The ideology of media. Measuring the political leaning of Spanish news media through Twitter users’ interactions
Article Sidebar
348)
Main Article Content
Authors
Abstract
1240
The news media have a strong influence on people’s perception of reality. But despite claims to objectivity, media organizations are, in general, politically biased (Patterson & Donsbach, 1996; Gaebler, 2017). The link between news media outlets and political organizations has been a critical question in political science and communication studies. To assess the closeness between the news media and particular political organizations, scholars have used different methods such as content analysis, undertaking surveys or adopting a political economy view. With the advent of social networks, new sources of data are now available to measure the relationship between media organizations and parties. Assuming that users coherently retweet political and news information (Wong, Tan, Sen & Chiang, 2016), and drawing on the retweet overlap network (RON) method (Guerrero-Solé, 2017), this research uses people’s perceived ideology of Spanish political parties (CIS, 2020) to propose a measure of the ideology of news media in Spain. Results show that scores align with the result of previous research on the ideology of the news media (Ceia, 2020). We also find that media outlets are, in general, politically polarized with two groups or clusters of news media being close to the left-wing parties UP and PSOE, and the other to the right-wing and far-right parties Cs, PP, and Vox. This research also underlines the media’s ideological stability over time.
Keywords
References
An, J., Cha, M., Gummadi, K., Crowcroft, J. & Quercia, D. (2012). Visualizing media bias through Twitter. In Proceedings of the International AAAI Conference on Web and Social Media (pp. 2-5). Dublin: AAAI.
Barberá, P., Jost, J. T., Nagler, J., Tucker, J. A. & Bonneau, R. (2015). Tweeting From Left to Right: Is Online Political Communication More Than an Echo Chamber?, Psychological Science, 26(10), 1531–1542. https://www.doi.org/10.1177/0956797615594620
Baumgartner, F. R. & Chaqués Bonafont, L. (2015). All news is bad news: Newspaper coverage of political parties in Spain. Political Communication, 32(2), 268-291. https://www.doi.org/10.1080/10584609.2014.919974
Bosi, L., Lavizzari, A. & Voli, S. (2020). Representation of Youth in the Public Debate in Greece, Italy, and Spain: Does the Political Leaning of Newspapers Have Any Effect?, American Behavioral Scientist, 64(5), 620-637. https://www.doi.org/10.1177/0002764219885437
Bruns, A. & Highfield, T. (2013). Political networks on Twitter: tweeting the Queensland state election. Information, Communication & Society, 16, 667-691. https://www.doi.org/10.1080/1369118X.2013.782328.
Ceia, V. (2020). Digital Ecosystems of Ideology: Linked Media as Rhetoric in Spanish Political Tweets. Social Media and Society, 6(2). https://www.doi.org/10.1177/2056305120926630
Cohen, R. & Ruths, D. (2013). Classifying political orientation on Twitter: It’s not easy! In Proceedings of the 7th International Conference on Weblogs and Social Media (pp. 91-99). Cambridge, MA: ICWSM 2013.
Conover, M. D., Gonçalves, B., Ratkiewicz, J., Flammini, A. & Menczer, F. (2011). Predicting the political alignment of twitter users. In Proceedings - 2011 IEEE International Conference on Privacy, Security, Risk and Trust and IEEE International Conference on Social Computing, PASSAT/SocialCom 2011 (pp. 192-199). https://www.doi.org/10.1109/PASSAT/SocialCom.2011.34
D’Allesio, D. & Allen, M. (2000). Media bias in presidential elections: a meta analysis. Journal of Communication, 50(4), 133-156. https://www.doi.org/10.1111/j.1460-2466.2000.tb02866.x
David, E., Zhitomirsky-Geffet, M., Koppel, M. & Uzan, H. (2016). Utilizing Facebook pages of the political parties to automatically predict the political orientation of Facebook users. Online Information Review, 40(5), 610-623. https://www.doi.org/ 10.1108/OIR-09-2015-0308
Eady, G., Nagler, J., Guess, A., Zilinsky, J. & Tucker, J. A. (2019). How Many People Live in Political Bubbles on Social Media? Evidence From Linked Survey and Twitter Data. SAGE Open. https://www.doi.org/10.1177/2158244019832705
El Español (19 October 2020). El Español logra su récord con 23,3 millones de usuarios: supera a El País y ABC y se queda a un 5 % de El Mundo. Retrieved from https://www.elespanol.com/invertia/medios/20201019/espanol-record-millones-usuarios-pais-abc-mundo/529447647_0.html
Falck, F., Marstaller, J., Stoehr, N., Maucher, S., Ren, J., Thalhammer, A. & Studer, R. (2020). Measuring Proximity Between Newspapers and Political Parties: The Sentiment Political Compass. Policy and Internet, 12(3), 367-399. https://www.doi.org/10.1002/poi3.222
Gautam, G. & Yadav, D. (2014). Sentiment Analysis of Twitter Data Using Machine Learning Approaches and Semantic Analysis. In 2014 7th International Conference on Contemporary Computing (pp. 437-442). IEEE Conference Location: Noida.
Gentzkow, M., Petek, N., Shapiro, J. M. & Sinkinson, M. (2015). Do newspapers serve the state? Incumbent party influence on the US press 1869-1928. Journal of the European Economic Association, 13(1), 29-61. https://www.doi.org/ 10.1111/jeea.12119
Golbeck, J. & Hansen, D. (2014). A Method for Computing Political Preference Among Twitter Followers. Social Networks, 36, 177-184. https://www.doi.org/10.1016/j.socnet.2013.07.004
Guerrero-Solé, F. & López-González, H. (2019). Government Formation and Political Discussions on Twitter. An Extended Model for Quantifying Political Distances in Multiparty Democracies. Social Science Computer Review, 37, 3-21. https://www.doi.org/10.1177/0894439317744163
Guerrero-Solé, F. (2018). Interactive Behavior in Political Discussions on Twitter: Politicians, Media, and Citizens’ Patterns of Interaction in the 2015 and 2016 Electoral Campaigns in Spain. Social Media + Society, 4(4), 1-16. https://www.doi.org/10.1177/2056305118808776
Guerrero-Solé, F. (2017). Community detection in political discussions on Twitter. An application of the Retweet Overlap Network method to the Catalan process towards independence. Social Science Computer Review, 35(2), 244-261. https://www.doi.org/10.1177/0894439315617254
Guerrero-Solé, F., Corominas-Murtra, B. & López-González, H. (2014). Pacts with Twitter. Predicting voters’ indecision and preferences for coalitions in multiparty systems. Information, Communication & Society, 17(10), 1280–1297. https://www.doi.org/10.1080/1369118X.2014.920040
Gyftopoulos, S., Drosatos, G., Stamatelatos, G. & Efraimidis, P. S. (2020). A Twitter-based approach of news media impartiality in multipartite political scenes. Social Network Analysis and Mining, 10(1). https://www.doi.org/10.1007/s13278-020-00642-x
Hallin, D. C. & Mancini, P. (2004). Comparing media systems: Three models of media and politics. New York, NY: Cambridge University Press.
Haselmayer, M., Wagner, M. & Meyer, T. M. (2017). Partisan Bias in Message Selection: Media Gatekeeping of Party Press Releases. Political Communication, 34(3), 367-384.
Kim, M. & Park, H. W. (2012). Measuring Twitter-based political participation and deliberation in the South Korean context by using social network and Triple Helix indicators. Scientometrics, 90, 121-140. https://www.doi.org/10.1007/s11192-011-0508-5
Kosinski, M., Stillwell, D. & Graepel, T. (2013). Private traits and attributes are predictable from digital records of human behavior. Proceedings of the National Academy of Sciences of the United States of America, 110(15), 5802-5805. https://www.doi.org/10.1073/pnas.1218772110
Kosinski, M., Wang, Y., Lakkaraju, H. & Leskovec, J. (2016). Mining big data to extract patterns and predict real-life outcomes. Psychological Methods, 21(4), 493-506. https://www.doi.org/10.1037/met0000105
Labio, A. & Pineda, A. (2016). Leftward shift, media change? Ideology and politics in Spanish online-only newspapers after the 15-M movement. International Journal of Communication, 10, 2661-2682. https://www.doi.org/1932–8036/20160005
Llorens, C. (2010). Spain’s media concentration policy: A patchwork crucial to the understanding of the Spanish media system. International Journal of Communication, 4, 844-864.
Markowetz, A., Błaszkiewicz, K., Montag, C., Switala, C. & Schlaepfer, T. E. (2014). Psycho-Informatics: Big Data shaping modern psychometrics. Medical Hypotheses, 82, 405-411. https://www.doi.org/10.1016/j.mehy.2013.11.030
Mas Manchón, L. & Guerrero-Solé, F. (2019). The use of hashtags as a political branding strategy. Revista internacional de relaciones públicas, 17(9), 5-24. https://www.doi.org/10.5783/ RIRP-17-2019-02-05-24
Obschonka, M., Lee, N., Rodríguez-Pose, A., Eichstaedt, J. C. & Ebert, T. (2020). Big data methods, social media, and the psychology of entrepreneurial regions: capturing cross-county personality traits and their impact on entrepreneurship in the USA. Small Business Economics, 55, 567-588. https://www.doi.org/10.1007/s11187-019-00204-2
Park, S., Ko, M., Kim, J., Liu, Y. & Liu, Song, J. (2011). The politics of comments: Predicting political orientation of news stories with commenters’ sentiment patterns. In Proc. ACM Conf. Comput. Supported Cooperative Work (pp. 113–122). Hangzhou, China.
Park, G., Andrew Schwartz, H., Eichstaedt, J. C., Kern, M. L., Kosinski, M., Stillwell, D. J., Ungar, L. H. & Seligman, M. E. P. (2015). Automatic personality assessment through social media language. Journal of Personality and Social Psychology, 108(6), 934-952. https://www.doi.org/10.1037/pspp0000020
Patterson, T. E. & Donsbach, W. (1996). News decisions: Journalists as partisan actors. Political Communication, 13, 455-468. https://www.doi.org/10.1080/10584609.1996.9963131
Pew Research (2018). News Media and Political Attitudes in Spain. Retrieved from https://www.pewresearch.org/global/fact-sheet/news-media-and-political-attitudes-in-spain/
Renoust, B., Cheung, G. & Satoh, S. (2017). Estimating political leanings from mass media via graph-signal restoration with negative edges. In Proceedings - IEEE International Conference on Multimedia and Expo (pp. 1009-1014). Hong Kong: IEEE. https://www.doi.org/10.1109/ICME.2017.8019302
Ribeiro, F. N., Henrique, L., Benevenuto, F., Chakraborty, A., Kulshrestha, J., Babaei, M. & Gummadi. K. P. (2018). Media bias monitor: Quantifying biases of social media news outlets at large-scale. In Proceedings of the 12th International AAAI Conference on Web and Social Media, ICWSM ‘18 (pp. 290-299). Palo Alto, CA: AAAI.
Sampedro, V. & Seoane Pérez, F. (2008). The 2008 Spanish general elections: “Antagonistic bipolarization” geared by presidential debates, partisanship, and media interest. The International Journal of Press/Politics, 13(3), 336-344.
Schena, J., Almiron, N. & Pineda, A. (2018). Mapping press ideology. A methodological proposal to systematise the analysis of political ideologies in newspapers. Observatorio, 12(3), 17-47. https://www.doi.org/10.15847/obsobs12320181227
Stefanov, P., Darwish, K., Atanasov, A. & Nakov, P. (2020). Predicting the Topical Stance and Political Leaning of Media using Tweets. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (pp. 527–537). ACL. https://www.doi.org/10.18653/v1/2020.acl-main.50
Tay, L., Woo, S. E., Hickman, L. & Saef, R. M. (2020). Psychometric and Validity Issues in Machine Learning Approaches to Personality Assessment: A Focus on Social Media Text Mining. European Journal of Personality, 34, 826-844. https://www.doi.org/10.1002/per.2290
Van Camp, K. (2018). Issue ownership as a determinant of political parties’ media coverage. Communications: The European Journal of Communication Research, 43(1), 25-45. https://www.doi.org/10.1515/commun-2017-0029
van Dijk, T. A. (1995). Discourse semantics and ideology. Discourse & Society, 6(2), 243-289.
Wong, F. M. F., Tan, C. W., Sen, S. & Chiang, M. (2016). Quantifying political leaning from tweets, retweets, and retweeters. IEEE Transactions on Knowledge and Data Engineering. https://www.doi.org/10.1109/TKDE.2016.2553667
Youyou, W., Kosinski, M. & Stillwell, D. (2015). Computer-based personality judgments are more accurate than those made by humans. Proceedings of the National Academy of Sciences of the United States of America, 112(4), 1036-1040. https://www.doi.org/10.1073/pnas.1418680112
Zhitomirsky-Geffet, M., David, E., Koppel, M. & Uzan, H. (2016). Utilizing overtly political texts for fully automatic evaluation of political leaning of online news websites. Online Information Review, 40(3), 362-379. https://www.doi.org/10.1108/OIR-06-2015-0211
Details
Article Details
RIGHTS TRANSFER
By submitting the article for evaluation and subsequent publication in Communication & Society, the AUTHOR exclusively assigns the rights of public communication, reproduction, distribution and sale for commercial exploitation to the University of Navarra through its Publications Service, for the maximum legal term in force -the entire life of the author and seventy years after his death or declaration of death-, in any country, and in any of the current and future edition modalities, both in print and electronic versions.
In the event that the article is not accepted for publication , this transfer of rights lapses with the communication of the refusal to the AUTHOR.
The AUTHOR affirms that the article is unpublished, that it has not been sent simultaneously to another publication medium and that the rights have not been transferred exclusively previously. He is responsible to the University of Navarra through its Publications Service for the authorship and originality of his work, as well as for all pecuniary charges that may arise for the University of Navarra through its Publications Service, in favor of third parties due to actions, claims or conflicts arising from the breach of obligations by the AUTHOR.
