Individual Submission Summary

Direct link:

How Search Engines and Social Media Shape News Use: Evidence from Tracking Data

Fri, August 30, 8:00 to 9:30am, Hilton, Tenleytown West


There has been significant growth in the number of people that use search engines and social media for news in the last ten years. Yet, we still know relatively little about how they shape online news use. Here, we use web tracking data from a representative panel of around 1,000 UK news users to explore whether people who are more reliant on search engines and social media for news (as opposed to direct access by navigating to homepages) have fundamentally different news repertoires in terms of diversity and partisanship.

As our reliance on distributed news access via search engines and social media has increased, scholars have worried about the potential for people to be trapped inside echo chambers and filter bubbles (Pariser, 2011; Sunstein, 2017). Although recent empirical research in this area has not typically found strong evidence of either phenomenon (Zuiderveen Borgesius et al., 2016), most studies—though still valuable—have focussed on the dynamics of news use via search engines and social media in isolation. For the most part, research has not examined how news access via search and social compares to direct access. As such, even if we reject the notion of prevalent echo chambers or filter bubbles, it remains possible that people who are more reliant on algorithmic news selection via search engines and social media might still have less diverse and more partisan news repertoires compared to those who are more reliant (or perhaps solely reliant) on self-selection via direct access.

We investigate these issues by analysing desktop web tracking data (collected by YouGov) that recorded the news use of a representative sample of 1,000 UK internet users for one month in 2017. The dataset contains every visit made to a news story during this period (n = ~170,000), as well as data on whether each news story was arrived at via a search engine, social media, or direct access. By combining measures of diversity used in communications research (McDonald & Dimmick, 2003) and audience-based measures of news outlet ideology (Gentzkow & Shapiro, 2011), we compared the partisanship and diversity of individual news repertoires of people with different degrees of reliance on search engines and social media. This approach allowed us to analyse data on news use at the story level (rather than the outlet level), avoid problems associated with recall, analyse social media and search engine use in the context of other online behaviours, analyse the behaviour of those who do not use search and social for news at all, whilst controlling for a number of other socio-demographic variables.

We find that (i) people who are more reliant on search engines and social media for news use significantly more news sources, (ii) and—perhaps surprisingly—have significantly more diverse news repertoires. However, (iii) people who are more reliant on search engines and social media for news also have more partisan news repertoires. In addition to these findings, the data also allow us to produce more accurate estimates of incidental exposure to news via search engines and social media, for example revealing that 86% of people who used social media for news used it to access sources they did not otherwise go to directly.

These findings expand our knowledge of how search engines and social media shape online news use, and shed light on the relative impact of both self-selection and algorithmic selection. In particular, the positive association between reliance on search and social and news repertoire diversity adds to the mounting body of evidence countering fears of echo chambers and filter bubbles, but also highlights that algorithmic selection can produce broader news repertoires than self-selection. However, these findings also raise the possibility that this increased diversity may ultimately consist of more partisan news sources, which has the potential to increase negative outcomes like political polarization, even as cross-cutting exposure becomes more prevalent (Bail et al., 2018).


Bail, C. A., Argyle, L. P., Brown, T. W., Bumpus, J. P., Chen, H., Fallin Hunzaker, M. B., … Volfovsky, A. (2018). Exposure to Opposing Views on Social Media Can Increase Political Polarization. Proceedings of the National Academy of Sciences in the United States of America, 0(0), 1–6.

Gentzkow, M., & Shapiro, J. M. (2011). Ideological Segregation Online and Offline. The Quarterly Journal of Economics, 126, 1799–1839.

McDonald, D. G., & Dimmick, J. (2003). The Conceptualization and Measurement of Diversity. Communication Research, 30(1), 60–79.

Pariser, E. (2011). Filter Bubbles: What the Internet is Hiding from You. London: Penguin.

Sunstein, C. R. (2017). #republic: Divided Democracy in the Age of Social Media. Princeton: Princeton University Press.

Zuiderveen Borgesius, F. J., Trilling, D., Möller, J., Bodó, B., de Vreese, C. H., & Helberger, N. (2016). Should We Worry about Filter Bubbles? Internet Policy Review, 5(1), 1–16.


©2020 All Academic, Inc.   |   Privacy Policy