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BRIEF REPORT
SOCIAL SCIENCES
How social network sites and other online
intermediaries increase exposure to news
Michael Scharkowa,1, Frank Mangoldb, Sebastian Stierc, and Johannes Breuerc
aDepartment of Communication, Johannes Gutenberg University Mainz, 55099 Mainz, Germany; bDepartment of Communication, University of
Hohenheim, 70599 Stuttgart, Germany; and cGESIS Leibniz Institute for the Social Sciences, 50667 Cologne, Germany
Edited by Mary C. Waters, Harvard University, Cambridge, MA, and approved January 9, 2020 (received for review November 4, 2019)
Research has prominently assumed that social media and web
portals that aggregate news restrict the diversity of content
that users are exposed to by tailoring news diets toward the
users’ preferences. In our empirical test of this argument, we
apply a random-effects within–between model to two large rep-
resentative datasets of individual web browsing histories. This
approach allows us to better encapsulate the effects of social
media and other intermediaries on news exposure. We find
strong evidence that intermediaries foster more varied online
news diets. The results call into question fears about the van-
ishing potential for incidental news exposure in digital media
environments.
news exposure |online media use |web tracking data
People can come across news and other internet offerings in
a variety of ways, for example, by visiting their favorite web-
sites, using search engines, or following recommendations from
contacts on social media (1). These routes do not necessarily
lead people to the same venues. While traditionally considered as
an important ingredient of well-functioning democratic societies,
getting news as a byproduct of other media-related activities
has been assumed to wane in the online sphere. Intermedi-
aries like social networking sites (SNS) and search engines are
regarded with particular suspicion, often criticized for fostering
news avoidance and selective exposure (2). This assumption has
been, perhaps most prominently, ingrained in the “filter bubble”
thesis, positing that search and recommendation algorithms bias
news diets toward users’ preferences and, thus, decrease content
diversity (3). On the other hand, incidental news exposure (INE)
due to other online activities has received much scholarly atten-
tion for several decades (4). Contrary to widely held assumptions,
recent INE research found that SNS users have more rather than
less diverse news diets than nonusers. For example, one study
showed that SNS users consumed almost twice the number of
news outlets in the previous week as did nonusers (2). Similar
results emerged regarding the use of web aggregators (portals)
and search engines, although people may use search engines in a
more goal-driven fashion compared to SNS (1).
In previous studies, SNS-based news exposure was typically
measured by asking respondents whether they are (unintention-
ally) exposed to news via social media. Like many survey studies,
this approach naturally suffers from the limited accuracy and
reliability of self-reports (5). More specifically, recent work has
criticized self-report measures for being biased toward active
news choices and routine use (6) and being particularly inaccu-
rate when people access news via intermediaries (7). To alleviate
these limitations, some studies have used log data to estimate
the quantity and quality of online news exposure, for exam-
ple, in terms of exposure to cross-cutting news (8, 9). However,
these studies have focused only on single social media plat-
forms instead of different intermediary routes to news. Other
recent studies (1, 10) have traced direct and indirect pathways
to online news using browser logs, but have not distinguished
nonregular—and therefore possibly incidental—news exposure
from regular, typically more intentional or routinized forms of
news consumption online. In other words, the question whether
visiting SNS more often (than usual) actually leads to more
varied news exposure (than usual) essentially remains unan-
swered. This problem concerns almost all studies on the use and
effects of online media, and has received considerable attention
in recent communication research (11). We argue that positive
within-person effects of visiting intermediary sites on online news
exposure are a necessary (although not sufficient, since even
nonregular visits could be intentional) precondition for INE,
and, therefore, testing for such effects is a useful endeavor. We
address this question using a statistical model that distinguishes
between stable between-person differences and within-person
effects, that is, the random-effects within–between (REWB)
model (12). Investigating within-person effects has additional
value by safeguarding causal inferences against bias due to (pre-
viously) unmeasured person-level confounders. We apply the
REWB model to two large, representative tracking datasets of
individual-level browsing behavior in Germany, collected inde-
pendently in 2012 and 2018. This allows us not only to compare
within- and between-person effects but also to analyze possible
changes in the effects of SNS (Facebook, Twitter) and interme-
diaries (Google, web portals) over recent years. Specifically, we
investigate their effects on the amount and variety of online news
exposure. Using this approach enables us to replicate and extend
two recent survey studies (2, 13) that looked at the effects of
SNS, web portals, and search engines on 1) overall online news
exposure and 2) the diversity of people’s online news diets.
Results
News accounted for only a very small portion of total site visits,
with an average of 1.51 news visits (SD = 5.61) per respondent
and day in 2012. News visits were more frequent in the 2018 sam-
ple, with a daily average of 2.51 (SD = 8.41), which is largely in
line with previous research (10). Accounting for between-person
differences using a logistic regression model with person-level
random intercepts yielded an estimated probability for a news
visit of 0.009 (99% CI 0.009 to 0.010) in 2012, and 0.014 (99%
CI 0.013 to 0.015) in 2018. Following previous studies (1, 10), we
estimated the effect of the previously visited site on the probabil-
ity of a news visit, and found positive and significant effects for
all intermediary platforms, most notably Facebook and Google
(Fig. 1). However, this clickstream-level analysis likely under-
estimates the effects of intermediaries, since indirect pathways
(e.g., bookmarking, revisiting news later) are ignored, and it
does not distinguish regular from nonregular online activities, as
mentioned above.
Author contributions: M.S. and F.M. designed research; M.S., F.M., S.S., and J.B. per-
formed research; M.S. and F.M. analyzed data; and M.S., F.M., S.S., and J.B. wrote the
paper.y
The authors declare no competing interest.y
This open access article is distributed under Creative Commons Attribution-NonCommercial-
NoDerivatives License 4.0 (CC BY-NC-ND).y
Data deposition: Replication data, code, and supplementary materials are available on
the Open Science Framework, https://osf.io/pqd9f/.y
1To whom correspondence may be addressed. Email: scharkow@uni-mainz.de.y
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Fig. 1. Probability of news site exposure, conditional on the previously
visited site. Estimated marginal probabilities and 99% CIs from two random-
effects logistic regression models with random intercepts and slopes for
respondents; n2012 =1, 254,490 site visits, and n2018 =1, 276, 519 site visits.
In a next step, we estimated four REWB panel models using
daily aggregated web tracking data. The point estimates and CIs
of the REWB models are displayed in Fig. 2. Looking at the
within-person effects in the upper part of the figure, there is
strong and consistent evidence that visiting SNS more often on
a given day increased the chance of being exposed to more news
outlets and more news overall. For example, for a respondent
in 2012 who visited Twitter twice as often as usual, we would
expect her to consume about 41% more news from about 28%
more online outlets. This positive effect, however, was signif-
icantly smaller in 2018. Using Google and other web portals
also had a strong positive effect on the amount and variety of
news exposure. Google visits had the largest and most consis-
tent within-person effect overall, while the large positive effects
of portals declined somewhat between 2012 and 2018. There was
also a positive effect of overall site visits on news exposure.
The REWB models also indicate that much online news expo-
sure is not incidental, but related to stable interindividual dif-
ferences in browsing behavior. These between-person effects are
displayed in the lower part of Fig. 2, and show that differences
in respondents’ news diets as well as overall news consumption
were strongly associated with the respondents’ regular use of
Facebook, Google, and other web portals. Respondents who
used these sites more often than other respondents were signifi-
cantly more likely to have a larger and more varied online news
diet. The large positive effects for SNS and online intermediaries
support previous findings indicating that respondents regularly
use these sites to get their news (2).
Overall, our results provide robust evidence for increased news
exposure due to SNS and intermediaries on the within-person
level. Looking at the differences in effect sizes of the within-
and between-person coefficients, we conclude that nonregular
intermediary use is not the main route to online news, but that
the intraindividual effects are substantial across two different
samples and time points. The two platforms often accused of
fostering selective exposure (14), Facebook and Google, were
consistently associated with a more varied news diet, on both the
within- and between-person levels, in addition to increasing the
overall amount of news exposure.
Conclusion
We used large-scale observational data to avoid the limited reli-
ability and validity of self-reports on news exposure. Leveraging
the potential of such data with the REWB model, our study pro-
vides strong evidence that getting more and more-diverse news
as a consequence of other media-related activities is a common
phenomenon in the online sphere. The findings contradict widely
held concerns that social media and web portals specifically con-
tribute to news avoidance and restrict the diversity of news diets.
Note that we followed previous studies and measured the vari-
ety of news diets by counting the number of outlets visited.
Given the overall low frequency of news visits, intermediaries
add diversity to the news diets of the large majority of partici-
pants with a small news repertoire (2). While we cannot say that
outlet variety always equals viewpoint variety, prior research has
shown that using a larger number of online news sources typi-
cally translates into more-diverse overall news exposure (15). In
contrast to previous studies (9, 10), we cannot quantify diver-
sity in terms of cross-cutting exposure, but note that previous
Fig. 2. Relation between browsing behavior and news exposure. Regression coefficients and 99% CIs from Poisson REWB models. Four separate models
were estimated for the two outcomes (number of news outlets visited and number of news visits) and the two samples (2012 and 2018). The models include
random intercepts and slopes for respondents, random intercepts for days, and OLRE to account for overdispersion. All predictors except age and gender
were log-transformed before estimation; n2012 =48, 919 person-days, and n2018 =40, 158 person-days.
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BRIEF REPORT
SOCIAL SCIENCES
studies have shown little evidence for strong partisan alignments
of news audiences in Germany (16) on the outlet level, so that
variety would have to be measured on the level of individual
news items, which requires URL-level tracking and content anal-
ysis data. In addition, future combinations of web tracking with
experience sampling surveys are needed to disentangle in what
instances nonregular news use is entirely nonintentional and
how the respective contents specifically affect the diversity in
news diets.
Materials and Methods
Samples. Our analysis is based on data from two representative samples of
German internet users aged 14 to 65 y who agreed to use a tracking soft-
ware that hooks into the web browsers on their desktop computers and/or
smartphone. For privacy reasons, respondents could temporarily disable the
tracking. The 2012 dataset was originally collected as part of a large, nation-
ally representative household panel (5). It contains the desktop browser
logs of n=2,970 respondents in November 2012. The average age of the
respondents was m=44.6 y, and 53.1% were female. The 2018 dataset was
drawn from an online access panel, with browser logs (desktop and mobile)
collected from n=2,035 respondents in December 2018. The average age
of the 2018 respondents was a little lower (m=41.6 y), as was the pro-
portion of female respondents (50.6%). In order to simplify comparisons
across samples, the datasets were matched in terms of the respondents’
age range.
Data collection was carried out by market research companies in accor-
dance with the ICC/ESOMAR International Code of marketing and Social
Research Practice (https://www.esomar.org). Informed consent was obtained
from the participants prior to participation.
Measures. Both the 2012 and 2018 data contain all logged visits from
the respondents’ web browser on the domain level (e.g., https://www.
spiegel.de). For the present analysis, we defined a visit with a threshold
of 10-s exposure (rather than 1 s or 3 s as in previous studies; ref. 6), in
order to establish that respondents had at least somewhat engaged with
a website. We compiled a list of 319 general interest news domains using
data from the German Audit Bureau of Circulation as well as a manual
inspection of the most frequently visited domains. Similarly, we defined
the relevant domains for web portal use (seven sites, such as Yahoo or
T-Online), as well as Facebook, Twitter, and Google. For the clickstream anal-
ysis, the coded log entries were analyzed. For the REWB model, the number
of news visits and number of news outlets visited, as well as Facebook, Twit-
ter, Google and portal visits, were counted per respondent and day, yielding
a panel dataset with a maximum of k=31 repeated measurements of
browser use.
Data Analysis. In order to account for between- and within-person associ-
ations of browsing behavior and news exposure, we estimated an REWB
model (12). For a single predictor variable x,irespondents, and trepeated
measurements, the REWB model is specified as
yit =µ+β1W(xit −xi)+ β2Bxi+vi0+vi1(xit −xi)+ it0
with β1Was the within-person effect and β2Bas the between-person
effect. In addition to random intercepts for respondents vi0, the model
also includes random slopes vi1for the within-person effect, following cur-
rent recommendations for conservative fixed effects estimates (12). We
expanded the linear REWB model in two regards: Since the outcomes are
count variables, we estimated a Poisson rather than a linear model. More-
over, we log-transformed all predictor variables from the web tracking data,
because we expected diminishing returns for additional site visits. The mod-
els also include random intercepts for days, as well as observation-level
random effects (OLRE) to account for overdispersion. Total visits (minus the
intermediary sites) were included as a predictor to control for the conflation
of the associations between news website use and the use of intermediaries
with general internet use intensity.
Data Availability. Replication data and code are available on the Open
Science Framework, https://osf.io/pqd9f/ (17).
ACKNOWLEDGMENTS. M.S. thanks GfK Germany for providing survey and
log data from their Media Efficiency Panel. J.B. and S.S. thank Pascal Siegers
for his contribution to the collection of the 2018 data. We thank Marko
Bachl for helpful comments on the statistical models.
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