Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

An empirical examination of echo chambers in US climate policy networks

Subjects

A Corrigendum to this article was published on 23 October 2015

This article has been updated

Abstract

Diverse methods have been applied to understand why science continues to be debated within the climate policy domain. A number of studies have presented the notion of the ‘echo chamber’ to model and explain information flows across an array of social settings, finding disproportionate connections among ideologically similar political communicators. This paper builds on these findings to provide a more formal operationalization of the components of echo chambers. We then empirically test their utility using survey data collected from the community of political elites engaged in the contentious issue of climate politics in the United States. Our survey period coincides with the most active and contentious period in the history of US climate policy, when legislation regulating carbon dioxide emissions had passed through the House of Representatives and was being considered in the Senate. We use exponential random graph (ERG) modelling to demonstrate that both the homogeneity of information (the echo) and multi-path information transmission (the chamber) play significant roles in policy communication. We demonstrate that the intersection of these components creates echo chambers in the climate policy network. These results lead to some important conclusions about climate politics, as well as the relationship between science communication and policymaking at the elite level more generally.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Network building blocks of an echo chamber.
Figure 2: Ego networks coloured by degree of agreement with ‘There should be an international binding commitment on all nations to reduce GHG emissions’.
Figure 3: Images for terms used in the exponential random graph models.
Figure 4: ERGM results.

Similar content being viewed by others

Change history

  • 01 October 2015

    In the version of this Article originally published, the colouration and detail in Fig. 2 were incorrect. These errors have been corrected in the online versions of the Article.

References

  1. Jorgenson, A. K. Energy: Analyzing fossil-fuel displacement. Nature Clim. Change 2, 398–399 (2012).

    Article  Google Scholar 

  2. Jorgenson, A. K. Economic development and the carbon intensity of human well-being. Nature Clim. Change 4, 186–189 (2014).

    Article  Google Scholar 

  3. Rogelj, J., McCollum, D. L., Reisinger, A., Meinschausen, M. & Riahi, K. Probabilistic cost estimates for climate change mitigation. Nature 493, 79–83 (2013).

    Article  Google Scholar 

  4. Loarie, S. R. et al. The velocity of climate change. Nature 462, 1052–1055 (2009).

    Article  CAS  Google Scholar 

  5. Meinhausen, M. et al. Greenhouse-gas emission targets for limiting global warming to 2C. Nature 458, 1158–1162 (2009).

    Article  Google Scholar 

  6. Fisher, D. R., Waggle, J. & Liefeld, P. Where does political polarization come from? Locating polarization within the U.S. climate change debate. Am. Behav. Sci. 57, 70–92 (2013).

    Article  Google Scholar 

  7. Biello, D. Senators vote in circles about global warming and the Keystone XL Pipeline. Scientific American Blog Network (January 30, 2015); http://blogs.scientificamerican.com/observations/2015/01/30/senators-vote-in-circles-about-global-warming-and-the-keystone-xl-pipeline

  8. McComas, K. & Shanahan, J. Telling stories about global climate change: Measuring the impact of narratives on issue cycles. Commun. Res. 26, 30–57 (1999).

    Article  Google Scholar 

  9. Shanahan, J. & Good, J. Heat and hot air: Influence of local temperatures on journalists’ coverage of global warming. Public Underst. Sci. 9, 285–295 (2000).

    Article  Google Scholar 

  10. Weingart, P., Engels, A. & Pansegrau, P. Risks of communication: Discourses on climate change in science, politics, and the mass media. Public Underst. Sci. 9, 261–283 (2000).

    Article  Google Scholar 

  11. Jacques, P. J., Dunlap, R. E. & Freeman, M. The organisation of denial: Conservative think tanks and environmental scepticism. Environ. Polit. 17, 349–385 (2008).

    Article  Google Scholar 

  12. Brulle, R. J. Institutionalizing delay; building and maintaining the U.S. climate change countermovement. Climatic Change 122, 681–694 (2013).

    Article  Google Scholar 

  13. Liu, X., Lindquist, E. & Vedlitz, A. Explaining media and Congressional attention to global climate change, 1969–2005 An empirical test of agenda-setting theory. Polit. Res. Q. 64, 1–15 (2009).

    Google Scholar 

  14. McCright, A. M. & Dunlap, R. E. Challenging global warming as a social problem: An analysis of the conservative movement’s counter-claims. Soc. Prob. 47, 499–522 (2000).

    Article  Google Scholar 

  15. Feldman, L., Myers, T., Hmielowski, J. & Leiserowitz, A. The mutual reinforcement of media selectivity effects: Testing the reinforcing spirals framework in the context of global warming. J. Commun. 64, 590–611 (2014).

    Article  Google Scholar 

  16. Dandekar, P., Goel, A. & Lee, D. T. Biased assimilation, homophily and the dynamics of polarization. Proc. Natl Acad. Sci. USA 110, 5791–5796 (2013).

    Article  CAS  Google Scholar 

  17. Adamic, L. & Glance, N. Proc. Intl Wkshp. Link. Disc. 3rd edn (LinkKDD-2005, 2005).

    Google Scholar 

  18. Uzzi, B. & Dunlap, S. How to build your network. Harv. Bus. Rev. 83, 53–60 (2005).

    Google Scholar 

  19. Burt, R. S. in Networks and Markets (eds Rauch, J. E. & Casella, A.) Ch. 2, 30–74 (Russell Sage Foundation, 2001).

    Google Scholar 

  20. Key, V. O. Jr The Responsible Electorate (Harvard Univ. Press, 1966).

    Book  Google Scholar 

  21. Callison, C. Distorting the climate message. Nature 463, 161–162 (2010).

    Article  CAS  Google Scholar 

  22. Alvarez, R. M. & Nagler, J. Party system compactness: Measurement and consequences. Polit. Anal. 12, 46–62 (2004).

    Article  Google Scholar 

  23. Garrett, R. K. Echo chambers online? Politically motivated selective exposure among internet news users. J. Comput. Mediate. Commun. 14, 265–285 (2009).

    Article  Google Scholar 

  24. Jamieson, K. H. & Cappella, J. N. Echo Chamber: Rush Limbaugh and the Conservative Media Establishment (Oxford Univ. Press, 2008).

    Google Scholar 

  25. Peters, H. P. Gap between science and media revisited: Scientists as public communicators. Proc. Natl Acad. Sci. USA 110, 14102–14109 (2013).

    Article  CAS  Google Scholar 

  26. Bennett, W. L. & Iyengar, S. A new era of minimal effects? The changing foundations of political communication. J. Commun. 58, 707–731 (2008).

    Article  Google Scholar 

  27. Gleeson, J. P. et al. A simple generative model of collective online behavior. Proc. Natl Acad. Sci. USA 111, 10411–10415 (2014).

    Article  CAS  Google Scholar 

  28. Lewis, K., Gonzalez, M. & Kaufman, J. Social selection and peer influence in an online social network. Proc. Natl Acad. Sci. USA 109, 68–72 (2012).

    Article  CAS  Google Scholar 

  29. McPherson, M., Smith-Lovin, L. & Cook, J. M. Birds of a feather: Homophily in social networks. Annu. Rev. Sociol. 27, 415–444 (2001).

    Article  Google Scholar 

  30. Wallsten, K. Political blogs and the bloggers who blog them: Is the political blogosphere an echo chamber? Am. Polit. Sci. Assoc. Ann. Meet. (2005); http://go.nature.com/szuS7j

  31. Gilbert, E., Bergstrom, T. & Karahalios, K. Blogs are echo chambers. Proc. HICSS 42, 1–10 (2009).

    Google Scholar 

  32. Onnela, J. P. & Reed-Tsochas, F. Spontaneous emergence of social influence in online systems. Proc. Natl Acad. Sci. USA 107, 18375–18380 (2010).

    Article  CAS  Google Scholar 

  33. Reese, S. D., Rutigliano, L., Hyun, K. & Jeong, J. Mapping the blogosphere: Professional and citizen-based media in the global news arena. Journalism 8, 235–261 (2007).

    Article  Google Scholar 

  34. Nickerson, R. S. Confirmation bias: A ubiquitous phenomenon in many guises. Rev. Gen. Psychol. 2, 175–220 (1998).

    Article  Google Scholar 

  35. Butts, C. T. A Bayesian model of panic in belief. CMOT 4, 373–404 (1998).

    Google Scholar 

  36. Weaver, K., Garcia, S. M., Schwarz, N. & Miller, D. T. Inferring the popularity of an opinion from its familiarity: A repetitive voice can sound like a chorus. J. Pers. Soc. Psychol. 92, 821–833 (2007).

    Article  Google Scholar 

  37. Mas, M. & Flache, A. Differentiation without distancing: Explaining bi-polarization of opinions without negative influence. PLoS ONE 8, e74516 (2013).

    Article  Google Scholar 

  38. Stroud, N. J. Niche News: The Politics of News Choice (Cambridge Univ. Press, 2011).

    Book  Google Scholar 

  39. Jamieson, K. H. & Hardy, B. W. Leveraging scientific credibility about Arctic sea ice trends in a polarized political environment. Proc. Natl Acad. Sci. USA 111, 13598–13605 (2014).

    Article  CAS  Google Scholar 

  40. Macy, M. W., Kitts, J. A., Flache, A. & Benard, S. in Dynamic Social Network Modeling and Analysis: Workshop Summary and Papers (eds Breiger, R., Carley, K. & Pattison, P.) 162–173 (National Academies Press, 2003).

    Google Scholar 

  41. Knoke, D. Political Networks: The Structural Perspective (Cambridge Univ. Press, 1990).

    Book  Google Scholar 

  42. Roodhouse, E. A. The voice from the base(ment): Stridency, referential structure, and partisan conformity in the political blogosphere. First Monday 14, 9 (2009).

    Article  Google Scholar 

  43. Laumann, E. O. & Knoke, D. The Organizational State: Social Choice in National Policy Domains (Univ. Wisconsin Press, 1987).

    Google Scholar 

  44. Fisher, D. R., Leifeld, P. & Iwaki, Y. Mapping the ideological networks of American climate politics. Climatic Change 116, 523–545 (2013).

    Article  Google Scholar 

  45. Shwed, U. & Bearman, P. S. The temporal structure of scientific consensus formation. Am. Soc. Rev. 75, 817–840 (2010).

    Article  Google Scholar 

  46. Christakis, N. A. & Fowler, J. H. Friendship and natural selection. Proc. Natl Acad. Sci. USA 111, 10796–10801 (2014).

    Article  CAS  Google Scholar 

  47. Eagle, N., Pentland, A. S. & Lazer, D. Inferring friendship network structure by using mobile phone data. Proc. Natl Acad. Sci. USA 109, 15274–15278 (2009).

    Article  Google Scholar 

  48. Fowler, J. H. & Christakis, N. A. Cooperative behavior cascades in human social networks. Proc. Natl Acad. Sci. USA 107, 5334–5338 (2010).

    Article  CAS  Google Scholar 

  49. Rand, D. G., Arbesman, S. & Christakis, N. A. Dynamic social networks promote cooperation in experiments with humans. Proc. Natl Acad. Sci. USA 108, 19193–19198 (2011).

    Article  CAS  Google Scholar 

  50. Lazer, D., Rubineau, B., Chetkovich, C., Katz, N. & Neblo, M. The coevolution of networks and political attitudes. Polit. Commun. 27, 248–274 (2010).

    Article  Google Scholar 

  51. Scheufele, D. Science communication as political communication. Proc. Natl Acad. Sci. USA 111, 13585–13592 (2014).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

This research was supported by the US National Science Foundation (BCS-0826892) and the National Socio-Environmental Synthesis Center (SESYNC) (DBI-1052875). The authors would like to thank K. Krimmel and M. Abascal for their help in collecting some of the data used in this paper. The authors would also like to thank P. Leifeld, M. Palmer and P. Cohen for providing comments on earlier drafts of this paper.

Author information

Authors and Affiliations

Authors

Contributions

D.R.F. directed data collection. L.J. was responsible for data analysis. J.W. cleaned data and prepared reports and drafts of the manuscript. All authors contributed to project design, write-up of findings, and revisions.

Corresponding author

Correspondence to Dana R. Fisher.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jasny, L., Waggle, J. & Fisher, D. An empirical examination of echo chambers in US climate policy networks. Nature Clim Change 5, 782–786 (2015). https://doi.org/10.1038/nclimate2666

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nclimate2666

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing