Spread of tweets in climate discussions: A case study of the 2019 Nobel Peace Prize announcement

Xia, Yan; Chen, Ted Hsuan Yun; Kivelä, Mikko

doi:10.2478/njms-2021-0006

Abstract

Characterising the spreading of ideas within echo chambers is essential for understanding polarisation. In this article, we explore the characteristics of popular and viral content in climate change discussions on Twitter around the 2019 announcement of the Nobel Peace Prize, where we find the retweet network of users to be polarised into two well-separated groups of activists and sceptics. Operationalising popularity as the number of retweets and virality as the spreading probability inferred using an independent cascade model, we find that the viral themes echo and differ from the popular themes in interesting ways. Most importantly, we find that the most viral themes in the two groups reflect different types of bonds that tie the community together, yet both function to enhance ingroup connections while repulsing outgroup engagement. With this, our study sheds light, from an information-spreading perspective, on the formation and upkeep of echo chambers in climate discussions.

References

Adam, K. (2019, October 22). Why didn’t Greta Thunberg win the Nobel Peace Prize? The Washington Post. https://www.washingtonpost.com/world/europe/why-didnt-greta-thunberg-win-the-nobel-peace-prize/2019/10/11/e84e6efc-eba4-11e9-9306-47cb0324fd44_story.html.
Search in Google Scholar Back to article
Asikainen, A., Iñiguez, G., Ureña-Carrión, J., Kaski, K., & Kivelä, M. (2020). Cumulative effects of triadic closure and homophily in social networks. Science Advances, 6(19). https://doi.org/10.1126/sciadv.aax7310
Search in Google Scholar Back to article
Babyak, M. A. (2004). What you see may not be what you get: A brief, nontechnical introduction to overfitting in regression-type models. Psychosomatic medicine, 66(3), 411–421. https://doi.org/10.1097/01.psy.0000127692.23278.a9
Search in Google Scholar Back to article
Bail, C. A., Argyle, L. P., Brown, T. W., Bumpus, J. P., Chen, H., Hunzaker, M. F., Lee, J., Mann, M., Merhout, F., & Volfovsky, A. (2018). Exposure to opposing views on social media can increase political polarization. Proceedings of the National Academy of Sciences, 115(37), 9216–9221. https://doi.org/10.1073/pnas.1804840115
Search in Google Scholar Back to article
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://doi.org/10.1177/0956797615594620
Search in Google Scholar Back to article
Barbieri, N., Bonchi, F., & Manco, G. (2013). Topic-aware social influence propagation models. Knowledge and Information Systems, 37(3), 555–584. https://doi.org/10.1007/s10115-013-0646-6
Search in Google Scholar Back to article
Barrat, A., Barthelemy, M., & Vespignani, A. (2008). Dynamical processes on complex networks. Cambridge University Press.
Search in Google Scholar Back to article
Baumann, F., Lorenz-Spreen, P., Sokolov, I. M., & Starnini, M. (2020). Modeling echo chambers and polarization dynamics in social networks. Physical Review Letters, 124(4), 048301. https://doi.org/10.1103/PhysRevLett.124.048301
Search in Google Scholar Back to article
Bench, S. W., & Lench, H. C. (2013). On the function of boredom. Behavioral Sciences, 3(3), 459–472. https://doi.org/10.3390/bs3030459
Search in Google Scholar Back to article
Berger, J., & Milkman, K. L. (2012). What makes online content viral? Journal of Marketing Research, 49(2), 192–205. https://doi.org/10.1509/jmr.10.0353
Search in Google Scholar Back to article
Birch, S. (2020). Political polarization and environmental attitudes: A cross-national analysis. Environmental Politics, 29(4), 697–718. https://doi.org/10.1080/09644016.2019.1673997
Search in Google Scholar Back to article
Carrington, D. (2019, March 14). Greta Thunberg nominated for Nobel Peace Prize. The Guardian. https://www.theguardian.com/world/2019/mar/14/greta-thunberg-nominated-nobel-peace-prize
Search in Google Scholar Back to article
Chen, T. H. Y., Salloum, A., Gronow, A., Ylä-Anttila, T., & Kivelä, M. (2020, July 6). Polarization of climate politics results from partisan sorting: Evidence from Finnish Twittersphere. arXiv preprint arXiv:2007.02706. https://doi.org/10.31235/osf.io/49qgu
Search in Google Scholar Back to article
Cody, E. M., Reagan, A. J., Mitchell, L., Dodds, P. S., & Danforth, C. M. (2015). Climate change sentiment on twitter: An unsolicited public opinion poll. PloS one, 10(8), 1–18. https://doi.org/10.1371/journal.pone.0136092
Search in Google Scholar Back to article
Dahal, B., Kumar, S. A., & Li, Z. (2019). Topic modeling and sentiment analysis of global climate change tweets. Social Network Analysis and Mining, 9(24). https://doi.org/10.1007/s13278-019-0568-8
Search in Google Scholar Back to article
Dahlgren, P. M. (2021). A critical review of filter bubbles and a comparison with selective exposure. Nordicom Review, 42(1), 15–33. https://doi.org/10.2478/nor-2021-0002
Search in Google Scholar Back to article
Fariss, C. J., & Jones, Z. M. (2018). Enhancing validity in observational settings when replication is not possible. Political Science Research and Methods, 6(2), 365–380. https://doi.org/10.1017/psrm.2017.5
Search in Google Scholar Back to article
Garimella, K., Morales, G. D. F., Gionis, A., & Mathioudakis, M. (2018). Quantifying controversy on social media. ACM Transactions on Social Computing, 1(1), 1–27. https://doi.org/10.1145/3140565
Search in Google Scholar Back to article
Guerini, M., Strapparava, C., & Ozbal, G. (2011). Exploring text virality in social networks. Proceedings of the International AAAI Conference on Web and Social Media, 5(1).
Search in Google Scholar Back to article
Hansen, L. K., Arvidsson, A., Nielsen, F. Å., Colleoni, E., & Etter, M. (2011, June 28–30). Good friends, bad news-affect and virality in twitter. In J. J. J. H. Park, L. T. Yang, & C. Lee (Eds.), Future information technology: 6^th International Conference on Future Information Technology (pp. 34–43). Springer. https://doi.org/10.1007/978-3-642-22309-9
Search in Google Scholar Back to article
Hanteer, O., & Rossi, L. (2019). An innovative way to model twitter topic-driven interactions using multiplex networks. Frontiers in Big Data, 2(9). https://doi.org/10.3389/fdata.2019.00009
Search in Google Scholar Back to article
Hawkins, D. M. (2004). The problem of overfitting. Journal of Chemical Information and Computer Sciences, 44(1), 1–12. https://doi.org/10.1021/ci0342472
Search in Google Scholar Back to article
Jang, S. M., & Hart, P. S. (2015). Polarized frames on “climate change” and “global warming” across countries and states: Evidence from twitter Big Data. Global Environmental Change, 32, 11–17. https://doi.org/10.1016/j.gloenvcha.2015.02.010
Search in Google Scholar Back to article
Jenders, M., Kasneci, G., & Naumann, F. (2013). Analyzing and predicting viral tweets. Proceedings of the 22nd international conference on world wide web (pp. 657–664). https://doi.org/10.1145/2487788.2488017
Search in Google Scholar Back to article
Karypis, G. & Kumar, V. (1998). A fast and high quality multilevel scheme for partitioning irregular graphs. SIAM Journal on scientific Computing, 20(1), 359–392. https://dl.acm.org/doi/10.5555/305219.305248
Search in Google Scholar Back to article
Kempe, D., Kleinberg, J., & Tardos, É. (2003, August). Maximizing the spread of influence through a social network. Proceedings of the ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 137–146).
Search in Google Scholar Back to article
Kirilenko, A. P. & Stepchenkova, S. O. (2014). Public microblogging on climate change: One year of twitter worldwide. Global Environmental Change, 26, 171–182. https://doi.org/10.1016/j.gloenvcha.2014.02.008
Search in Google Scholar Back to article
McCright, A. M., & Dunlap, R. E. (2011). The politicization of climate change and polarization in the American public's views of global warming, 2001–2010. The Sociological Quarterly, 52(2), 155–194. https://doi.org/10.1111/j.1533-8525.2011.01198.x
Search in Google Scholar Back to article
McNeish, D. M. (2015). Using lasso for predictor selection and to assuage overfitting: A method long overlooked in behavioral sciences. Multivariate Behavioral Research, 50(5), 471–484. https://doi.org/10.1080/00273171.2015.1036965
Search in Google Scholar Back to article
Muddiman, A., McGregor, S. C., & Stroud, N. J. (2019). (Re)claiming our expertise: Parsing large text corpora with manually validated and organic dictionaries. Political Communication, 36(2), 214–226. https://doi.org/10.1080/10584609.2018.1517843
Search in Google Scholar Back to article
Munger, K. (2019). The limited value of non-replicable field experiments in contexts with low temporal validity. Social Media + Society, 5(3), 1–4. https://doi.org/10.1177/2056305119859294
Search in Google Scholar Back to article
Musco, C., Musco, C., & Tsourakakis, C. E. (2018). Minimizing polarization and disagreement in social networks. Proceedings of the 2018 World Wide Web Conference (pp. 369–378).
Search in Google Scholar Back to article
Nagarajan, M., Purohit, H., & Sheth, A. (2010). A qualitative examination of topical tweet and retweet practices. Fourth International AAAI Conference on Weblogs and Social Media. Citeseer.
Search in Google Scholar Back to article
Nelimarkka, M., Laaksonen, S.-M., & Semaan, B. (2018). Social media is polarized, social media is polarized: Towards a new design agenda for mitigating polarization. Proceedings of the 2018 Designing Interactive Systems Conference (pp. 957–970).
Search in Google Scholar Back to article
Pariser, E. (2011). The filter bubble: What the Internet is hiding from you. Penguin UK.
Search in Google Scholar Back to article
Pearce, W., Holmberg, K., Hellsten, I., & Nerlich, B. (2014). Climate change on Twitter: Topics, communities and conversations about the 2013 IPCC working group 1 report. PloS one, 9(4), e94785. https://doi.org/10.1371/journal.pone.0094785
Search in Google Scholar Back to article
Saito, K., Nakano, R., & Kimura, M. (2008). Prediction of information diffusion probabilities for independent cascade model. International conference on knowledge-based and intelligent information and engineering systems (pp. 67–75). Springer.
Search in Google Scholar Back to article
Stieglitz, S., & Dang-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. https://doi.org/10.2753/MIS0742-1222290408
Search in Google Scholar Back to article
Suh, B., Hong, L., Pirolli, P., & Chi, E. H. (2010). Want to be retweeted? Large scale analytics on factors impacting retweet in twitter network. 2010 IEEE Second International Conference on Social Computing (pp. 177–184). IEEE.
Search in Google Scholar Back to article
Tyagi, A., Uyheng, J., & Carley, K. M. (2020). Affective polarization in online climate change discourse on twitter. arXiv preprint arXiv:2008.13051.
Search in Google Scholar Back to article
Weng, L., Menczer, F., & Ahn, Y.-Y. (2013). Virality prediction and community structure in social networks. Scientific reports, 3, 2522. https://doi.org/10.1038/srep02522
Search in Google Scholar Back to article
Williams, H. T., McMurray, J. R., Kurz, T., & Lambert, F. H. (2015). Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global environmental change, 32, 126–138. https://doi.org/10.1016/j.gloenvcha.2015.03.006
Search in Google Scholar Back to article
Yuan, M., & Lin, Y. (2006). Model selection and estimation in regression with grouped variables. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 68(1), 49–67. https://doi.org/10.1111/j.1467-9868.2005.00532.x
Search in Google Scholar Back to article
Zuckerman, M. (2010). Sensation seeking. The Corsini encyclopedia of psychology, 1–4.
Search in Google Scholar Back to article

Spread of tweets in climate discussions: A case study of the 2019 Nobel Peace Prize announcement

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