Da personalização algorítmica às guerras informacionais: a dinâmica das bolhas de (des)informação em torno do Dia 7 de setembro de 2021

Karen Santos-d'Amorim; Raimundo Nonato Macedo dos Santos

doi:10.5007/1518-2924.2022.e86628

Autores/as

Karen Santos-d'Amorim Universidade Federal de Pernambuco, Programa de Pós-graduação em Ciência da Informação (PPGCI-UFPE). https://orcid.org/0000-0002-2043-3853
Raimundo Nonato Macedo dos Santos Universidade Federal de Pernambuco https://orcid.org/0000-0002-9208-3266

DOI:

https://doi.org/10.5007/1518-2924.2022.e86628

Palabras clave:

Desinformación, Cámaras de eco , Filtros de burbujas, Exposición selectiva a la información, Twitter

Resumen

Objetivo: La retórica antidemocrática relacionada con las festividades del Día de la Independencia de Brasil de 2021 se difundió rápidamente en las redes sociales, creando burbujas informativas susceptibles a la amplia difusión de piezas desinformativas. Centrándose en la producción, circulación y uso de la información, este estudio investiga las características de estas burbujas de (des)información en Twitter.

Método: el análisis de datos se realizó a partir de la combinación de Análisis de Redes Sociales y Análisis de Contenido, con una encuesta realizada a través de la Interfaz de Programación de Aplicaciones (API) de Twitter utilizando el término de búsqueda “7 de Setembro”.

Resultados: a partir del análisis de 40.000 tweets, se identificó que en seis de los ocho días analizados, una sola burbuja tuvo la mayor influencia en la red. Se identificaron cuatro características que contribuyeron a ello: (1) la prevalencia del uso de bots políticos (77,8% de n = 28) para compartir temas de interés; o (2) uso intencional de hashtags con mayor esfuerzo de coordinación y movilización; y (3) uso de fuentes y tipos de información derivados de medios partidistas (83,3% de n = 20), que en su mayoría apelan a la estética, los afectos y las pasiones colectivas.

Conclusiones: si, por un lado, las estrategias de selección y entrega de información son fundamentales en un mundo donde la información se produce a gran escala, por otro lado, la forma poco transparente en que se realiza esta personalización se ha convertido en una fórmula dañina para la ámbito democrático, al permitir la propagación de desinformación a gran escala, además de reposicionar en el centro del debate ideologías extremistas que alguna vez fueron periféricas, ética y moralmente rechazadas.

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Biografía del autor/a

Karen Santos-d'Amorim, Universidade Federal de Pernambuco, Programa de Pós-graduação em Ciência da Informação (PPGCI-UFPE).

Doutoranda (Doutorado Direto) em Ciência da Informação no Programa de Pós-Graduação em Ciência da Informação da Universidade Federal de Pernambuco (DCI/UFPE), com Especialização em Gestão de Projetos, tendo atuado na Gestão de Projetos de Ciência, Tecnologia e Inovação: Instituto Nacional de Ciência e Tecnologia (INCT- INAMI) e Capes (Capes Nanobiotec Brasil - Rede 36). É membro dos grupos de Pesquisa SCIENTIA (CNPq/DCI/UFPE), Estudos Epistemológicos em Informação (EEI) e GrandFoton (CNPq/dQF/UFPE). É membro da Associação Nacional de Pesquisa e Pós-Graduação em Ciência da Informação (ANCIB) e parecerista ad-hoc de periódicos da Ciência da Informação e interdisciplinares.

Raimundo Nonato Macedo dos Santos, Universidade Federal de Pernambuco

É doutor em Information Stratégique et Critique Veille Technol - Université Paul Cézanne Aix Marseille III (1995), menção Très Honorable - Felicitation du Jury, e estágio pós-doutoral na Universidad Carlos III de Madrid (2016). É líder do grupo de pesquisa SCIENTIA (CNPq), bolsista de Produtividade em Pesquisa do CNPq nível 1C e docente credenciado como orientador e pesquisador no Programa de Ciência da Informação (PPGCI) da Universidade Federal de Pernambuco. É membro das Sociedades Científicas de sua especialidade: Associação Nacional de Pesquisa e Pós-Graduação em Ciência da Informação (ANCIB) e do Capítulo Brasileiro da International Society for Knowledge Organization ISKO, no Brasil.

Foi membro Titular do Comitê de Assessoramento Científico da área de Comunicação, Artes e Ciência da Informação do CNPq (2017 a 2020) e é parecerista ad hoc de agências de fomento, revisor e membro de Comitês Científicos de periódicos científicos em Ciência da Informação no Brasil.

Tem experiência na área de Ciência da Informação, com ênfase em Teoria Geral da Informação, atuando principalmente nos seguintes temas: Ciência da Informação, Bibliometria, Cientometria, Estudos Métricos, Comunicação Científica e Institucionalização da Pesquisa Científica.

Citas

AKERS, J. et al. Technology-Enabled Disinformation: Summary, Lessons, and Recommendations. arXiv.org, [s. l.], v. 1, 2018. Disponível em: https://arxiv.org/abs/1812.09383. Acesso em: 25 fev. 2022.

ARAUJO, R. F.; OLIVEIRA, T. M. Desinformação e mensagens sobre a hidroxicloroquina no Twitter: da pressão política à disputa científica. AtoZ: novas práticas em informação e conhecimento, v. 9, n. 2, p. 196-205, 2020. DOI: https://doi.org/10.5380/atoz.v9i2.75929

ATEFEH, F.; KHREICH, W. A Survey of Techniques for Event Detection in Twitter. Computational Intelligence, v. 31, p. 132-164, 2015. DOI: https://doi.org/10.1111/coin.12017

AZEVEDO, M. L.; ROBERTSON, S. L. Authoritarian populism in Brazil: Bolsonaro’s Caesarism, ‘counter-trasformismo’ and reactionary education politics. Globalisation, Societies and Education, v. 20, n. 2, p. 151-162, 2022. DOI: https://doi.org/10.1080/14767724.2021.1955663

BARAKAT, A.; DABBOUS, K.; TARHINI, A. An empirical approach to understanding users' fake news identification on social media. Online Information Review, v. 45, n. 6, p. 1080-1096, 2021. DOI: https://doi.org/10.1108/OIR-08-2020-0333

BARBERÁ, P. How social media reduces mass political polarization. Evidence from Germany, Spain, and the U.S. In: American Political Science Association conference, 2015, Proceedings […] San Francisco, CA, 2015.

BARBERÁ, P. Social Media, Echo Chambers, and Political Polarization. In: PERSILY, Nathaniel; TUCKER, Joshua (org.). Social Media and Democracy: The State of the Field and Prospects for Reform, Cambridge: Cambridge University Press, 2020. p. 34-55. DOI: https://doi.org/10.1017/9781108890960.004

BARBERÁ, P.; STEINERT-THRELKELD, Z. How to use social media data for Political Science Research. In: CURINI, Luigi; FRANZESE, Robert (ed.). The SAGE Handbook of Research Methods in Political Science and International Relations.Thousand Oaks, CA: SAGE Publications, 2020. DOI: https://doi.org/10.4135/9781526486387.n26

BARHATE, S. et al. Twitter bot detection and their influence in hashtag manipulation. In: IEEE India Council International Conference, 17, 2020, India. Proceedings […]. India: IEEE, 2020, p. 1-7. DOI: https://doi.org/10.1109/INDICON49873.2020.9342152

BASTIAN, M., HEYMANN, S., & JACOMY, M. Gephi: an open source software for exploring and manipulating networks. Proceedings of the international AAAI conference on web and social media, v. 3, n. 1, 2009.

BRAZIL'S Bolsonaro: Only God will remove me from power. BBC, 2021. Disponível em: https://www.bbc.com/news/world-latin-america-58479028. Acesso em: 18 out. 2021

BEERS, D. The Public Sphere and Online, Independent Journalism. Revue Canadienne de L’éducation, v. 29, n. 1, 2006. DOI: https://doi.org/10.2307/20054149

BERGER, J. M.; MORGAN, J. The ISIS Twitter census: defining and describing the population of ISIS supporters on Twitter. Washington, DC: The Brookings Institution, 2015.

BESSI, A.; FERRARA, E. Social bots distort the 2016 US presidential election online discussion. First Monday, v. 21, n. 11, 2016. DOI: https://doi.org/10.5210/fm.v21i11.7090

BEZERRA, A. C. Vigilância e cultura algorítmica no novo regime global de mediação da

Informação. Perspectivas em Ciência da Informação, v. 22, n. 4, p. 68-81, 2017. DOI: https://doi.org/10.1590/1981-5344/2936

BEZERRA, A. C.; ALMEIDA, M. A. Rage against the machine learning: a critical approach to the algorithmic mediation of information. Brazilian Journal of Information Science: research trends, v. 14, n. 2, 2020. DOI: https://doi.org/10.36311/1981-1640.2020.v14n2.02.p6

BICALHO, L. A. G. A função mediadora das hashtags no processo de impeachment de Dilma Rousseff: semiose e transmídia. Tese (Doutorado em Comunicação Social) -

Faculdade de Filosofia e Ciências Humanas, Universidade Federal de Minas Gerais. Minas Gerais, 2019.

BOLSOVER, G.; HOWARD, P. Chinese computational propaganda: automation, algorithms and the manipulation of information about Chinese politics on Twitter and Weibo. Information, Communication & Society, v. 22, n. 14, p. 2063-2080, 2019. DOI: https://doi.org/10.1080/1369118X.2018.1476576

BOYD, D. It’s complicated: the social lives of networked teens. New Haven: Yale University Press, 2014.

BRADSHAW, S.; HOWARD, P. Social Media and Democracy in Crisis. In: GRAHAM, M.; DUTTON, W. H. (ed.). Society and the Internet: How Networks of Information and Communication are Changing Our Lives. United Kingdom: Oxford University Press, 2019.

BRONIATOWSKI, D. A. et al. Weaponized health communication: Twitter bots and Russian trolls amplify the vaccine debate. American Journal of Public Health, v. 108, n. 10, p. 1378-1384, 2018. DOI: https://doi.org/10.2105/AJPH.2018.304567

CABALLERO, F. S. Guerra informacional y sociedad-red: la potencia inmaterial de los ejércitos. Signo y Pensamiento, v. XXI, n. 40, 2002, p. 32-41.

CASTELLS, Manuel. A sociedade em rede. 6. ed. São Paulo: Paz e Terra, 2002.

CHOI, D. et al. Rumor Propagation is amplified by Echo Chambers in Social Media. Scientific Reports, v. 10, n. 310, 2020. DOI: https://doi.org/10.1038/s41598-019-57272-3

DAHLGREN, P. M. et al. Reinforcing spirals at work? Mutual influences between selective news exposure and ideological leaning. European Journal of Communication, v. 34, n. 2, 2019. DOI: https://doi.org/10.1177/0267323119830056

DEGENNE, A.; FORSÉ, M. Introducing Social Networks. London: SAGE, 1999. DOI: https://doi.org/10.4135/9781849209373

DRUCKMAN, J. N.; LEVENDUSKY, M. S.; MCLAIN, A. No Need to Watch: How the Effects of Partisan Media Can Spread via Interpersonal Discussions. American Journal of Political Science, v. 62, n. 1, 2018. DOI: https://doi.org/10.1111/ajps.12325

DUBOIS, E.; GAFFNEY, D. The multiple facets of influence: identifying political influentials and opinion leaders on Twitter. American Behavioral Scientist, v. 58, n. 10, 2014. DOI: https://doi.org/10.1177/0002764214527088

EVANS, S. K. et al. Explicating Affordances: a conceptual framework for understanding affordances in Communication Research, Journal of Computer-Mediated Communication, v. 22, n. 1, 2017. DOI: https://doi.org/10.1111/jcc4.12180

FECHINE, Y. Uma dinâmica interacional complexa. Acta Semiotica, v. 1, n. 1, 2021. DOI: https://doi.org/10.23925/2763-700X.2021n1.54179

FERRARA, E. et al. Characterizing social media manipulation in the 2020 U.S. presidential election. First Monday, v. 25, n. 11, 2020. DOI: https://doi.org/10.5210/fm.v25i11.11431

FERRARA, E. et al. The rise of social bots. Communications of the ACM, v. 59, n. 7, p. 96-104, 2016. DOI: https://doi.org/10.1145/2818717

FREITAS, E. C.; BOAVENTURA, L. H. Cenografia e ethos: o discurso da intolerância e

polarização política no Twitter. Letras de Hoje, v. 53, n. 3, p. 449-458, 2018. DOI: https://doi.org/10.15448/1984-7726.2018.3.30796

FORELLE, M. et al. Political Bots and the Manipulation of Public Opinion in Venezuela. SSRN, 2015. DOI: https://doi.org/10.2139/ssrn.2635800

GIGER, N. et al. Policy or person? What voters want from their representatives on Twitter. Electoral Studies, v. 74, 2021. DOI: https://doi.org/10.1016/j.electstud.2021.102401

GRAHAM, T.; WRIGHT, S. Discursive equality and everyday talk online: the impact of “superparticipants”. Journal of Computer-Mediated Communication, v. 19, n. 3, 2013. DOI: https://doi.org/10.1111/jcc4.12016

HAUSTEIN, S. et al. Tweets as impact indicators: Examining the implications of automated “bot” accounts on Twitter. Journal of the Association for Information Science and Technology, v. 67, n. 1, 2015. DOI: https://doi.org/10.1002/asi.23456

HOLT, K.; FIGENSCHOU, T. U.; FRISCHLICH, L. Key Dimensions of Alternative News Media. Digital Journalism, v. 7, n. 7, 2019. DOI: https://doi.org/10.1080/21670811.2019.1625715

HUSZÁR, F. et al. Algorithmic Amplification of Politics on Twitter. Proceedings of the National Academy of Sciences, v. 119, n. 1, 2021. DOI: https://doi.org/10.1073/pnas.2025334119

JACOMY, M. et al. ForceAtlas2, a Continuous Graph Layout Algorithm for Handy Network Visualization Designed for the Gephi Software. PLOS ONE, v. 9, n. 6, 2014. DOI: https://doi.org/10.1371/journal.pone.0098679

JAKOBSON, R. Linguistics and poetics. In: SEBEOK, T. (ed.). Style in language. Cambridge, MA: MIT Press, 1960. p. 350-377.

JUST, N.; LATZER, M. Governance by algorithms: reality construction by algorithmic selection on the Internet. Media, Culture & Society, 39, v. 2, p. 238-258. 2017. DOI: https://doi.org/10.1177/0163443716643157

KADUSHIN, C. Who benefits from network analysis: ethics of social network research Social Networks, v. 27, n. 2, 2005. DOI: https://doi.org/10.1016/j.socnet.2005.01.005

KALIL, I.; SILVEIRA, S. C.; PINHEIRO, W.; KALIL, Á.; PEREIRA, J. V.; AZARIAS, W.; AMPARO, A. B. (2021). Politics of fear in Brazil: Far-right conspiracy theories on COVID-19, Global Discourse, v. 11, n. 3, p. 409-425, 2021. Disponível em: https://bristoluniversitypressdigital.com/view/journals/gd/11/3/article-p409.xml. Acesso em: 07 jun. 2022.

KALUŽA, J. Far-reaching effects of the filter bubble, the most notorious metaphor in media studies. AI & Soc, 2022. DOI: https://doi.org/10.1007/s00146-022-01399-x

KAWCHUK, G. et al. Misinformation about spinal manipulation and boosting immunity: an analysis of Twitter activity during the COVID-19 crisis. Chiropractic & Manual Therapies, v. 28, n. 34, 2020. DOI: https://doi.org/10.1186/s12998-020-00319-4

KOLLANYI, B.; HOWARD, P. N.; WOOLLEY, S. C. Bots and Automation over Twitter during the US Election. Data Memo 2016.2. Oxford: UK: Project on Computational Propaganda.

LEE, E.-J.; SOO, Y., S. When the Medium Is the Message: How Transportability Moderates the Effects of Politicians’ Twitter Communication. Communication Research, v. 41, n. 8, 2014. DOI: https://doi.org/10.1177/0093650212466407

MELLEUISH, G. Taming the Bubble. M/C Journal, v. 24, n. 1, 2021. DOI: https://doi.org/10.5204/mcj.2733

NIKOLOV, D.; FLAMMINI, A.; MENCZER, F. Right and left, partisanship predicts (asymmetric) vulnerability to misinformation. Harvard Kennedy School (HKS) Misinformation Review, v. 1, n. 7, 2021. DOI: https://doi.org/10.37016/mr-2020-55

OLTMANN, S. M.; COOPER, T. B.; PROFERES, N. How Twitter’s affordances empower dissent and information dissemination: an exploratory study of the rogue and alt government agency Twitter accounts. Government Information Quarterly, v. 37, n. 3, 2020. DOI: https://doi.org/10.1016/j.giq.2020.101475

ORDUÑA-MALEA, E.; AGUILLO, I. F. Cibermetría: midiendo el espacio red. Barcelona: Editorial UOC, 2015.

PARISER, E. The Filter Bubble: What the Internet Is Hiding from You. London: Penguin, 2012. DOI: https://doi.org/10.3139/9783446431164

PEGABOT. https://pegabot.com.br/ Acesso em: 10, set. 2021.

RAPOSO, J. F. Algoritmos, personalização e filtragem do conteúdo. In: SAAD, E. C.; SILVEIRA, S. C. (org.) Tendências em comunicação digital. São Paulo: ECA USP, 2017, 148-167.

RECUERO, R. et al. Hashtags Functions in the Protests Across Brazil. SAGE Open, 2015. DOI: https://doi.org/10.1177/2158244015586000

RECUERO, R.; ARAÚJO, R. On the rise of artificial trending topics in Twitter. In: ACM Conference on Hypertext and Social Media, 23rd, 2012, Wisconsin. Proceedings […]. Wisconsin: Association for Computing Machinery, 2012. p. 305-306.DOI: https://doi.org/10.1145/2309996.2310046

ROCHA, C.; SOLANO, E.; MEDEIROS, J. The Bolsonaro Paradox: The Public Sphere and Right-Wing Counterpublicity in Contemporary Brazil. Denmark: Springer Cham, 2021.

WANG, S. B. et al. Click traffic analysis of short URL spam on Twitter. In: IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing, 9th, 2013, Austin. Proceedings […]. Austin: ICST, 2013. p. 250-259. DOI: https://doi.org/10.4108/icst.collaboratecom.2013.254084

ROCHA, N. A.; HOLZ, M. S. A Indústria Bolsonarista de Trending Topics no Twitter: a que se deve a eficiente estratégia Pró-Governo nas Redes Sociais? In: Encontro Nacional de Ensino e Pesquisa do Campo de Públicas, 3., 2019, Rio Grande do Norte. Anais eletrônicos […] Natal, 2019. p. 2137-2147.

RUBIN, V.; CHEN, Y.; CONROY, N. Deception detection for news: three types of fakes. Proceedings of the Association for Information Science and Technology, v. 52, n. 1, 2016. DOI: https://doi.org/10.1002/pra2.2015.145052010083

SANTANA, C.; NUNES, A.; SILVA, F. The role of bots in the disinformation process in brazilian politics between 2014 and 2018. Libri, v. 71, n. 4. DOI: https://doi.org/10.1515/libri-2020-0071

SANTINI, R. M.; SALLES, D.; TUCCI, G. When machine behavior targets future voters: The use of social bots to test narratives for political campaigns in Brazil. International Journal of Communication, v. 15, 2021.

SANTOS-D’AMORIM, K.; MIRANDA, M. K. F. O. Misinformation, disinformation, and malinformation: clarifying the definitions and examples in disinfodemic times. Encontros Bibli: revista eletrônica de biblioteconomia e ciência da informação, v. 26, 2021. DOI: https://doi.org/10.5007/1518-2924.2021.e76900

SMITH, M. et al. Mapping Twitter Topic Networks: From Polarized Crowds to Community Clusters. Washington: Pew Research Center, 2014.

STUKAL, D. et al. Detecting Bots on Russian Political Twitter. Big Data, v. 5, n. 4, p. 310-324, 2017. DOI: https://doi.org/10.1089/big.2017.0038

STATISTA. Leading countries based on number of Twitter users as of October 2021. 2021. Disponível em: https://www.statista.com/statistics/242606/number-of-active-twitter-users-in-selected-countries/. Acesso em: 09 março 2022.

STRUDWICKE, I.; GRANT, W. J. 2020. #JunkScience: Investigating pseudoscience disinformation in the Russian Internet Research Agency tweets. Public Understanding of Science, v. 29, n. 5, 2020. DOI: https://doi.org/10.1177/0963662520935071

SUNSTEIN, C. #Republic: Divided Democracy in the Age of Social Media. Princeton: Princeton University Press, 2018. DOI: https://doi.org/10.1515/9781400884711

SUNSTEIN, C. Echo Chambers. Princeton: Princeton University Press, 2001.

TSFATI, Y. et al. Causes and consequences of mainstream media dissemination of fake news: literature review and synthesis, Annals of the International Communication Association, v. 44, n. 2, p. 157-173, 2020. https://doi.org/10.1080/23808985.2020.1759443

TUBARO, P. et al. Social network analysis: New ethical approaches through collective reflexivity. Introduction to the special issue of Social Networks. Social Networks, v. 67, 2021. DOI: https://doi.org/10.1016/j.socnet.2020.12.001

VIEGAS, F. B.; SMITH, M. A. Newsgroup crowds and author lines: visualizing the activity of individuals in conversational cyberspaces. Big Island, HI: IEEE, 2004. DOI: https://doi.org/10.1109/HICSS.2004.1265288

WANG, R.; LIU, W.; GAO, S. Hashtags and information virality in networked social movement: examining hashtag co-occurrence patterns. Online Information Review, v. 40, n. 7, 2016. DOI: https://doi.org/10.4108/icst.collaboratecom.2013.254084

WANG, S. B. et al. Click traffic analysis of short URL spam on Twitter. In: IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing, 9th, 2013, Austin. Proceedings […]. Austin: ICST, 2013. p. 250-259. DOI: https://doi.org/10.4108/icst.collaboratecom.2013.254084

WASSERMAN, S.; FAUST, K. Social Network Analysis: Methods and Applications. Cambridge: Cambridge University Press, 1994. DOI: https://doi.org/10.1017/CBO9780511815478

WEEKS, B. Why Partisan News—Not Just Fake News—Promotes Political Misperceptions. Learn Speak Act. Michigan, 2017. Disponível em: https://sites.lsa.umich.edu/learn-speak-act/2017/04/12/why-partisan-news-not-just-fake-news-promotes-political-misperceptions/. Acesso em: 20. out. 2021.

WELSER, H. T. et al. Visualizing the signatures of social roles in online discussion groups. Journal of Social Structure, v. 8, n. 2, 2007.

WINTOUR, Patrick. Brazil: warning Bolsonaro may be planning military coup amid rallies. The Guardian, 6 set. 2021. https://www.theguardian.com/world/2021/sep/06/brazil-warning-bolsonaro-may-be-planning-military-coup-amid-rallies

YANG, K-C. et al. Arming the public with artificial intelligence to counter social bots. Human Behavior & Emerging Technologies, v. 1, n. 1, 2019. DOI: https://doi.org/10.1002/hbe2.115

ZAGO, G.; RECUERO, R.; SOARES, F. Political fandoms and superparticipants in political conversations on twitter. AoIR Selected Papers of Internet Research, v. 18, n. 1, 2018. DOI: ttps://doi.org/10.5210/spir.v2018i0.10514