Public Understanding of Science
2019, Vol. 28(7) 759 –777
© The Author(s) 2019
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P U S
Fostering public trust in science:
The role of social media
University of Vienna, Austria
The University of Alabama, USA
Homero Gil de Zúñiga
University of Vienna, Austria; Universidad Diego Portales, Chile
Massey University, New Zealand
The growing importance of social media for getting science news has raised questions about whether these
online platforms foster or hinder public trust in science. Employing multilevel modeling, this study leverages
a 20-country survey to examine the relationship between social media news use and trust in science. Results
show a positive relationship between these variables across countries. Moreover, the between-country
variation in this relationship is related to two cultural characteristics of a country, individualism/collectivism
and power distance.
comparative research, cross-cultural indicators, Hofstede, science communication, social media, trust in
Nowadays, the public increasingly gets science news online, particularly via social media such as
Twitter, Facebook, or YouTube (Brossard, 2013). For example, people in the United States cite the
Internet as their primary science and technology information source (National Science Board,
2016). Some scholars have expressed concerns regarding social media’s growing impact on sci-
ence news by asking whether a lack of quality control online threatens public trust in science
(Weingart and Guenther, 2016). Social media are not only used to share new scientific insights but
Brigitte Huber, Department of Communication, University of Vienna, Währinger Str. 29, Vienna A-1090, Austria.
869097PUS0010.1177/0963662519869097Public Understanding of ScienceHuber et al.
760 Public Understanding of Science 28(7)
also to spread scientific misinformation (Allgaier, 2016; Liang et al., 2014). Social media have
been used by individuals or groups to negatively influence public opinion about science-related
topics such as vaccination (Dunn et al., 2015) or climate change (Jang and Hart, 2015).
However, there also are good theoretical reasons to expect a positive relationship between social
media news use and trust in science. Not only do social media have the potential to correct misin-
formation (Vraga and Bode, 2017), they also expand information networks (Bakshy et al., 2015;
Barnidge, 2015; Kim et al., 2013) and promote user engagement with content posted by trusted
social contacts (Bonchi et al., 2013; Media Insight Project, 2017; Wang and Mark, 2013).
Scholars have only just begun to explore the wide range of online formats and platforms used
for science communication (Davies and Hara, 2017), and few studies to date have examined social
media from a cross-national perspective. Our study fills this gap in the literature by testing the
relationship between social media news use and public trust in science in 20 countries worldwide.
As Schäfer (2017) points out, findings from the United States are only partially translatable to
other regions due to differences regarding the relevance of online science communication and the
ways in which scientific topics are debated. Hence, scholars and science communicators around
the world will benefit from the insights provided by cross-cultural research by gaining a better
understanding of whether key relationships are consistent across national contexts.
1. Trust in science
The trustworthiness of science is often debated in public, and the narrative that science is not trust-
worthy has taken hold. For instance, headlines such as “Americans’ increasing distrust of science”
(Blake, 2015) or “The challenge of fighting mistrust in science” (Beck, 2017) create an image of a
public that trusts science less and less. While some of the public debates about science arise from
specific scientific misconduct cases, others are driven by a generalized lack of belief in science,
particularly science related to climate change or health. But why is trust so important? First, scien-
tific knowledge is a critical resource that enables political actors to inform and legitimate political
decisions (Bogner and Torgersen, 2005), and it is also important for laypeople in terms of forming
public opinion about important political issues. Therefore, distrust in science can be problematic
for society as a whole. For example, people who do not believe in anthropogenic climate change
will see no need to take political action to slow its progress. Second, science depends on people’s
willingness to participate in research projects (Medical Research Council, 2016), and declining
trust in science could diminish that willingness. Much research would simply not be possible with-
out survey respondents, experimental participants, focus group discussants, and so on. Third, sci-
ence also depends on public funding. Specific types of scientific research could be limited if people
think that money invested in it is unnecessary or wasteful (Huber et al., 2019).
Definition and dimensions of trust
Trust is essential to democratic societies (Barber, 1987) because it helps reduce social complexity
(Luhmann, 1989). Trust can be defined as “the probability that [someone] will perform an action
that is beneficial or at least not detrimental to us is high enough for us to consider engaging in some
form of cooperation with [them]” (Gambetta, 1988: 217). Prior literature suggests that trust in sci-
ence is a multidimensional concept (Achterberg et al., 2017; Miller, 2004). More specifically,
people assess scientific institutions differently from scientific principles and methods. Some peo-
ple trust principles and methods but distrust institutions (Achterberg et al., 2017). While support
for principles and methods is generally high (Miller, 2004), there is a growing distrust in scientific
authorities (Aupers, 2012). Because the current study focuses on the question of fostering trust in
Huber et al. 761
science, we examine trust in scientific institutions and scientists rather than trust in principles and
methods, which is relatively stable.
Predictors of trust in science
Since the 1980s, the concept of trust in science has increasingly attracted scholarly attention (see,
for example, Evans and Durant, 1989; Ziman, 1991), and it remains a popular research subject
today (e.g. Achterberg et al., 2017; Brewer and Ley, 2013; Liu and Priest, 2009; Myers et al.,
2017). Research has identified a wide range of factors predicting trust in science, including age
(Anderson et al., 2012), gender (Von Roten, 2004), political ideology (Gauchat, 2012), and religi-
osity (Brewer and Ley, 2013; Liu and Priest, 2009), and results show that younger, liberal, non-
religious men trust science more. Moreover, research shows that education (Bak, 2001; Hayes and
Tariq, 2000), income (Anderson et al., 2012), and science knowledge (Evans and Durant, 1995;
Nisbet et al., 2002) positively predict trust in science. Moreover, media use was found to be an
important predictor: Heavy TV viewing (Gerbner, 1987; Nisbet et al., 2002) and conservative news
media use (Hmielowski et al., 2014) negatively correlate with trust in science. The opposite is true
for non-conservative news media use (Hmielowski et al., 2014), as well as newspaper use and
Internet use (Dudo et al., 2011).
2. Social media news use and trust in science
While there is a large body of literature investigating the relationship between traditional media use
and attitudes toward science (e.g. Anderson et al., 2012; Dudo et al., 2011; Gerbner, 1987;
Hmielowski et al., 2014; Nisbet et al., 2002; Scheufele and Lewenstein, 2005; Taddicken, 2013) or
online media use and attitudes toward science (Dudo et al., 2011; Su et al., 2015), less research has
been conducted on social media. Still, this prior research on traditional news use and online news
use provides an important baseline for theorizing about the relationship between social media news
use and public trust in science. For example, research has shown that online media use increases
science knowledge (Cacciatore et al., 2014; Su et al., 2015) and positive attitudes toward science
(Dudo et al., 2011). Other studies show that science news framing influences science information
processing (Scheufele and Lewenstein, 2005) and that habitual media use cultivates perceptions
about science and the scientific process (Gerbner, 1987; Nisbet et al., 2002). Thus, traditional news
has relatively strong effects on trust in science.
There are several reasons why social media news use may have a stronger relationship with trust
in science than traditional or online news use. First, social media diversify and expand information
networks (Bakshy et al., 2015; Barnidge, 2015; Kim et al., 2013). Social media users have a greater
chance of encountering science news than non-users because they are exposed through incidental
exposure in addition to active news seeking; both forms of news use are positively related to
engagement with news content (Oeldorf-Hirsch, 2018). Accordingly, social media news users may
be exposed to and engage with a greater volume and a broader range of science news, and this
heightened exposure fosters trust in science (Nisbet et al., 2002). Second, social media news is
supplemented by social recommendations (Bode, 2016; Thorson and Wells, 2015), which affect
news engagement (Messing and Westwood, 2012). People engage with news posted by people they
trust (Media Insight Project, 2017), people with whom they perceive similarity (Bonchi et al.,
2013), or people to whom they feel closer (Ganley and Lampe, 2009; Wang and Mark, 2013).
Therefore, people are more likely to trust the science news on social media because it was likely
posted by a social contact they trust. Finally, scientists and universities increasingly rely on social
media to interact with users (Collins et al., 2016; Darling et al., 2013; Liang et al., 2014; Peters
762 Public Understanding of Science 28(7)
et al., 2014). Rather than receiving science news from journalists, social media users also get sci-
ence news directly from experts. If people have the choice, they prefer scientists to present scien-
tific information rather than journalists because it is perceived as more trustworthy, more precise,
and more objective (Special Eurobarometer, 2007). Moreover, the author’s authority has a positive
effect on trust in information (Sbaffi and Rowley, 2017).1 For these reasons, it is hypothesized that
social media news use will be positively related to trust in science across all 20 countries. Thus, the
first hypothesis reads as follows:
H1: Social media news use will be positively related to trust in science.
(Science) news use worldwide. While in some countries, nearly three-quarters of the population
access news via social media (e.g. Argentina: 72%; Brazil: 66%), in other countries, less than half
of the population does so (UK: 39%; US: 45%; see Newman et al., 2018). Hence, online news
consumption is not the same worldwide. These same claims can be made about science news use,
specifically. One can observe “significant shifts among audiences away from traditional news
[. . .] as primary source for scientific information and towards news diets that are heavily supple-
mented by or rely exclusively on online sources” (Scheufele, 2013: 14041). This trend is also
evolving differently around the globe. In the United States, for example, more people used the
Internet than TV to learn about science and technology by 2010 (National Science Board, 2016).
However, the shift from traditional media to online sources has not progressed as far in Europe
(Special Eurobarometer 468; see European Union, 2017). When looking at implications of tradi-
tional science news use, one can expect to find differences between countries based on the amount
of news available, the framing of stories, and so on. When it comes to social media news, one also
has to consider differential social media use, differential emphasis on user comments and social
opinion formation, and different attitudes toward authorities.
Cross-cultural indicators. The Hofstede model is widely used in comparative cultural research
(Hofstede, 1980, 2001; Hofstede et al., 2010). The model offers a six-dimensional typology of
indicators that characterize national cultures: power distance, individualism/collectivism, uncer-
tainty avoidance, masculinity/femininity, long-/short-term orientation, and indulgence/restraints.
The model has been subjected to criticism: besides the countries included, the age of the data,
and the number of dimensions the model should contain,2 scholars have criticized the model for
attempting cultural quantification and using national culture as a causal factor of individual
behavior (Baskerville, 2003; McSweeney, 2002). Hofstede (2002), as well as other scholars,
have provided arguments and empirical research to address these points of criticism. For exam-
ple, Hofstede (2002) increased the numbers of dimensions, and the updated model has been vali-
dated through replication studies. Taras (2017) concluded, “His model may not be perfect, but it
remains the most popular and nothing revolutionary or remarkably better has been offered in the
decades since it was introduced” (p. 4). When it comes to social media, prior research has shown
that the power distance and individualism/collectivism dimensions are particularly important in
terms of explaining cross-cultural differences in a range of outcomes (e.g. Goodrich and De
Mooij, 2014; Yang and Kang, 2015). Therefore, the current study focuses on these two
Power distance index (PDI). Power distance is the extent to which less powerful members in soci-
ety accept that power is distributed unequally (Hofstede, 2001). In countries with low PDI scores,
Huber et al. 763
people see inequality as a negative aspect of society that should be minimized, and they believe
that the use of power should be legitimate. In countries with high PDI scores, people see inequal-
ity as a fact of life, and they believe power dynamics are basic aspects of the social order that do
not require legitimacy. PDI scores tend to be higher in Eastern Europe, Latin Europe and Latin
America, Asia, and Africa. German-speaking and English-speaking countries tend to score lower.
Individualism (IDV). Individualism is the degree to which people are integrated into social groups
and networks (Hofstede, 2001). In more individualistic societies, the ties between individuals are
looser and less dense, and individuals prioritize the needs of themselves and their immediate fami-
lies. In more collectivistic societies, individuals are integrated into dense, cohesive groups and
networks, and the needs of the collective are a relatively stronger priority than in individualistic
societies. IDV scores are higher in developed and/or Western countries and lower in less developed
and Eastern countries.
Social media news use and culture
Prior research shows that Hofstede’s (2001) cross-cultural indicators influence how people use
social media. Cross-cultural indicators not only affect users’ motivations for using social media
(e.g. Kim et al., 2011; Vasalou et al., 2010) but also the importance they place on using it (Jackson
and Wang, 2013; Shneor and Efrat, 2014) and the composition of their social networks (e.g. Choi
et al., 2011). Because scholars have only just begun to connect Hofstede’s cross-cultural indicators
to country-level differences in news use (Wei et al., 2012), we draw instead from research that
focuses on cross-cultural indicators and various forms of social media use. These findings on gen-
eral social media use are helpful when theorizing about social media news use because people tend
to stumble upon the news in the natural course of communicating and connecting with others on
Wei et al. (2012) tested how IDV is related to online news use and social media use in China and
the United States. Interestingly, while it less helpful in explaining online news use, it is related to
social media use. IDV could therefore influence how people use social media for news, as well. In
the United States, which is relatively more individualistic, social media users are motivated more
by entertainment than by social relationships; meanwhile students in Korea, which is relatively
more collectivistic, are motivated more by social relationships than by entertainment (Kim et al.,
2011). Similarly, social media users in individualistic countries like the United Kingdom, the
United States, or Australia are less likely to use social media for purchasing decisions than collec-
tivistic countries like China and Thailand, where social media are more central for opinion forma-
tion (Goodrich and De Mooij, 2014).
IDV could therefore affect the relationship between social media news use and trust in science.
Specifically, the relationship should be stronger in collectivistic cultures because social media
users in these cultures place higher importance on the recommendations of others, which should
theoretically increase the trust they have in the science news they encounter. Accordingly, we for-
mulated the following hypothesis:
H2: The positive relationship between social media news use and trust in science (H1) will be
relatively stronger in collectivistic countries than individualistic countries.
Likewise, prior research shows that PDI plays a key role in explaining cross-cultural differences
in human behavior. People in high-PDI countries tend to be more accepting of authority and prefer
more guidance from superiors, than people in low-PDI countries (Bochner and Hesketh, 1994). For
764 Public Understanding of Science 28(7)
example, corporate employees in low-PDI countries respond more unfavorably when left out of
decision-making processes than employees in high-PDI countries (Brockner et al., 2001). Similarly,
employees in low-PDI countries are more likely to take initiative without supervision than people
in high-PDI countries (Van der Vegt et al., 2005). Variation in PDI could lead to variation in trust
in authority figures including scientists and universities. For example, one study found that White
Americans, who come from a low-PDI culture, were less likely to believe the US Surgeon General’s
anti-alcohol messaging than Mexican Americans, who come from a cultural background with
higher PDI (Perea and Slater, 1999). Thus, when it comes to science news on social media, direct
access to science news and information from scientists and universities should have a stronger
relationship with trust in science in high-PDI countries than in countries with low PDI. Accordingly,
our third hypothesis reads as follows:
H3: The positive relationship between social media news use and trust in science (H1) will be
relatively stronger in high-PDI countries than it is in low-PDI countries.
These two cultural dimensions, IDV and PDI, represent different but interrelated dimensions of
how people interact with messages: IDV focuses on the importance people place on the opinions
of others, while PDI represents the degree to which people are willing to accept the opinions of
authority figures. But while these dimensions may be distinct, they may also interact. For example,
one study found that in collectivistic countries with high PDI, people are less active information
seekers and place higher importance on the opinions of others (Goodrich and De Mooij, 2014).
Meanwhile, the opposite is true for people in individualistic countries with low PDI, where people
place more importance on individualistic information seeking than they do on the opinions of oth-
ers. Therefore, when it comes to science news on social media, where people get science informa-
tion both from trusted others and from authority figures, there are good reasons to expect the IDV
and PDI will interact to shape the relationship between social media news use and trust in science.
In high-IDV/low-PDI countries, people will be less likely to place importance on the opinions of
others and more likely to seek non-authoritarian information. Meanwhile, the opposite should be
true in low-IDV/high-PDI countries, where people will be more likely to place importance on oth-
ers’ opinions and to seek authoritarian information. Therefore, we hypothesize that the relationship
between social media news use and trust in science will be the strongest in countries with low IDV
and high PDI, and it will be the weakest in countries with high IDV and low PDI. Thus, our last
hypothesis reads as follows:
H4: The positive relationship between social media news use and trust in science (H1) will be
relatively stronger in collectivistic countries with high PDI and relative weaker in individualis-
tic countries with low PDI.
Sample and data
This study relies on survey data collected in 20 countries (for the list of countries, see Table 1).
The data stem from the project Digital Influence, a collaboration between researchers at the
University of Vienna (Austria) and Massey University (New Zealand). One main challenge in
conducting this international research project was to achieve the most comparable and reliable
data set among different countries with different languages. For this purpose, researchers relied
on a large group of participating scholars from each country involved to perform the translation
Huber et al. 765
of all items. Researchers at University of Vienna performed the survey administration by using
the online poll survey platform Qualtrics. The study was fielded online between September 14
and 24, 2015. The research group partnered with Nielsen. Nielsen used stratified quota sam-
pling technique to create samples whose demographics closely match those reported by official
census agencies in each country (see Callegaro et al., 2014). The total sample size is N = 21,321,
and individual country sample sizes range from 943 at the lowest (Korea) and 1223 (Ukraine)
at the highest. Overall cooperation rate was relatively high, averaging 77% across the panel
(American Association for Public Opinion Research, 2011; CR3). For more information on the
sample and a demographic breakdown by country, see (Gil de Zúñiga et al., 2017).
Trust in science. The dependent variable in the analysis is trust in science. Based on prior research
(Brewer and Ley, 2013; Nisbet and Goidel, 2007), this variable relies on two questionnaire items3
that ask respondents to rate their feelings of trust toward particular actors or institutions (0 = “No
Trust,” 6 = “A Great Deal of Trust”) toward (a) scientists and (b) universities. These two items are
highly correlated (r = .77), and therefore the final variable took the average of the two scores
(M = 3.42, SD = 1.41).
Table 1. Tests of mean differences between each country mean and the grand mean for trust in science.
Country Trust in science
M (SD)t (df)
Argentina 4.11 (1.37)+17.07 (1143)*
Brazil 3.26 (1.60)− −3.28 (1084)*
Chile 3.37 (1.42) −1.11 (961)
China 3.36 (1.37) −1.44 (1002)
Estonia 4.06 (1.08)+20.21 (1164)*
Germany 3.43 (1.41) 0.20 (1084)
Indonesia 3.60 (1.22)+4.89 (1075)*
Italy 3.52 (1.47)+2.15 (1037)*
Japan 2.73 (1.22)− −17.77 (974)*
Korea 2.81 (1.26)− −14.97 (940)*
New Zealand 3.60 (1.28)+4.65 (1155)*
The Philippines 3.56 (1.23)+3.74 (1056)*
Poland 3.13 (1.43)− −6.60 (1059)*
Russia 3.38 (1.44) −0.90 (1142)
Spain 3.89 (1.41)+10.46 (1017)*
Taiwan 2.42 (1.33)− −23.84 (1003)*
Turkey 3.72 (1.46)+6.19 (954)*
Ukraine 3.46 (1.31) 0.99 (1216)
The United Kingdom 3.44 (1.33) 0.40 (1063)
The United States 3.32 (1.40)− −2.41 (1160)*
Notes. Cell entries are means (M), standard deviations (SD), test statistics (t) and degrees freedom (df) from one-sample
t-tests assessing the difference between each country mean and the grand mean for trust in science (M = 3.42, SD = 1.41).
+ or − signs denote whether the difference with the grand mean is a positive or a negative one.
Significance values are indicated as follows: *p < .05 (two-tailed tests).
766 Public Understanding of Science 28(7)
Social media news use. Based on prior research (Gil de Zúñiga et al., 2012; Valenzuela et al., 2012),
we asked respondents how often they use social media to (a) get news, (b) stay informed about
current events and public affairs, (c) get news about their local communities, and (d) get news
about current events from mainstream media. These four items, which were measured on 7-point
scales (0 = “Never,” 6 = “All the Time”), form a reliable scale (Cronbach’s α = .865, M = 3.33,
SD = 1.51).
Control variables. The study controlled for an array of variables that prior studies have identified as
having an influence (demographics, political ideology, science knowledge, religiosity, traditional
news use; for details, see Supplementary Appendix Table A1).
We included PDI and Individualism (IDV) as macro variables in our analysis (for details, see
Supplementary Appendix Table A1).
First, one-sample t-tests were used to test whether each country’s mean for trust in science is sta-
tistically different from the overall (grand) mean across the 20 countries.4 Next, a series of log-
likelihood model comparisons were used to establish the most appropriate multi-level model for
the data. A fixed intercept null model was compared to a random intercept model. This comparison
is useful for establishing whether, without accounting for control variables, the mean of trust in
science significantly varies across countries. A full model with a random intercept was then com-
pared to a full model with random slopes, which establishes that, accounting for the controls, the
effect of social media news use varies randomly across countries. Once the appropriate model was
determined, multi-level modeling was conducted. The between-country variance was first assessed
with a random slope model, before moving on to test the cross-level interactions between social
media news use and PDI and IDV.
One-sample t-tests were first conducted to assess each country’s difference with the overall sample
in terms of mean levels of trust in science (M = 3.42, SD = 1.41). Results are summarized in Table
1, and means are illustrated in Figure A1 in the Supplementary Appendix. The highest test statistics
(indicating country means greater than the grand mean) are seen in Estonia (20.21), Argentina
(17.07), and Spain (10.46). Meanwhile, the lowest test statistics are seen in Taiwan (−23.84), Japan
(−17.77), and Korea (−14.97). Finally, non-significant test statistics (indicating a country mean
close to the grand mean) are observed in Germany (.20), the United Kingdom (.40), Russia (−.90),
Ukraine (.99), Chile (−1.11), and China (−1.44).
Figure 1 plots the PDI and individualism (IDV) index scores by country. Because these scales
have been standardized for the purposes of this visualization, the specific scores for each country
are not as meaningful as the relative distance to other scores. The highest scoring countries on PDI
(indicating more inequality, or less equality) include the Philippines, Russia, and Ukraine. The
lowest scoring countries are New Zealand, the United Kingdom, Germany, the United States, and
Estonia. Countries with average PDI include Taiwan, Spain, and Chile. For IDV, the United States,
the United Kingdom, New Zealand, and Italy score the highest while Indonesia, Taiwan, Korea,
and China score the lowest. Meanwhile, Argentina and Japan score close to the mean.
Huber et al. 767
A series of model comparisons was conducted to establish the most suitable model for the data.
Results are summarized in Table A2 in the Supplementary Appendix. First, a null model with a
random intercept (i.e. a model with no predictors and a random intercept) is a better fit (log likeli-
hood = −36,708.31) than a null model with a fixed intercept (log likelihood = −37,538.22), which
indicates that, without accounting for the predictors, mean levels of trust in science vary from
country to country. Next, results show that a full model with a random slope (i.e. a model including
predictors and a random slope for social media news use) is a better fit to the data (log likeli-
hood = −33,534.29) than a similar model with a fixed effect for social media news use (log likeli-
hood = −33,563.17). This result indicates that the effect for social media news use significantly
varies from country to country.
Having established that a random slope model is the best fit to the data, we proceeded to test H1,
which predicts an overall positive relationship between social media news use on trust in science.
Results, which are shown in the first column of Table 2, support this prediction, showing a statisti-
cally significant and positive coefficient (B = .13, SE = 0.02, p < .001). Moreover, this relationship
varies in magnitude across countries with a standard deviation of .08, indicating that the result is
strongly positive (+2 SD = 0.29) in some countries and non-significant in others (−2 SD = −0.03).
The second model in Table 2 models this between-country variation in the relationship between
social media news use and trust in science. The model estimates a fixed intercept—which can be
interpreted as the grand mean of trust in science adjusted at the mean of all predictors—of 2.66
(SE = 0.78). This mean varies between countries with a standard deviation of 0.34, which indicates
that in 96% of countries (approximately 19 of 20), the adjusted mean for trust in science falls
between 1.98 and 3.34 (Minimum = 0, Maximum = 6). The fixed coefficient for social media news
use is non-significant, owing to the presence of the cross-level interaction terms. Neither second-
level predictor is independently statistically significant in this model.
The first interaction between social media news use and PDI is significant with B = .01
(SE = 0.00), but the second and third interactions are not statistically significant (for social media
news use by PDI: B = .00, SE = 0.00, n.s. and for PDI by IDV: B = .00, SE = 0.00, n.s.). However, the
three-way interaction (social media news use by PDI by IDV) is statistically significant (B = −.01,
SE = 0.00, p < .001). This three-way interaction is illustrated in Figure 2, which shows that the
Figure 1. Country scores on the power distance index (PDI) and the individualism index (IDV).
768 Public Understanding of Science 28(7)
relationship between social media news use and trust in science is strongest where PDI is also
high—but only in collectivistic countries (i.e. where IDV is low). These results support H3 and H4,
but not H2.
This study tested the relationship between social media news use and trust in science in 20 coun-
tries worldwide. Results show a positive relationship between social media news use and trust in
science across different societies. Social media news use is more strongly related to trust in science
than traditional news use (the difference in betas strength based on z-score test is significant at
p < .001). Social media expand and diversity information networks (e.g. Bakshy et al., 2015), pro-
mote engagement with news posted by trusted social contacts (e.g. Media Insight Project, 2017),
and provide direct access to science news posted by scientists and universities (e.g. Collins et al.,
2016; Darling et al., 2013). It is unclear which of these three mechanisms is at play (an important
limitation to our study); it could be that all three mechanisms work together.
Table 2. The relationship between social media news use and trust in science with and without cross-
Variable Trust in science
Random effects SD
Intercept 0.34 0.34
Social media news use 0.08 0.06
Residual 1.31 1.31
Fixed effects B (SE)
Intercept 2.87 (0.51)*** 2.66 (0.78)***
Age 0.01 (0.00)*** 0.01 (0.00)***
Gender (1 = female) −0.12 (0.02)*** −0.12 (0.02)***
Education 0.04 (0.01)*** 0.04 (0.01)***
Socio-economic status 0.20 (0.01)*** 0.20 (0.01)***
Ideological extremity 0.04 (0.01)*** 0.04 (0.01)***
Religiosity −0.06 (0.01)*** −0.06 (0.01)***
Science knowledge 0.17 (0.02)*** 0.17 (0.02)***
Traditional news use 0.05 (0.01)*** 0.05 (0.01)***
Social media news use 0.13 (0.02)*** −0.10 (0.15)
Power distance index 0.00 (0.01) 0.01 (0.01)
Individualism 0.01 (0.00) 0.01 (0.01)
Cross-level interactions B (SE)
Social media news use × power distance index − 0.01 (0.00)*
Social media news use × individualism − 0.00 (0.00)
Power distance index × individualism − 0.00 (0.00)
Social media news use × power distance index ×
− −0.01 (0.00)*
AIC 67,098.42 67,095.69
BIC 67,224.75 67,253.60
Log likelihood −33,533.21 −33,527.84
AIC: Akaike information criterion; BIC: Bayesian information criterion; HLM: hierarchical linear model.
Cell entries are parameters from a random slope HLM with a cross-level interaction. n = 19,841, groups = 20.
Significance values are indicated as follows: *p < .05; ** p < .01; *** p < .001 (two-tailed tests).
Huber et al. 769
Figure 2. The relationship between social media news use and trust in science at three levels of the
Power Distance Index (left = low, right = high) and Individualism (top = low, bottom = high).
770 Public Understanding of Science 28(7)
First, social media make it more likely that people will encounter science news in the first place,
whether through active news seeking or incidental exposure, both of which are positively related
to engagement with news (Oeldorf-Hirsch, 2018). Second, the social recommendations that accom-
pany science news in social media environments could increase the credibility of the story or
counteract mistrust based on ideological tendencies (Bode, 2016; Messing and Westwood, 2012).
Finally, social media give users the opportunity to receive science news directly from scientists and
institutions engaged in science research, which are inherently more trustworthy than news organi-
zations (Sbaffi and Rowley, 2017).
However, this conclusion comes with an important caveat. This study has examined trust in sci-
ence based on exposure to social media news regardless of the quality of the information.
Misinformation and fake news have become increasingly prevalent on social media (Allcott and
Gentzkow, 2017), including misinformation about scientific findings (Allgaier, 2016; Liang et al.,
2014). Hence, important questions for future research are how to deal with scientific misinforma-
tion on social media (Vraga and Bode, 2017) and how to deal with incivility in social media discus-
sions about science (Anderson and Huntington, 2017). Circulating science news on social media
and interacting with the public is a challenging task which entails risks, and not all researchers and
their institutions are prepared to take on those risks (Bucchi, 2017). Moreover, recent research sug-
gests that researchers and their institutions do not fully utilize the dialogic potential of social media
(e.g. Jia et al., 2017; Lee et al., 2018), and science communicators have only just started to inte-
grate two-way communication strategies into training programs (Yuan et al., 2017). Hence, future
research should focus on two-way communication between scientists and the public and investi-
gate its association with trust in science.
Second, the results of the current study indicate that the relationship between social media news
use and trust in science is the strongest in collectivistic countries with high power distance. These
differences may be explained by how these cultural indicators affect the ways in which people
engage with information posted on social media. People in collectivistic countries are more likely
to place high importance on the opinions of others (Goodrich and De Mooij, 2014), and people in
high-PDI countries are more likely to trust information obtained directly from authority figures
(Perea and Slater, 1999). Because social media afford the opportunity for users to engage with sci-
ence news posted by trusted others and by scientists and universities, these tendencies interact to
make people in low-IDV/high-PDI countries more likely to trust the science news they encounter
in social media environments.
These insights are important for science communicators, especially for those who are engaged in
transnational communication. Culture plays a significant role in shaping the dialogue between organ-
izations and publics in online environment in different countries (Men and Tsai, 2012). Specifically,
social media could have a stronger positive impact on scientific information campaigns in collectiv-
istic countries with high PDI, including, for example China or Indonesia. These countries tend to be
more accepting of social and institutional hierarchies, and they tend to have more of a collectivistic
mind-set. As such, science messages may be more effective in these contexts if they play to the
authoritativeness of scientists or scientific institution. Appeals to collective benefits to the society
may also be particularly effective in these contexts. However, these strategies may be less effective in
individualistic countries with low PDI, including, for example, Germany or the United States. Future
research should focus on uncovering which components of science communication on social media
may be effective in different contexts. For example, a message effective in some countries might irri-
tate people in other countries due to violation of cultural norms. Hence, future studies should also test
how emotions while reading science news on social media relate to trust in the information and trust in
science, and contribute to the emerging research on emotions, humor, and entertainment in science
communication (e.g. Bore and Reid, 2014; Simis-Wilkinson et al., 2018).
Huber et al. 771
These conclusions are limited in several ways. Social media news use was measured by using
generic wording (“social media”), rather than wording about specific social media platforms. In
addition, we measured general social media news use and not science news, specifically.
Nonetheless, there is good reason to assume that our respondents encountered science news. First,
science coverage is not limited to science sections; rather, scientific findings and scientists’ state-
ments are an integral part of general news (e.g. Brantner and Huber, 2013; Elmer et al., 2008).
Second, survey data indicate that around half of social media news users regularly see posts about
science (Pew Research Center, 2015). Third, recent research shows that it is quite common to share
links to science and research on Facebook (Hargittai et al., 2018): 44% of young adults do so.
Hence, it is quite likely that social media news users encounter science news. However, future
studies could focus specifically on social media use for science news and differentiate between
getting science news from mainstream media accounts via social media and getting news directly
from scientists on social media.
Moreover, cross-level interactions in multi-level regression are notoriously difficult to detect
(see, for example, Mathieu et al., 2012), because doing so requires at least 15 second-level groups
to have enough statistical power. Given this understanding of multi-level analysis, we would argue
that detecting any cross-level interaction is a noteworthy finding. That said, the readers should
interpret these small effect sizes with caution. Finally, our study is based on cross-sectional data
and, therefore, do not allow for causal inferences.
Despite these limitations, our study shows relatively strong evidence across 20 countries about
the positive relationship between social media news use and trust in science. In addition, it points
out the role of Hofstede’s (2001) cultural dimensions individualism/collectivism and power dis-
tance in shaping this relationship: The potential of social media to foster public trust in science
seems to be especially high in collectivistic countries with a large power distance.
Declaration of conflicting interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship and/or publi-
cation of this article.
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publica-
tion of this article: This research was supported by Grant FA2386-15-1-0003 from the Asian Office of
Aerospace Research and Development. Responsibility for the information and views set out in this study lies
entirely with the authors.
Brigitte Huber https://orcid.org/0000-0002-9070-4962
Matthew Barnidge https://orcid.org/0000-0002-0683-3850
Homero Gil de Zúñiga https://orcid.org/0000-0002-4187-3604
Supplemental material for this article is available online.
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2. For more details on critiques of the Hofstede model, see Taras (2017).
772 Public Understanding of Science 28(7)
3. Some scholars suggest a multidimensional measurement of trust (see Hendriks et al., 2015). However,
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dependent variable to changes in the independent variable (Lin et al., 2013). The p values on the cross-
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Brigitte Huber (PhD, University of Vienna) is a Post Doc at the Media Innovation Lab of the Department of
Communication at the University of Vienna. Her research interests include science communication, political
communication, journalism studies, and social media. E-mail: firstname.lastname@example.org.
Matthew Barnidge (PhD, University of Wisconsin–Madison) is an Assistant Professor in the Department of
Journalism & Creative Media at the University of Alabama, where he directs the Emerging Media Research
Group. He specializes in emerging news media and contentious political communication with an international
perspective. E-mail: email@example.com.
Homero Gil de Zúñiga (PhD, University of Wisconsin–Madison) is the Medienwandel Professor in the
Department of Communication at the University of Vienna, and Research Fellow at Departamento de
Comunicación y Letras, Universidad Diego Portales, Chile. His research addresses the influence of new tech-
nologies and digital media on people’s daily lives and the overall democratic process. E-mail: homero.gil.
James Liu (PhD, UCLA) is professor and head of the School of Psychology at Massey University in New
Zealand. His research is in cross-cultural, social, and political psychology, specializing in social representa-
tions of history and their relationship to identity, prejudice, and international relations. He has more recent
interests in global consciousness and digital influence—how systems like liberal democracy and hierarchical
relationalism function to create global social order. E-mail: firstname.lastname@example.org.