INTERACTION FROM THE MESSAGES ON CORRUPTION PUBLISHED ON TWITTER BY THE PRECANDIDATES TO THE PRESIDENCY OF COLOMBIA (2018-2022)
DOI:
https://doi.org/10.21501/22161201.2618Keywords:
Interaction, Twitter, Corruption, Precandidates, Social networks, Elections.Abstract
Social networks are increasingly used by politicians in campaign to present their proposals to the electorate and show their positions in front of different social problems. Through a content analysis, this study investigated how the interaction is based on the messages about corruption published on Twitter by the pre-candidates for the presidency of Colombia (2018-2022). NodeXL Pro software was used for the selection of messages. This tool was also used to analyze the sentiment of the tweets. The results found indicate that when referring to corruption, candidates use Twitter more as a means to disseminate opinions than to interact with other social actors. When they interact, they do so especially with journalists and the media and to a lesser extent with institutions charged with punishing corrupt actors. Likewise, opposition candidates to the government publish more frequently about corruption and Twitter users are more likely to interact with messages loaded with negative sentiment and where other agents are accused of incurring possible corruption cases.
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Ahmed, S., Jaidka, K. & Cho, J. (2016). The Indian Elections of 2014 on Twitter: A Comparison of Campaign Strategies of Political Parties. Telematics and Informatics, 33(4), 1071-1087. doi: 10.1016/j.tele.2016.03.002.
Ángel, A. (2013). Retóricas sobre crisis de corrupción en organizaciones del Eje Cafetero. Colombia: Universidad de Manizales.
Ausserhofer, J. & Maireder, A. (2013). National Politics on Twitter. Information, Communication and Society, 16(3), 291-314. doi: https://doi.org/10.1080/1369118X.2012.756050.
Banica, L., y Hagiu, A. (2016). Using big data analytics to improve decision-making in apparel supply chains. Information Systems for the Fashion and Apparel Industry, 1, 63-95.
Ben-Ali, M. & Gasmi, A. (2017). Does ICT Diffusion Matter for Corruption? An Economic Development Perspective. Telematics and Informatics, 34(8), 1145-1453. doi: 10.1016/j.tele.2017.06.008.
Berelson, B. & Steiner, G. (1964). Human Behavior: an Inventory of Scientific Findings. Oxford, England: Harcourt, Brace & World.
Berger, P. y Luckmann, T. (1993). La construcción social de la realidad. Buenos Aires: Amorrortu.
Bilal, M., Israr, H., Shahid, M. & Khan, A. (2016). Sentiment Classification of Roman Urdu Opinions Using Naïve Bayesian, Decision Tree and KNN Classification Techniques. Journal of King Saud University - Computer and Information Sciences, 28(3), 330-344.
Blumer, H. 1968. Symbolic Interactionism. Perspective and Method. New Jersey: Prentice Hall.
Bode, L., & Dalrymple, K. (2014). Politics in 140 Characters or Less: Campaign Communication, Network Interaction, and Political Participation on Twitter. Journal of Political Marketing, 15(4), 311-332. doi: 10.1080/15377857.2014.959686.
Brei, Z. (1996). Corrupção: dificuldades para definição e para um consenso. Revista de Administração Pública, 30(1), 64-77.
Brown, D., Touchton, M. & Whitford, A. (2011). Political Polarization as a Constraint on Corruption: A Cross-national Comparison. World Development, 39(9), 1516-1529. doi:10.1016/j.worlddev.2011.02.006.
Bruns, A., Harrigton, S. & Hihgfield, T. (2013). Twitter as a Technology for Audiencing and Fandom. Information, Communication and Society, 16(3), 315-339. doi: https://doi.org/10.1080/1369118X.2012.756053.
Bulte, E., Damania, R. & López, R. (2007). On the Gains of Committing to Inefficiency: Corruption, Deforestation and Low Land Productivity in Latin America. Journal of Environmental Economics and Management, 54(3), 277-295. doi.org/10.1016/j.jeem.2007.05.002.
Burton, S., y Soboleva, A. (2011). Interactive or Reactive? Marketing with Twitter. Journal of Campaign Strategies of Political Parties. Telematics and Informatics, 33(4), 1071-1087. doi: 10.1016/j.tele.2016.03.002.
Castells, M. (2006). La sociedad red. Madrid: Alianza Editorial.
Casalino, I., Ingunza, M., Jiménez, A., Véliz, M. y Yap, L. (2017). Significado y uso de los emojis de WhatsApp dentro de situaciones comunicativas interculturales, Procesos Interculturales, (pp. 47-69). Lima, Perú: Siglo XXI Editores.
Castañeda, M. (2016). An Inquiry on Public Corruption and its Determinants. Revista Mexicana de Ciencias Políticas y Sociales. Vol, 61, pp. 103-135
Chibnall, S. & Saunders, P. (1977). Worlds Apart: Notes on the Social Reality of Corruption. The British Journal of Sociology, 28(2), 138-154. doi: 10.2307/590207.
Coesemans, R. & De Cock, B. (2017). Self-reference of Politicians on Twitter: Strategies to Adapt to 140 Characters. Journal of Pragmatics, 116, 37-50. doi:10.1016/j.pragma.2016.12.005.
Cogburn, D. y Espinoza, F. (2011). From Networked Nominee to Networked Nation: Examining the Impact of Web 2.0 and Social Media on Political Participation and Civic Engagement in the 2008 Obama Campaign. Journal of Political Marjketing, 10(2), 199-213. doi:10.1080/15377857.2011.540224.
Colliander, J., Marder, B., Lid, L., Madestam, J., Modig, E. & Sagfossen, S. (2017). The Social Media Balancing Act: Testing the Use of a Balanced Self-presentation Strategy for Politicians Using Twitter. Computers in Human Behavior, 74, 277-285.
D'Adamo, O; García, V., y Kievsky, T. (2015). Comunicación política y redes sociales: análisis de las campañas para las elecciones legislativas de 2013 en la ciudad de Buenos Aires. Revista Mexicana de Opinión Pública, 19, 107-126. doi: 10.1016/j.rmop.2015.02.002.
Dahlgren, P. (2005). The Internet, Public Spheres, and Political Communication: Dispersion and Deliberation, Political Communication, 22(2), 147-162. doi: 10.1080/10584600590933160.
Dobson, S. & Ramlogan C. (2012). Why is Corruption Less Harmful to Income Inequality in Latin America? World Development, 40(8), 1534-1545. doi:10.1016/j.worlddev.2012.04.015.
Dubois, E. & Gaffney, D. (2014). The Multiple Facets of Influence: Identifying Political Influentials and Opinion Leader on Twitter. American Behavioral Scientist, 58(10), 1260–1277. doi: 10.1177/0002764214527088
El Tiempo. (2 de marzo de 2017). Corrupción es el principal problema del país en este momento: Gallup. Recuperado de http://www.eltiempo.com/politica/gobierno/corrupcion-es-el-principal-problema-de-colombia-segun-gallup-63194
Enli, G. & Skogerbø, E. (2013). Personalized Campaigns in Party-centred Politics: Twitter and Facebook as Arenas for Political Communication. Information Communication and Society, 16(5), 757-774. doi:10.1080/1369118X.2013.782330.
Evans, H., Córdobva, V. & Sipole. (2014). Twitter Style: An Analysis of How House Candidates Used Twitter in Their 2012 Campaigns. Political Science and Politics, 47(2), 454-462.
Farizah, N., Xiaojun, W. & Humphrey, B. (2017). Exploring the Effect of User Engagement in online Brand Communities: Evidence from Twitter. Computers in Human Behavior, 72, 321-338. doi: https://doi.org/10.1016/j.chb.2017.03.005.
Fischer, E., y Reuber, R. (2011). Social interaction via new social media: (How) can interactions on Twitter affect effectual thinking and behavior? Journal of Business Venturing, 26(1), 1-18. doi: 10.1016/j.jbusvent.2010.09.002
Gallegos, C., Gómez, C., Imaz, C. y Paredes, Y. (2005). Pierre Bourdieu. Campos de conocimiento: teoría social, educación y cultura. México: Centro de Investigaciones Humanísticas, Universidad Autónoma de Chiapas.
Galindo, J. (2004). Hacia una comunicología posible en México. Notas preliminares para un programa de investigación. Anuario de Investigación de la Comunicación (pp. 51-72). México: Universidad Intercontinental.
Gaviria, A. (2002). Assessing the Effects of Corruption and Crime on Firm Performance: Evidence from Latin America. Emerging Markets Review, 3(3), 245-268. doi: https://doi.org/10.1016/S1566-0141(02)00024-9.
Glaeser, E. & Saks, R. (2006). Corruption in America. Journal of Public Economics, 90(6), 1053-1072. doi: 10.1016/j.jpubeco.2005.08.007.
Godinez, J. y Liu, L. (2015). Corruption Distance and FDI Flows into Latin America. International Business Review, 24(1), 33-42. doi.org/10.1016/j.ibusrev.2014.05.006
Graham, T., Broersma, M., Hazelhoff, K. & van 't Haar, G. (2013). Between Broadcasting Political Messages and Interacting With Voters. The Use of Twitter During the 2010 UK General Election Campaign. Communication and Society, 16(5), 692-716. doi:10.1080/1369118X.2013.785581.
Graham, T., Jackson, D. & Broersma, M. (2014). New Platform, Old Habits? Candidates’ Use of Twitter During the 2010 British and Dutch General Election Campaigns. New Media & Society, 18(5), 765-783. doi:10.1177/ 1461444814546728.
Grant, W., Moon, B. & Grant, B. (2010). Digital Dialogue? Australian Politicians' Use of the Social Network Tool Twitter. Australian Journal of Political Science, 45(4), 579-604.
Halberstam, Y. & Knight, B. (2016). Homophily, Group Size, and the Diffusion of Political Information in Social Networks: Evidence from Twitter. Journal of Public Economics, 143, 73-88. doi: 10.3386/w20681.
Hoffman, D. & Novak, T. (1996). Marketing in Hypermedia Computer-Mediated Environments: Conceptual Foundations. Journal of Marketing, 60(3), 50-68.
Hong, S. & Nadler, D. (2012). Which candidates do the public discuss online in an election campaign?: The Use of Social Media by 2012 Presidential Candidates and its Impact on Candidate Salience. Government Information Quarterly, 29(4), 455-461.
Hornbæk, K. & Oulasvirta, A. (2017). What is Interaction? Interaction Design. doi:10.1145/3025453.3025765.
Huberty, M. (2015). Can we Vote with our Tweet? On the Perennial Difficulty of Election Forecasting with Social Media. International Journal of Forecasting, 31(3), 992-1007.
Kim, J., y Park, H. (2014). Food policy in cyberspace: A webometric analysis of national food clusters in South Korea. Government Information Quarterly, 31(3), 443-453. doi: 10.1016/j.giq.2014.01.013
Jackson, L. & Valentine, G. (2014). Emotion and Politics in a Mediated Public Sphere: Questioning Democracy, Responsibility and Ethics in a Computer Mediated World. Geoforum, 52, 193-202. doi:10.1016/j.geoforum.2014.01.008.
Jensen, J. (1998). Interactivity: Tracking a New Concept in Media and Communication Studie, Nordicom Review, 1, 185-204. Recuperado de: http://www.nordicom.gu.se/en/tidskrifter/nordicom-review-11998/interactivity-tracking-new-concept-media-and-communication-studies
Jha, C. & Sarangi, S. (2017). Does Social Media Reduce Corruption? Information Economics and Policy, 39, 60-71. do:10.1016/j.infoecopol.2017.04.001.
Jung, Y., Shin, D. & Hyun, J. (2016). High/low Reputation Companies' Dialogic Communication Activities and Semantic Networks on Facebook: A Comparative Study. Technological Forecasting and Social Change, 110, 78-92. doi: https://doi.org/10.1016/j.techfore.2016.05.003.
Kanyam, D., Kostandini, G. & Ferreira, S. (2017). The Mobile Phone Revolution: Have Mobile Phones and the Internet Reduced. World Development, 99, 271-284. doi:10.1016/j.worlddev.2017.05.022.
Kreiss, D. (2014). Seizing the Moment: The Presidential Campaigns’ Use of Twitter During the 2012 Electoral Cycle. New Media and Society, 18(8), 1473-1490.
Kruikemeier, S. (2014). How Political Candidates use Twitter and the Impact on Votes. Computers in Human Behavior, 34, 131-139.
Larsson, A. & Moe, H. (2011). Studying Political Microblogging: Twitter Users in the 2010 Swedish Election Campaign. New Media and Society, 14(5), 729-747.
Lasorsa, D., Lewis, S. & Holton, A. Standardization of Twitter: Practice of Journalism in an Emerging Communication Space. Journalism Studies, 13(1), pp. 19-36.
Lightman, S., Dzogang, F. & Cristianini, N. (2017). Circadian Mood Variations in Twitter Content. Brain and Neuroscience Advances, 1. doi: 10.1177/2398212817744501.
Lilleker, D., Jackson, N. (2011). Microblogging, Constituency Service and Impression Management: UK MPs and the Use of Twitter. The Journal of Legislative Studies, 17(1), 86-105. doi: 10.1080/13572334.2011.545181
Lui, G., Odell, J., Whipple, E., Ralston, R., Caroll, A. y Downs, S. (2015). Data visualization for truth maintenance in clinical decision support systems. International Journal of Pediatrics and Adolescent Medicine, 2(2), 64-69. doi: 10.1016/j.ijpam.2015.06.001
López, W., Roa, D., Correa, A., Pérez, C. y Pineda, C. (2016). El rol de la filiación política en las creencias y discursos legitimadores de la corrupción. Psychosocial Intervention, 25(3), 179-186. doi:10.1016/j.psi.2016.07.001.
Marc, E., y Picard, D. (1992). La interacción social. Barcelona: Paidós.
Martimort, D. & Straub, S. (2009). Infrastructure Privatization and Changes in Corruption Patterns: The Roots of Public Discontent. Journal of Development Economics, 90(1), 69-84. doi.org/10.1016/j.jdeveco.2008.08.002.
Menard, A. & Weill, L. (2016). Understanding the Link between Aid and Corruption: A Causality Analysis. Economic Systems, 40(2), 260-272. doi:10.1016/j.ecosys.2016.01.001.
Miquel, S. Alonso, L. y Marcos S. (2017). Buscando la interacción. Partidos y candidatos en Twitter durante las elecciones generales de 2015. Prisma Social, (18), 34-54. Recuperado de http://www.redalyc.org/articulo.oa?id=353751820002
Moya, M., y Herrera, S. (2016). Cómo medir el potencial persuasivo en Twitter: propuesta metodológica. Palabra Clave 19(3), 838-867. doi:10.5294/pacla.2016.19.3.7.
Nass De Ledo, I. (2011). Las redes sociales. Revista Venezolana de Oncología, 23(3), 133.
Nielsen, R. (2003). Corruption Networks and Corruption for Ethical Reform. Journal of Business Ethics, 42(2), 125-149. doi:10.1023/A:1021969204875.
O’Sullivan, T. (1997). Conceptos clave en comunicación y estudios culturales. Buenos Aires: Amorrortu.
Olorunnisola, A. & Martin, B. (2013). Influences of Media on Social Movements: Problematizing Hyperbolic Inferences about Impacts. Telematics & Informatics, 30, 275-288. doi:10.1016/j.tele.2012.02.005.
Paltoglou, G. & Thelwall, M. (2010). A Study of Information Retrieval Weighting Schemes for Sentiment Analysis. Annual Meeting of the Association for Computational Linguistics 48, 1386-1395.
Paunov, C. (2016). Corruption’s Asymmetric Impacts on Firm Innovation. Journal of Development Economics, 118, 216-231. doi10.1016/j.jdeveco.2015.07.006.
Pérez, T. y da Silva, G. (2015). Corrupción en la función pública: un estudio sobre correlaciones entre corrupción, calidad de la democracia, gobernanza, desigualdad de renta y desempleo en el mundo (2008-2012). Revista Colombiana de Ciencias Sociales, 6(1), 15-33.
Quiroga, M. (2009). Corrupción y democracia: América Latina en perspectiva comparada. Gestión y Política Pública, 18(2), 205-252.
Rafaeli, S. (1988). Interactivity: From New Media to Communication. En J. M. Hawkins Wiemann, & S. Pingree (Eds.), Advancing Communication Science: Merging Mass and Interpersonal Processes, Sage Publications (pp. 110-134). Beverly Hills, CA.
Reed, M. (2015). Social Network Influence on Consistent Choice. Journal of Choice Modelling, 17, 28-38. doi:10.1016/j.jocm.2015.12.004.
Revista Semana. (28 de septiembre de 2017). Gran encuesta: Sergio Fajardo saca ventaja. Recuperado de http://www.semana.com/nacion/articulo/sergio-fajardo-lider-gran-encuesta-septiembre-2017/541935
Ribalko, S. & Seltzer, T. (2010). Dialogic Communication in 140 Characters or less: How Fortune500 Companies Engage Stakeholders Using Twitter. Public Relations, 36(4), 5040-5052.
Ritonga, R., Murwani, E., Nurochim, B. & Gunawan, K. (2017). The Social Media Use for Presidential Candidates Campaign and Political Awareness of Young Voters in Indonesia. International Journal of Control and Automation, 10(9), 11-122. doi: 10.14257/ijca.2017.10.9.10.
Rizo, M. (2005). Comunicología, psicología social y sociología fenomenológica. Exploraciones teóricas para la conceptualización de la interacción y la comunicación. Anuario de la Investigación de la Comunicación (pp. 105-127). México: CONEICC.
Roa, M. C. (30 de agosto de 2017). La corrupción es el principal problema del país, según encuesta Gallup. Blu Radio. Recuperado de https://www.bluradio.com/nacion/la-corrupcion-es-el-principal-problema-del-pais-segun-encuesta-gallup-152079
Rosas, G. & Manzetti, L. (2015). Reassessing the Trade-off Hypothesis: How Misery Drives the Corruption Effect on Presidential Approval. Electoral Studies, 39, 26-38. doi.org/10.1016/j.electstud.2015.03.002.
Saha, S., Gounder, R. & Su, J. J. (2009). The Interaction Effect of Economic Freedom and Democracy on Corruption: A Panel Cross-country Analysis. Economics Letters, 105(2), 173-176. doi:10.1016/j.econlet.2009.07.010.
Santoveña, S. (2015). Cibersociedad y debate público en 140 caracteres: #paro y #corrupción. Athenea Digital, 15(3), 47-84. doi:10.5565/rev/athenea.1416.
Seker, M. & Yang, J. (2014). Bribery Solicitations and Firm Performance in the Latin America and Caribbean Region. Journal of Comparative Economics, 42(1), 246-264. doi.org/10.1016/j.jce.2013.05.004.
Seligson, M. (2006). The Measurement and Impact of Corruption Victimization: Survey Evidence from Latin America. World Development, 34(2), 381-404. doi:10.1016/j.worlddev.2005.03.012.
Semana. (28 de septiembre de 2017). Gran encuesta: Sergio Fajardo saca ventaja.
Recuperado de: https://www.semana.com/nacion/articulo/sergio-fajardo-lider
gran-encuesta-septiembre-2017/541935.
Small, T. (2011). What the hashtag? A content analysis of Canadian politics on Twitter. Information, Communication & Society, 14, 872-895.
Solimano, A., Tanzi, V. y Del Solar, F. (2008). Las termitas del Estado: ensayos sobre corrupción, transparencia y desarrollo. Santiago de Chile: Fondo de Cultura Económica.
Stlieglitz, S. & Dank-Xuan, L. (2013). Emotions and Information Diffusion in Social Media-Sentiment of Microblogs and Sharing Behavior. Journal of Management Information Systems, 29(4), 217-248.
Stromer, J. & Foot, K. (2002). Citizen Perceptions of Online Interactivity and Implications for Political Campaign Communication. Journal of Computer Mediate Communication, 8(1). doi: 10.1111/j.1083-6101.2002.tb00161.x.
Swaleheen, M. (2008). Corruption and Saving in a Panel of Countries. Journal of Macroeconomics, 30(3), 1285-1301. doi: 10.1016/j.jmacro.2007.05.002.
Toledano, B. (27 de julio de 2017). El número de usuarios que ha sumado Twitter en el último trimestre asciende a cero. El Mundo. Recuperado de http://www.elmundo.es/tecnologia/2017/07/27/5979dc3146163fc6568b4674.html
Transparencia por Colombia. (2016). Índice de transparencia de las entidades públicas, resultados 2015-2016. Recuperado de http://transparenciacolombia.org.co/indice-de-transparencia-de-las-entidades-publicos-enero-de-2015-a-abril-de-2016/
Transparencia Internacional (2017). Índice de percepción de la corrupción, resultados 2016. Recuperado de https://www.transparency.org/news/feature/corruption_perceptions_index_2016
Treisman, D. (2000). The Causes of Corruption: a Cross-national Study. Journal of Public Economics, 76, 399-457. doi.org/10.1016/S0047-.
Tumasjan, A., Sprenger, T., Sandner, P. & Welpe, I. (2010). Predicting Elections with Twitter: What 140 Characters Reveal about Political Sentiment. Proceedings of the Fourth International AAAI Conference on Weblogs and Social Media (pp. 178-185). doi: 10.1074/jbc.M501708200.
Turner, B. (1990). The Two Faces of Sociology: Global or National? Theory, Culture and Society, 7(2), 343-358.
Unankard, S., Li, X., Sharaf, M. & Zhong, J. (2014). Predicting Elections from Social Networks Based on Sub-event Detection and Sentiment Analysis. Lecture Notes in Computer Science, 87, 1-16.
Vargas, J. (2009). The Multiple faces of Corruption: Typology, Forms and Levels. Contemporary Legal & Economic, 3, 269-290.
Vergeer, M., Hermans, L. & Sams, S. (2011). Online Social Networks and Micro-blogging in Political Campaigning the Exploration of a New Campaign Tool and a New Campaign Style. Party politics, 19(3), 477-501.
Vidal, L., Ares, G., Kam, K. & Jaeger, G. (2016). Can Emoji Be Used as a Direct Method to Measure Emotional Associations to Food Names? Preliminary Investigations with Consumers in USA and China. Food Quality and Preference, 56, 38-48.
Vobic, I., Maksuti, A. & Dezelan, T. (2016). Who Leads the Twitter Tango? Digital Journalism, 5(9), pp. 1134-1154. doi.org/10.1080/21670811.2016.1259002.
White, R. (2013). What Counts as Corruption? Social Research: An International Quarterly, 80(4), 1033-1056.
Wong, M. (2016). Public Spending, Corruption, and Income Inequality: A Comparative Analysis of Asia and Latin America. International Political Science Review, 38(3), 1-18. doi:10.1177/0192512116642617.
Zhao, Q., Erdogdu, M., He, H., Rajaraman, A. & Leskovec, J. (2015). SEISMIC: A self-Exciting Point Process Model for Predicting Tweet Popularity. En International Conference on Knowledge Discovery and Data Mining (pp. 1513-1522). doi: 10.1145/2783258.2783401.
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