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:

Auditing local news presence on Google News

Nature Human Behaviour volume 4, pages 1236–1244 (2020)Cite this article

Subjects

Matters Arising to this article was published on 11 August 2022

Abstract

Local news outlets have struggled to stay open in the more competitive market of digital media. Some have noted that this decline may be due to the ways in which digital platforms direct attention to some news outlets and not others. To test this theory, we collected 12.29 million responses to Google News searches within all US counties for a set of keywords. We compared the number of local outlets reported in the results against the number of national outlets. We find that, unless consumers are searching specifically for topics of local interest, national outlets dominate search results. Features correlated with local supply and demand, such as the number of local outlets and demographics associated with local news consumption, are not related to the likelihood of finding a local news outlet. Our findings imply that platforms may be diverting web traffic and desperately needed advertising dollars away from local news.

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

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

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

Fig. 1: Gini index for individual searches.
Fig. 2: Relative frequency of local and national outlets for the top-n results of each search query.
Fig. 3: Estimated coefficients from the model with no interactions and standard errors clustered by county.
Fig. 4: Estimated effects on the number of appearances in scraped results with standard errors clustered by county.
Fig. 5: Google trends for locally oriented and general terms over time.

Similar content being viewed by others

Data availability

The figures and analyses in this paper are based on original data collected by the authors. Raw data, as well as processed minimal datasets necessary for reproducing the analyses and figures, are available via the associated OSF repository for this project (https://osf.io/hwuxf/?view_only=3fa7499661df487689031e11b8ea20b4).

Code availability

Original code is available via the associated OSF repository for this project (https://osf.io/hwuxf/?view_only=3fa7499661df487689031e11b8ea20b4).

References

  1. Abernathy, P. M. The Expanding News Desert (UNC Press, 2018).

  2. Hindman, M. The Internet Trap: How the Digital Economy Builds Monopolies and Undermines Democracy (Princeton Univ. Press, 2018).

  3. For Local News, Americans Embrace Digital but Still Want Strong Community Connection Technical Report (Pew Research Center, 2019).

  4. Diakopoulos, N. Audit suggests Google favors a small number of major outlets. Columbia Journalism Review https://www.cjr.org/tow_center/google-news-algorithm.php (10 May 2019).

  5. Pan, B. et al. In Google we trust: users’ decisions on rank, position, and relevance. J. Comput. Mediat. Commun. 12, 801–823 (2007).

    Article  Google Scholar 

  6. Eubanks, V. Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor (St. Martin’s Press, 2018).

  7. Robertson, R. E. et al. Auditing partisan audience bias within Google Search. Proc. ACM Hum. Comput. Interact. 2, 148 (2018).

    Article  Google Scholar 

  8. Kliman-Silver, C., Hannak, A., Lazer, D., Wilson, C. & Mislove, A. Location, location, location: the impact of geolocation on web search personalization. in Proceedings of the Internet Measurement Conference 2015 (eds Cho, K., Fukuda, K., Pai, V. & Spring, N.)121–127 (IMC, 2015).

  9. Trielli, D. & Diakopoulos, N. Search as news curator: the role of Google in shaping attention to news information. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems 453 (ACM, 2019).

  10. Thorson, K., Cotter, K., Medeiros, M. & Pak, C. Algorithmic inference, political interest, and exposure to news and politics on Facebook. Inf. Commun. Soc. https://doi.org/10.1080/1369118X.2019.1642934 (2019).

  11. Haim, M., Graefe, A. & Brosius, H.-B. Burst of the filter bubble? Effects of personalization on the diversity of Google News. Digit. Journal. 6, 330–343 (2018).

    Google Scholar 

  12. Nechushtai, E. & Lewis, S. C. What kind of news gatekeepers do we want machines to be? Filter bubbles, fragmentation, and the normative dimensions of algorithmic recommendations. Comput. Hum. Behav. 90, 298–307 (2019).

    Article  Google Scholar 

  13. Bakshy, E., Messing, S. & Adamic, L. A. Exposure to ideologically diverse news and opinion on Facebook. Science 348, 1130–1132 (2015).

    Article  CAS  Google Scholar 

  14. Newman, N., Fletcher, R., Kalogeropoulos, A. & Nielsen, R. Reuters Institute Digital News Report 2019 Vol. 2019 (Reuters Institute for the Study of Journalism, 2019).

  15. Barthel, M., Grieco, E. & Shearer, E. Older Americans, Black Adults and Americans With Less Education More Interested in Local News. Technical Report (Pew Research Center, 2019).

  16. Benjamin, R. Race After Technology: Abolitionist Tools for the New Jim Code (John Wiley & Sons, 2019).

  17. Hannak, A. et al. Measuring personalization of web search. In Proceedings of the 22nd International World Wide Web Conference (WWW 2013) (2013).

  18. Jansen, B. J., Spink, A. & Saracevic, T. Real life, real users, and real needs: a study and analysis of user queries on the web. Inf. Process. Manage. 36, 207–227 (2000).

    Article  Google Scholar 

  19. Jansen, B. J. & Spink, A. How are we searching the World Wide Web? A comparison of nine search engine transaction logs. Inf. Process. Manage. 42, 248–263 (2006).

    Article  Google Scholar 

  20. Epstein, R. & Robertson, R. E. The search engine manipulation effect (SEME) and its possible impact on the outcomes of elections. Proc. Natl Acad. Sci. USA 112, E4512–E4521 (2015).

    Article  CAS  Google Scholar 

  21. Granka, L. A., Joachims, T. & Gay, G. Eye-tracking analysis of user behavior in www search. In Proceedings of the 27th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 478–479 (ACM, 2004).

  22. Hopkins, D. J. The Increasingly United States: How and Why American Political Behavior Nationalized (Univ. Chicago Press, 2018).

  23. Mahone, J., Wang, Q., Napoli, P., Weber, M. & McCollough, K. Who’s Producing Local Journalism? Technical Report (Duke Univ., 2019).

  24. Athey, S., Mobius, M. M. & Pál, J. The impact of aggregators on internet news consumption. Research Paper No. 17-8 https://ssrn.com/abstract=2897960 (Stanford University Graduate School of Business, 2017).

  25. Calzada, J. & Gil, R. What do news aggregators do? Evidence from Google news in Spain and Germany. Mark. Sci. https://doi.org/10.1287/mksc.2019.1150 (2019).

  26. Deahl, D. Google News is getting an overhaul and customized news feeds. The Verge https://www.theverge.com/2018/5/8/17329074/google-news-update-new-features-newsstand-io-2018 (2018).

  27. Oberstein, M. AMP in Google News results skyrockets globally. RankRanger https://www.rankranger.com/blog/amp-google-news-results-spikes (30 January 2017).

  28. Darr, J. P., Hitt, M. P. & Dunaway, J. L.Newspaper closures polarize voting behavior. J. Commun. 68, 1007–1028 (2018).

    Article  Google Scholar 

  29. Shaker, L.Dead newspapers and citizens’ civic engagement. Political Commun. 31, 131–148 (2014).

    Article  Google Scholar 

  30. Hayes, D. & Lawless, J. L.As local news goes, so goes citizen engagement: media, knowledge, and participation in US House elections. J. Politics 77, 447–462 (2015).

    Article  Google Scholar 

  31. Hayes, D. & Lawless, J. L.The decline of local news and its effects: new evidence from longitudinal data. J. Politics 80, 332–336 (2018).

    Article  Google Scholar 

  32. Eder, J. S. Knowledge graph based search system. US patent 13/404,109 (2012).

  33. Napoli, P. M., Weber, M., McCollough, K. & Wang, Q. Assessing Local Journalism: News Deserts, Journalism Divides, and the Determinants of the Robustness of Local News (DeWitt Wallace Center for Media & Democracy, 2018).

  34. Pariser, E. The Filter Bubble: How the New Personalized Web is Changing What We Read and How We Think (Penguin, 2011).

  35. Robertson, R. E., Lazer, D. & Wilson, C. Auditing the personalization and composition of politically-related search engine results pages. In Proceedings of the 2018 World Wide Web Conference 955–965 (International World Wide Web Conferences Steering Committee, 2018).

  36. Noble, S. U. in Algorithms of Oppression: How Search Engines Reinforce Racism 41 (NYU Press, 2018).

  37. Gottfried, J. & Shearer, E. News Use Across Social Media Platforms 2016 Technical Report (Pew Research Center, 2016).

  38. Settle, J. E. Frenemies: How Social Media Polarizes America (Cambridge Univ. Press, 2018).

  39. Napoli, P. M., Stonbely, S., McCollough, K. & Renninger, B. Local journalism and the information needs of local communities: toward a scalable assessment approach. Journal. Pract. 11, 373–395 (2017).

    Google Scholar 

  40. Weber, M., Andringa, P. & Napoli, P. M. Local News on Facebook: Assessing the Critical Information Need Served through Facebook’s TodayIn Feature News Measures Research Project (Duke University Sanford School of Public Policy & Hubbard School of Journalism and Mass Communication, 2019).

  41. Friedland, L., Napoli, P., Ognyanova, K., Weil, C. & Wilson, E. J. III Review of the Literature Regarding Critical Information Needs of the American Public http://transition.fcc.gov/bureaus/ocbo/Final_Literature_Review.pdf (FCC, 2012).

  42. Van Mens, J. I Search From (2020); http://isearchfrom.com/

  43. Barysevich, A. How you can see Google search results for different locations. SEJ https://www.searchenginejournal.com/see-google-search-results-different-location/294829 (2019).

  44. Caizer, C. How to localize Google search results. Search Engine Land https://searchengineland.com/localize-google-search-results-239768 (2016).

  45. Yin, L. yinleon/LocalNewsDataset: initial release. Zenodo https://doi.org/10.5281/zenodo.1345145 (2018).

  46. Hagar, N., Bandy, J., Trielli, D., Wang, Y. & Diakopoulos, N. Defining local news: a computational approach. In Computational + Journalism Symposium 2020 https://cpb-us-w2.wpmucdn.com/sites.northeastern.edu/dist/d/53/files/2020/02/CJ_2020_paper_40.pdf (2020).

  47. Lowrey, W., Brozana, A. & Mackay, J. B. Toward a measure of community journalism. Mass Commun. Soc. 11, 275–299 (2008).

    Article  Google Scholar 

Download references

Acknowledgements

We thank D. Lazer, G. Martin, R. Robertson, D. Trielli, N. Usher and the participants and reviewers at the Politics and Computational Social Science 2019 conference, the Michigan Symposium on Media and Politics and the International Communication Association 2020 conference for helpful comments. The authors received no specific funding for this work.

Author information

Authors and Affiliations

  1. Annenberg School for Communication, University of Pennsylvania, Philadelphia, PA, USA

    Sean Fischer & Yphtach Lelkes

  2. Department of Communications and New Media, National University of Singapore, Singapore, Singapore

    Kokil Jaidka

Authors
  1. Sean Fischer
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kokil Jaidka
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yphtach Lelkes
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

S.F., K.J. and Y.L. designed the study, conducted the analysis and drafted and revised the manuscript.

Corresponding author

Correspondence to Yphtach Lelkes.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Primary Handling Editor: Aisha Bradshaw.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Figs. 1–3, Supplementary Tables 1–7, Supplementary Methods, Supplementary Results and Supplementary References.

Reporting Summary

Rights and permissions

Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Fischer, S., Jaidka, K. & Lelkes, Y. Auditing local news presence on Google News. Nat Hum Behav 4, 1236–1244 (2020). https://doi.org/10.1038/s41562-020-00954-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41562-020-00954-0

This article is cited by

Search

Advanced 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