (2015). "Cluster-discovery of Twitter messages for event detection and trending". Journal of computational science, v. 6, pp. 47-57. https://doi.org/10.1016/j.jocs.2014.11.004

Kata, Anna (2012). "Anti-vaccine activists, Web 2.0, and the postmodern paradigm - An overview of tactics and tropes used online by the anti-vaccination movement". Vaccine, v. 30, n. 25, pp. 3778-3789. https://doi.org/10.1016/j.vaccine.2011.11.112

Laylavi, Farhad; Rajabifard, Abbas; Kalantari, Mohsen (2017). "Event relatedness assessment of Twitter messages for emergency response". Information processing & management, v. 53, n. 1, pp. 266-280. https://doi.org/10.1016/j.ipm.2016.09.002

Leonhardt, James (2015). "Going viral on YouTube". Journal of digital & social media marketing, v. 3, n. 1, pp. 21-30. https://www.ingentaconnect.com/content/hsp/jdsmm/2015/00000003/00000001/art00004

Lichoti, Jacqueline-Kasiiti; Davies, Jocelyn; Kitala, Philip M.; Githigia, Samuel M.; Okoth, Edward; Maru, Yiheyis; Bukachi, Salome A.; Bishop, Richard P. (2016). "Social network analysis provides insights into African swine fever epidemiology". Preventive veterinary medicine, v. 126, pp. 1-10. https://doi.org/10.1016/j.prevetmed.2016.01.019

Lipschultz, Jeremy-Harris (2017). Social media communication: Concepts, practices, data, law and ethics (2nd ed.). New York: Routledge. ISBN: 978 1 315388144 https://doi.org/10.4324/9781315388144

Mejova, Yelena; Haddadi, Hamed; Abbar, Sofiane; Ghahghaei, Azadeh; Weber, Ingmar (2015). "Dietary habits of an expat nation: Case of Qatar". In: Healthcare Informatics (ICHI), 215 International Conference on. IEEE, pp. 57-62. https://doi.org/ 10.1109/ICHI.2015.13.

Ministério da Saúde da Brasil (2020). Ministério da Saúde on Twitter: "As fake news sí£o um grande obstáculo no combate ao #coronaví­rus (Covid-19). Além de desinformar, elas podem gerar um alarde desnecessário entre a populaí§í£o. Antes de compartilhar notí­cias, confirme a veracidade delas. Proteja vocíª e sua famí­lia. Saiba mais". Twitter, Marí§o 4. https://twitter.com/minsaude/status/1235007050159190016

Mohr, Iris (2014). "Going viral: An analysis of YouTube videos". Journal of marketing development and competitiveness, v. 8, n. 3, pp. 43-48. http://na-businesspress.homestead.com/JMDC/MohrI_Web8_3_.pdf

Moorhead, S. Anne; Hazlett, Diane E.; Harrison, Laura; Carroll, Jennifer K.; Irwin, Anthea; Hoving, Ciska (2013). "A new dimension of health care: Systematic review of the uses, benefits, and limitations of social media for health communication". Journal of medical internet research, v. 15, n. 4, e85. https://doi.org/10.2196/jmir.1933

NPR (2020). NPR on Twitter: "The state of Missouri is suing televangelist Jim Bakker and his production company to stop them from advertising or selling a fake coronavirus remedy. The Covid-19 disease does not yet have a treatment or cure". Twitter, March 12. https://twitter.com/npr/status/1238014380526186499

Odlum, Michelle; Yoon, Sunmoo (2015). "What can we learn about the Ebola outbreak from tweets?". American journal of infection control, v. 43, n. 6, pp. 563-571. https://doi.org/10.1016/j.ajic.2015.02.023

Otte, Evelien; Rousseau, Ronald (2002). "Social network analysis: A powerful strategy, also for the information sciences". Journal of information science, v. 28, n. 6, pp. 441-453.

Paolillo, John C. (2008). Structure and network in the YouTube core. Proceedings of the 41st Annual Hawaii international conference on system sciences (HICSS 2008), pp. 156-156. https://doi.org/10.1109/HICSS.2008.415

Park, Se-Jung; Lim, Yon-Soo; Park, Han-Woo (2015). "Comparing Twitter and YouTube networks in information diffusion: The case of the "˜Occupy Wall Street´ movement". Technological forecasting and social change, v. 95, pp. 208-217. https://doi.org/10.1016/j.techfore.2015.02.003

Pauner-Chulvi, Cristina (2018). "Noticias falsas y libertad de expresión e información. El control de los contenidos informativos en la red". Teorí­a y realidad constitucional, n. 41, pp. 297-318. https://doi.org/10.5944/trc.41.2018.22123

Ross, Andrew S.; Caldwell, David (2020). ""˜Going negative´: An appraisal analysis of the rhetoric of Donald Trump on Twitter". Language & communication, n. 70, pp. 13-27. https://doi.org/10.1016/j.langcom.2019.09.003

Rupar, Aaron (2020). Aaron Rupar on Twitter: "Trump´s response to @acosta´s good question about concerns he isn´t taking coronavirus seriously enough was to call CNN "˜fake news´. White House handlers then immediately forced reporters out of the room". Twitter, March 11. https://twitter.com/atrupar/status/1237875754576146445

Scanfeld, Daniel; Scanfeld, Vanessa; Larson, Elaine L. (2010). "Dissemination of health information through social networks: Twitter and antibiotics". American journal of infection control, v. 38, n. 3, pp. 182-188. https://doi.org/10.1016/j.ajic.2009.11.004

Scott, John; Carrington, Peter (2014). The SAGE Handbook of social network analysis. London: SAGE Publications Ltd. ISBN: 978 1 847873958. https://doi.org/10.4135/9781446294413

Seo, Sungwon; Kim, Jong-Kook; Kim, Sung-Il; Kim, Jeewoo; Kim, Joongheon (2019). "Semantic hashtag relation classification using co-occurrence word information". Wireless personal communications, v. 107, n. 3, pp. 1355-1365. https://doi.org/10.1007/s11277-018-5745-y

Shao, Chengcheng; Hui, Pik-Mai; Wang, Lei; Jiang, Xinwen; Flammini, Alessandro; Menczer, Filippo; Ciampaglia, Giovanni-Luca (2018). "Anatomy of an online misinformation network". PLoS one, v. 13, n. 4, e0196087. https://doi.org/10.1371/journal.pone.0196087

Sharevski, Filipo; Jachim, Peter; Florek, Kevin (2020). "To tweet or not to tweet: Covertly manipulating a Twitter debate on vaccines using malware-induced misperceptions". arXiv:2003.12093 [cs]. http://arxiv.org/abs/2003.12093

Sherman, Gabriel (2020). "He´s definitely melting down over this: Trump, germaphobe in chief, struggles to control the Covid-19 story". Vanity fair, 9 March. https://www.vanityfair.com/news/2020/03/trump-germaphobe-in-chief-struggles-to-control-the-covid-19-story

Shu, Kai; Sliva, Amy; Wang, Suhang; Tang, Jiliang; Liu, Huan (2017). "Fake news detection on social media: A data mining perspective". ACM SIGKDD Explorations newsletter, v. 19, n. 1, pp. 22-36. https://doi.org/10.1145/3137597.3137600

Skeptical7th (2019). "Fact checking "˜Educating liberals´ aka Dylan Wheeler". The seventh degree. https://www.theseventhdegree.net/news/2018/11/3/fact-checking-educating-liberals

Smith, Marc; Milic-Frayling, Natasa; Shneiderman, Ben; Mendes-Rodrigues, Eduarda; Leskovec, Jure; Dunne, Cody (2010). NodeXL: A free and open network overview, discovery and exploration add-in for Excel 2007/2010. Social Media Research Foundation. https://www.smrfoundation.org

Staub, Harvey (2020). Harvey Staub on Twitter: "MSNBC Hopes Americans Dying From Coronavirus Will "Take Down Trump´s Presidency" https://t.co/XUBaj6Y8x1 Think. The fake news media wants you to die so that it hurts Pres. Trump. This is equivalent to Goebbels Nazi Propaganda". Twitter, March 12. https://twitter.com/harveystaub1/status/1237926081480491008

Stieglitz, Stefan; Mirbabaie, Milad; Ross, Bjorn; Neuberger, Christoph (2018). "Social media analytics - Challenges in topic discovery, data collection, and data preparation". International journal of information management, n. 39, pp. 156-168. https://doi.org/10.1016/j.ijinfomgt.2017.12.002

Syed-Abdul, Shabbir; Fernández-Luque, Luis; Jian, Wen-Shan; Li, Yu-Chuan; Crain, Steven; Hsu, Min-Huei; Wang, Yao-Chin; Khandregzen, Dorjsuren; Chuluunbaatar, Enkhzaya; Nguyen, Phung-Aanh; Liou, Der-Ming (2013). "Misleading health-related information promoted through video-based social media: Anorexia on YouTube". Journal of medical internet research, v. 15, n. 2, e30. https://doi.org/10.2196/jmir.2237

Tatchell, Peter (2020). Peter Tatchell on Twitter: "Heroic #HongKong bookseller #GuiMinhai abducted from Thailand in 2015 by Beijing agents. Now jailed for 10 years on fake espionage charges. China announced sentence during coronavirus outbreak to bury it https://t.co/dJktPpkVQN FOLLOW @demosisto @CHRDnet @hrichina @joshuawongcf". Twitter, February 27. https://twitter.com/PeterTatchell/status/1233113354253803521

Tolson, Andrew (2010). "A new authenticity? Communicative practices on YouTube". Critical discourse studies, v. 7, n. 4, pp. 277-289. https://doi.org/10.1080/17405904.2010.511834

Trump, Donald (2020). Donald J. Trump on Twitter: «Vanity Fair Magazine, which will soon be out of business, and their third rate Fake reporters, who make up sources which don´t exist, wrote yet another phony & boring hit piece. The facts are just the opposite. Our team is doing a great job with CoronaVirus!». Twitter, March 11. https://twitter.com/realdonaldtrump/status/1237745593876873217

Túñez-López, José-Miguel; Toural-Bran, Carlos; Cacheiro-Requeijo, Santiago (2018). "Uso de bots y algoritmos para automatizar la redacción de noticias: Percepción y actitudes de los periodistas en España". El profesional de la información, v. 27, n. 4, pp. 750-758. https://doi.org/10.3145/epi.2018.jul.04

Vázquez-Herrero, Jorge; Vizoso, Ángel; López-Garcí­a, Xosé (2019). "Innovación tecnológica y comunicativa para combatir la desinformación: 135 experiencias para un cambio de rumbo". El profesional de la información, v. 28, n. 3, e280301. https://doi.org/10.3145/epi.2019.may.01

Verweij, Peter (2012). "Twitter links between politicians and journalists". Journalism practice, v. 6, n. 5-6, pp. 680-691. https://doi.org/10.1080/17512786.2012.667272

Vosoughi, Soroush; Mohsenvand, Mostafa-Neo; Roy, Deb (2017). "Rumor gauge: Predicting the veracity of rumors on Twitter". ACM Transactions on knowledge discovery from data, v. 11, n. 4, article 50. https://doi.org/10.1145/3070644

Wang, Tao; Brede, Markus; Ianni, Antonella; Mentzakis, Emmanouil (2017). "Detecting and characterizing eating-disorder communities on social media". In: Proceedings of the Tenth ACM International conference on web search and data mining, pp. 91-100. https://doi.org/10.1145/3018661.3018706

Wasserman, Stanley; Faust, Katherine (1994). Social network analysis: Methods and applications (vol. 8). Cambridge University Press. ISBN: 9781 1 39788618

Wheeler, Dylan (2020). Educating Liberals on Twitter: "The stock market dropped 1200 points today - the single worst drop in its history. This is what happens when the Fake news Media scares the public into believing the Coronavirus is worse than the Spanish flu. They will do anything to hurt Trump´s image before election season". Twitter, February 27. https://twitter.com/education4libs/status/1233146925689516032

White, Sean (2020). Sean White USMCSDI on Twitter: "Dear America: The ONLY difference between THIS pandemic of Coronavirus and the other hundreds we´ve dealt with is that FAKE NEWS has decided to POLITICIZE it because scumbag, left wing slobs know NO shame NOBODY lost their minds like this when 13K Americans died of H1N1 in 2010". Twitter, March 12. https://twitter.com/usmcsdi/status/1237895813667282945

Williams, Shirley A.; Terras, Melissa M.; Warwick, Claire (2013). "What do people study when they study Twitter? Classifying Twitter related academic papers". Journal of documentation, v. 69, n. 3, pp. 384-410. https://doi.org/10.1108/JD-03-2012-0027

Wood, Michael J. (2018). "Propagating and debunking conspiracy theories on Twitter during the 2015-2016 Zika virus outbreak". Cyberpsychology, behavior, and social networking, v. 21, n. 8, pp. 485-490. https://doi.org/10.1089/cyber.2017.0669

Wu, Shaomei; Hofman, Jake M.; Mason, Winter A.; Watts, Duncan J. (2011). "Who says what to whom on Twitter". Proceedings of the 20th International Conference on world wide web - WWW ´11, pp. 705-714. https://doi.org/10.1145/1963405.1963504

Wukich, Clayton; Steinberg, Alan (2013). "Nonprofit and public sector participation in self-organizing information networks: Twitter hashtag and trending topic use during disasters: Self-organizing information networks". Risk, hazards & crisis in public policy, v. 4, n. 2, pp. 83-109. https://doi.org/10.1002/rhc3.12036

Xiong, Ying; Cho, Moonhee; Boatwright, Brandon (2019). "Hashtag activism and message frames among social movement organizations: Semantic network analysis and thematic analysis of Twitter during the #MeToo movement". Public relations review, v. 45, n. 1, pp. 10-23. https://doi.org/10.1016/j.pubrev.2018.10.014

Xu, Zhan (2019). "Personal stories matter: Topic evolution and popularity among pro- and anti-vaccine online articles". Journal of computational social science, v. 2, n. 2, pp. 207-220. https://doi.org/10.1007/s42001-019-00044-w

Xu, Zhan; Ellis, Lauren; Umphrey, Laura R. (2019). "The easier the better? Comparing the readability and engagement of online pro- and anti-vaccination articles". Health education & behavior, v. 46, n. 5, pp. 790-797. https://doi.org/10.1177/1090198119853614

Yang, Haodong; Yang, Christopher C. (2013). "Harnessing social media for drug-drug interactions detection". 2013 IEEE International conference on healthcare informatics, pp. 22-29. https://doi.org/10.1109/ICHI.2013.10

Yom-Tov, Elad; Fernández-Luque, Luis; Weber, Ingmar; Crain, Steven P. (2012). "Pro-anorexia and pro-recovery photo sharing: A tale of two warring tribes". Journal of medical internet research, v. 14, n. 6, e151. https://doi.org/10.2196/jmir.2239

Zubiaga, Arkaitz; Liakata, Maria; Procter, Rob; Wong-Sak-Hoi, Geraldine; Tolmie, Peter (2016). "Analysing how people orient to and spread rumours in social media by looking at conversational threads". PLoS one, v. 11, n. 3, e0150989. https://doi.org/10.1371/journal.pone.0150989

Descargas

Archivos adicionales

Publicado

2020-05-08

Cómo citar

Pérez-Dasilva, J.-A., Meso-Ayerdi, K., & Mendiguren-Galdospí­n, T. (2020). Fake news y coronavirus: detección de los principales actores y tendencias a través del análisis de las conversaciones en Twitter. Profesional De La información, 29(3). https://doi.org/10.3145/epi.2020.may.08

Número

Vol. 29 Núm. 3 (2020): Relaciones Públicas

Sección

Artí­culos de investigación Covid-19 / Covid-19 research articles

Licencia

Condiciones de difusión de los artí­culos una vez son publicados

Los autores pueden publicitar libremente sus artí­culos en webs, redes sociales y repositorios
Deberán respetarse sin embargo, las siguientes condiciones:
- Solo deberá hacerse pública la versión editorial. Rogamos que no se publiquen preprints, postprints o pruebas de imprenta.
- Junto con esa copia ha de incluirse una mención especí­fica de la publicación en la que ha aparecido el texto, añadiendo además un enlace clicable a la URL: http://revista.profesionaldelainformacion.com

La revista Profesional de la información ofrece los artí­culos en acceso abierto con una licencia Creative Commons BY.