Abstract
Political opinions as expressed by the news media have created the phenomenon of polarization in the United States. Modern news agencies have always considered objectivity as being of primary importance. When opinions inadvertently color the facts, the resulting information manipulation can create confusion, and chaos. This study attempts to understand the language differences as expressed by the U.S. news media in the conveyance of political opinions, and to identify predictive language-action cues that can differentiate writing styles of right-wing news media from those of left-wing news media on Twitter. Original tweets from news media agencies were collected and analyzed using logistical regression analysis during September 2019. The study identifies a statistical significance with regards to cognitive loads, analytical thinking, and political sentiment profiles of tweets to allow for better ways of differentiating political opinions between the news media, from right-wing to left-wing. This suggests that news media of the left-wing and right-wing could employ more neutral writing styles to reduce political polarization. The study contributes to our understanding of the language strategies employed by the news media in terms of influencing the public opinions.
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References
Tumasjan, A., Sprenger, T.O., Sandner, P.G., Welpe, I.M.: Predicting elections with Twitter: what 140 characters reveal about political sentiment. In: Proceedings of the Fourth International AAAI Conference on Weblogs and Social Media (ICWSM 2010), pp. 178–185. Association for the Advancement of Artificial Intelligence, Washington, DC (2010)
Tripathi, G., Naganna, S.: Opinion mining: a review. Int. J. Inf. Comput. Technol. 4(16), 1625–1635 (2014)
Yu, B., Kaufmann, S., Diermeier, D.: Exploring the characteristics of opinion expressions for political opinion classification. In: Proceedings of the 9th Annual International Digital Government Research Conference, Montreal, Canada, pp. 82–91 (2008)
Tumasjan, A., Sprenger, T.O., Sandner, P.G., Welpe, I.M.: Election forecasts with Twitter: how 140 characters reflect the political landscape. Soc. Sci. Comput. Rev. 29(4), 402–418 (2011). https://doi.org/10.1177/0894439310386557
Stieglitz, S., Dang-Xuan, L.: Political communication and influence through microblogging-an empirical analysis of sentiment in Twitter messages and retweet behavior. In: Proceedings of the 2012 45th Hawaii International Conference on System Sciences (HICSS’45), pp. 3500–3509. IEEE Computer Society, Hawaii (2012). https://doi.org/10.1109/hicss.2012.476
Dang-Xuan, L., Stieglitz, S.: Impact and diffusion of sentiment in political communication-an empirical analysis of political weblogs. In: Proceedings of the 2012 Sixth International AAAI Conference on Weblogs and Social Media (ICWSM 2012), pp. 427–430. Association for the Advancement of Artificial Intelligence, Dublin (2012)
Stieglitz, S., Dang-Xuan, L.: Impact and diffusion of sentiment in public communication on Facebook. In: Proceedings of the 2012 European Conference on Information Systems (ECIS 2012), pp. 1–13. Association for Information Systems (AIS) (2012). aisel.aisnet.org/ecis2012/98
Wang, H., Can, D., Kazemzadeh, A., Bar, F., Narayanan, S.: A system for real-time Twitter sentiment analysis of 2012 U.S. presidential election cycle. In: Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics (ACL 2012), pp. 115–120. Association for Computational Linguistics, Jeju Island (2012)
Nooralahzadeh, F., Arunachalam, V., Chiru, C.: 2012 presidential elections on Twitter-an analysis of how the US and French election were reflected in tweets. In: Proceedings of the 2013 19th International Conference on Control Systems and Computer Science. IEEE, Bucharest (2013). https://doi.org/10.1109/cscs.2013.72
Alashri, S., Sandala, S.S., Bajaj, V., Parriott, E., Awazu, Y., Desouza, K.C.: The 2016 US presidential election on Facebook: an exploratory analysis of sentiments. In: Proceedings of the 2018 51st Hawaii International Conference on System Sciences (HICSS’51), pp. 1771–1780. University of Hawaii, Waikoloa Village, Hawaii Big Island (2018). https://doi.org/10.24251/hicss.2018.223
Jordan, K.N., Pennebaker, J.W., Ehrig, C.: The 2016 U.S. Presidential candidates and how people tweeted about them, 1–8 (2018). https://doi.org/10.1177/2158244018791218. Special collection: SMaPP global special issue
Pennebaker, J.W., Boyd, R.L., Jordan, K.N., Blackburn, K.: The development and psychometric properties of LIWC2015. University of Texas at Austin (2015)
Acknowledgements
The authors wish to thank Florida Center for Cybersecurity (FC2) Capability Building Program for the grant #FC2-3910-1007-00-B, 07/01/2018—06/30/2020. The authors also wish to thank Conrad Metcalfe for his editing assistance.
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Ho, S.M., Kao, D., Li, W., Lai, CJ., Chiu-Huang, MJ. (2020). “On the left side, there’s nothing right. On the right side, there’s nothing left:” Polarization of Political Opinion by News Media. In: Sundqvist, A., Berget, G., Nolin, J., Skjerdingstad, K. (eds) Sustainable Digital Communities. iConference 2020. Lecture Notes in Computer Science(), vol 12051. Springer, Cham. https://doi.org/10.1007/978-3-030-43687-2_16
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