ArticlePDF Available

Abstract and Figures

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.
Content may be subject to copyright.
Public Understanding of Science
2019, Vol. 28(7) 759 –777
© The Author(s) 2019
Article reuse guidelines:
DOI: 10.1177/0963662519869097
Fostering public trust in science:
The role of social media
Brigitte Huber
University of Vienna, Austria
Matthew Barnidge
The University of Alabama, USA
Homero Gil de Zúñiga
University of Vienna, Austria; Universidad Diego Portales, Chile
James Liu
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
Corresponding author:
Brigitte Huber, Department of Communication, University of Vienna, Währinger Str. 29, Vienna A-1090, Austria.
869097PUS0010.1177/0963662519869097Public Understanding of ScienceHuber et al.
Theoretical/research paper
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.
International comparison
(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
social media.
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.
3. Method
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).
Individual-level measures
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).
Country-level measures
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.
4. Results
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.
5. Discussion
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-
level interactions.
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
Matthew Barnidge
Homero Gil de Zúñiga
Supplemental material
Supplemental material for this article is available online.
1. For a more detailed overview on trust and credibility in online environment, see Choi and Stvilia (2015),
Fogg et al. (2001), and Sundar (2008).
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,
in standardized surveys, it is common to assess trust in science by using two questions or even a single
question; the merit from such a measurement is that it can easily be compared across countries (Schäfer,
4. To address the p value problem of large sample sizes, we tested statistical significance at a level of .001,
calculated and reported effect sizes (Kaplan et al., 2014; Lantz, 2012), and reported the sensitivity of the
dependent variable to changes in the independent variable (Lin et al., 2013). The p values on the cross-
level interactions are lower, because the N is only 20.
Achterberg P, de Koster W and van der Waal J (2017) A science confidence gap: Education, trust in scientific
methods, and trust in scientific institutions in the United States, 2014. Public Understanding of Science
26: 704–720.
Allcott H and Gentzkow M (2017) Social media and fake news in the 2016 election. Working paper no.
23089. Available at: (accessed 19 February 2018).
Allgaier J (2016) Science on YouTube: What users find when they search for climate science and climate
manipulation. Available at: (accessed 19 February 2018).
American Association for Public Opinion Research (2011) Standard definitions: Final dispositions of case
codes and outcome rates for surveys. Available at:
Anderson AA and Huntington HE (2017) Social media, science, and attack discourse: How Twitter discus-
sions of climate change use sarcasm and incivility. Science Communication 39(5): 598–620.
Anderson AA, Scheufele DA, Brossard D and Corley EA (2012) The role of media and deference to scien-
tific authority in cultivating trust in sources of information about emerging technologies. International
Journal of Public Opinion Research 24(2): 225–237.
Aupers S (2012) “Trust no one”: Modernization, paranoia and conspiracy culture. European Journal of
Communication 27(1): 22–34.
Bak HJ (2001) Education and public attitudes toward science: Implications for the “deficit model” of educa-
tion and support for science and technology. Social Science Quarterly 82: 779–795.
Bakshy E, Messing S and Adamic L (2015) Exposure to ideologically diverse news and opinion on Facebook.
Science 348: 1130–1132.
Barber B (1987) Trust in science. Minerva 25(1–2): 123–134.
Barnidge M (2015) The role of news in promoting political disagreement on social media. Computers in
Human Behavior 52: 211–218.
Baskerville RF (2003) Hofstede never studied culture. Accounting, Organizations and Society 28: 1–14.
Beck J (2017) The challenge of fighting mistrust in science. The Atlantic, 24 June. Available at: https://www
Blake A (2015) Americans’ increasing distrust of science—and not just on climate change. The Washington
Post, 30 January. Available at:
Bochner S and Hesketh B (1994) Power distance, individualism/collectivism, and job-related attitudes in a
culturally diverse work group. Journal of Cross-Cultural Psychology 25: 233–257.
Bode L (2016) Political news in the news feed: Learning politics from social media. Mass Communication
and Society 19(1): 24–48.
Bogner A and Torgersen H (2005) Sozialwissenschaftliche Expertiseforschung. Zur Einleitung in ein expandier-
endes Forschungsfeld [Social scientific research on expertise. Introduction to an expanding research field].
In: Bogner A. and Torgersen H (eds) Wozu Experten? Ambivalenzen der Beziehung von Wissenschaft und
Politik. Wiesbaden: Verlag für Sozialwissenschaften, pp. 7–29.
Bonchi F, Castillo C and Ienco D (2013) Meme ranking to maximize post vitality in microblogging platforms.
Journal of Intelligent Information Systems 40: 211–231.
Huber et al. 773
Bore ILK and Reid G (2014) Laughing in the face of climate change? Satire as a device for engaging audi-
ences in Public Debates. Science Communication 36(4): 454–478.
Brantner C and Huber B (2013) How visible is communication studies? Press coverage of the discipline in
three German-language quality newspapers. Studies in Communication—Media 2(2): 247–264.
Brewer PR and Ley BL (2013) Whose science do you believe? Explaining trust in sources of scientific infor-
mation about the environment. Science Communication 35: 115–137.
Brockner J, Ackerman G, Greenberg J, Gelfand MJ, Francesco AM, Chen ZX, et al. (2001) Culture and pro-
cedural justice: The influence of power distance on reactions to voice. Journal of Experimental Social
Psychology 37: 300–315.
Brossard D (2013) New media landscapes and the science information consumer. Proceedings of the National
Academy of Sciences of the United States of America 110(3): 14096–14101.
Bucchi M (2017) Credibility, expertise and the challenges of science communication 2.0. Public Understanding
of Science 26(8): 890–893.
Cacciatore MA, Scheufele DA and Corley EA (2014) Another (methodological) look at knowledge gaps and
the Internet’s potential for closing them. Public Understanding of Science 23(4): 376–394.
Callegaro M, Baker RP, Bethlehem J, Goritz AS, Krosnick JA and Lavrakas PJ (eds) (2014) Online Panel
Research: A Data Quality Perspective. West Sussex: John Wiley & Sons.
Choi SM, Kim Y, Sung Y and Sohn D (2011) Bridging or bonding? A cross-cultural study of social relation-
ships in social networking sites. Information, Communication & Society 14(1): 107–129.
Choi W and Stvilia B (2015) Web credibility assessment: Conceptualization, operationalization, variability,
and models. Journal of the Association for Information Science and Technology 66(12): 2399–2414.
Collins K, Shiffman D and Rock J (2016) How are scientists using social media in the workplace? PLoS ONE
11(10): e0162680.
Darling ES, Shiffman D, Cȏté IM and Drew JA (2013) The role of Twitter in the life cycle of a scientific
publication. Ideas in Ecology and Evolution 6: 32–43.
Davies SR and Hara N (2017) Public science in a wired world: How online media are shaping science com-
munication. Science Communication 39(5): 563–568.
Dudo A, Brossard D, Shanahan J, Scheufele DA, Morgan M and Signorelli N (2011) Science on television in
the 21st century: Recent trends in portrayals and their contributions to public attitudes toward science.
Communication Research 38(6): 754–777.
Dunn A, Leask J, Zhou X, Mandl K and Coiera E (2015) Associations between exposure to and expression
of negative opinions about human papillomavirus vaccines on social media: An observational study.
Journal of Medical Internet Research 17(6): e144.
Elmer C, Badenschier F and Wormer H (2008) Science for everybody? How the coverage of research issues
in German newspapers has increased dramatically. Journalism & Mass Communication Quarterly 85(4):
European Union (2017) Special Eurobarometer 468: Attitudes of European citizens towards the environment.
Available at:
Evans G and Durant J (1989) Understanding of science in Britain and the USA. In: Jowell R, Witherspoon S
and Brook (eds) British Social Attitudes, 6th Report. Aldershot: Gover, pp. 105–129.
Evans G and Durant J (1995) The relationship between knowledge and attitudes in the public understanding
of science in Britain. Public Understanding of Science 4: 57–74.
Fogg BJ, Marshall OL, Laraki O, Osipovich A, Varma C, Fang N, et al. (2001) What makes web sites cred-
ible? A report on a large quantitative study. In: Proceedings of the SIGCHI conference on human factors
in computing systems (eds J Jacko and A Sears), Seattle, WA, pp. 61–68. New York: ACM Press.
Gambetta DG (1988) Can we trust? In: Gambetta DG (ed.) Trust: Making and Breaking Cooperative
Relations. New York: Basil Blackwell, pp. 213–237.
Ganley D and Lampe C (2009) The ties that bind: Social network principles in online communities. Decision
Support Systems 47: 266–274.
Garrett RK and Stroud NJ (2014) Partisan paths to exposure diversity: Differences in pro- and counterattitu-
dinal news consumption. Journal of Communication 64(4): 680–701.
Gauchat G (2012) Politicization of science in the public sphere: A study of public trust in the United States,
1974 to 2010. American Sociological Review 77(2): 167–187.
774 Public Understanding of Science 28(7)
Gerbner G (1987) Science on television: How it affects public conceptions. Issues in Science and Technology
3: 109–115.
Gil de Zúñiga H, Jung N and Valenzuela S (2012) Social media use for news and individuals’ social capi-
tal, civic engagement and political participation. Journal of Computer-Mediated Communication 17(3):
Gil de Zúñiga H, Diehl T, Huber B and Liu JH (2017) Personality traits and social media use in 20 countries:
How personality relates to frequency of social media use, social media news use, and social media use
for social interaction. Cyberpsychology, Behavior, and Social Networking 20(9): 540–552.
Goodrich K and De Mooij M (2014) How “social” are social media? A cross-cultural comparison of online
and offline purchase decision influences. Journal of Marketing Communications 20(1–2): 103–116.
Hargittai E, Füchslin T and Schäfer MS (2018) How do young adults engage with science and research on
social media? Some preliminary findings and an agenda for future research. Social Media + Society
4(3): 1–10.
Hayes BC and Tariq V (2000) Gender differences in scientific knowledge and attitudes towards science: A
comparative study of four Anglo-American nations. Public Understanding of Science 9: 433–447.
Hendriks F, Kienhues D and Bromme R (2015) Measuring laypeople’s trust in experts in a digital age: The
Muenster Epistemic Trustworthiness Inventory (METI). PLoS ONE 10(10): e0139309.
Hmielowski JD, Feldman L, Myers TA, Leiserowitz A and Maibach E (2014) An attack on science? Media
use, trust in scientists, and perceptions of global warming. Public Understanding of Science 23(7): 866–
Hofstede G (1980) Culture’s Consequences: International Differences in Work-Related Values. Beverly
Hills, CA: SAGE.
Hofstede G (2001) Culture’s Consequences: Comparing Values, Behaviors, Institutions, and Organizations
across Nations, 2nd edn. Thousand Oaks CA: SAGE.
Hofstede G (2002) Dimensions do not exist: A reply to Brendan McSweeney. Human Relations 55(11):
Hofstede G, Hofstede GJ and Minkov M (2010) Cultures and Organizations: Software of the Mind, 3rd edn.
New York: McGraw-Hill.
Huber B, Wetzstein I and Aichberger I (2019) Societal problem solver or deficient discipline? The debate
about social science in the online public sphere. Journal of Science Communication 18(02): A04.
Jackson LA and Wang JL (2013) Cultural differences in social networking site use: A comparative study of
China and the United States. Computers in Human Behavior 29(3): 910–921.
Jang SM and Hart PS (2015) Polarized frames on “climate change” and “global warming” across countries
and states: Evidence from Twitter big data. Global Environmental Change 32: 11–17.
Jia H, Wang D, Miao W and Zhu H (2017) Encountered but not engaged: Examining the use of social media
for science communication by Chinese scientists. Science Communication 39(5): 646–672.
Kaplan RM, Chambers DA and Glasgow RE (2014) Big data and large sample size: A cautionary note on the
potential for bias. Clinical and Translational Science 7: 342–346.
Kim Y, Hsu SH and Gil de Zúñiga H (2013) Influence of social media use on discussion network heterogene-
ity and civic engagement: The moderating role of personality traits. Journal of Communication 63(3):
Kim Y, Sohn D and Choi SM (2011) Cultural difference in motivations for using social network sites:
A comparative study of American and Korean college students. Computers in Human Behavior 27:
Lantz B (2012) The large sample size fallacy. Scandinavian Journal of Caring Science 27(2): 487–492.
Lee NM, VanDyke MS and Cummins RG (2018) A missed opportunity? NOAA’s use of social media to
communicate climate science. Environmental Communication 12(2): 274–283.
Liang X, Leona YS, Yeo SK, Scheufele DA, Brossard D, Xenos M, et al. (2014) Building buzz: (Scientists)
communicating science in new media environments. Journalism & Mass Communication Quarterly
91(4): 772–791.
Lin M, Lucas HC and Shmueli G (2013) Too big to fail: Large samples and the p-value problem. Information
Systems Research 24(4): 906–917.
Huber et al. 775
Liu H and Priest S (2009) Understanding public support for stem cell research: Media communica-
tion, interpersonal communication and trust in key actors. Public Understanding of Science 18(6):
Luhmann N (1989) Vertrauen. Ein Mechanismus der Reduktion sozialer Komplexität [Trust. A mechanism to
reduce social complexity]. Stuttgart: Ferdinand Enke.
Mathieu JE, Aguinis H, Culpepper SA and Chen G (2012) Understanding and estimating the power to
detect cross-level interaction effects in multi-level modeling. Journal of Applied Psychology 97(5):
McSweeney B (2002) Hofstede’s model of national cultural differences and their consequences: A triumph of
faith—a failure of analysis. Human Relations 55(1): 89–118.
Medical Research Council (2016) Public trust in scientific research. Available at:
Men LR and Tsai WHS (2012) How companies cultivate relationships with publics on social network sites:
Evidence from China and the United States. Public Relations Review 38(5): 723–730.
Messing S and Westwood SJ (2013) Friends that matter: How social influence affects selection in social
media. In: Proceedings of the Midwest Political Science Association Annual Meeting. Chicago, USA.
Miller JD (2004) Public understanding of, and attitudes toward, scientific research: What we know and what
we need to know. Public Understanding of Science 13(3): 273–294.
Myers TA, Kotcher J, Stenhouse N, Anderson AA, Maibach E, Beall L, et al. (2017) Predictors of trust in the
general science and climate science research of U.S. federal agencies. Public Understanding of Science
26(7): 843–860.
National Science Board (2016) Science & Engineering Indicators 2016. Available at:
nsb/publications/2016/nsb20161.pdf (accessed 19 February 2018).
Newman N, Fletcher R, Kalogeropoulos A, Levy DAL and Nielsen RK (2018) Reuters Institute Digital
News Report 2018. Available at:
Nisbet MC and Goidel RK (2007) Understanding citizen perceptions of science controversy: Bridging the
ethnographic-survey research divide. Public Understanding of Science 16: 421–440.
Nisbet MC, Scheufele DA, Shanahan J, Moy P, Brossard D and Lewenstein BV (2002) Knowledge, res-
ervations, or promise? A media effects model for public perceptions of science and technology.
Communication Research 29(5): 584–608.
Oeldorf-Hirsch A (2018) The role of engagement in learning from active and incidental news exposure on
social media. Mass Communication and Society 21(2): 225–247.
Perea A and Slater MD (1999) Power distance and collectivistic/individualistic strategies in alcohol warnings:
Effects by gender and ethnicity. Journal of Health Communication 4(4): 295–310.
Peters PP, Dunwoody S, Allgaier J, Lo YY and Brossard D (2014) Public communication of science 2.0: Is
the communication of science via the “new media” online a genuine transformation or old wine in new
bottles? EMBO Reports 15(7): 749–753.
Pew Research Center (2015) The evolving role of news on Twitter and Facebook. Available at: http://www.
Sbaffi L and Rowley J (2017) Trust and credibility in web-based health information: A review and agenda for
future research. Journal of Medical Internet Research 19(6): e218.
Schäfer MS (2016) Mediated trust in science: Concept, measurement and perspectives for the “science of sci-
ence communication.” Journal of Science Communication 15(5): C02.
Schäfer MS (2017) Wissenschaftskommunikation Online [Science communication online]. In:
Bonfadelli H, Fähnrich B, Lüthje C, Milde J, Rhomberg M and Schäfer MS (eds) Forschungsfeld
Wissenschaftskommunikation [Research field of science communication]. Wiesbaden: Springer
Fachmedien, pp. 275–293.
Scheufele DA (2013) Communicating science in social settings. Proceedings of the National Academy of
Sciences of the United States of America 110(3): 14040–14047.
Scheufele DA and Lewenstein BV (2005) The public and nanotechnology: How citizens make sense of
emerging technologies. Journal of Nanoparticle Research 7: 659–667.
776 Public Understanding of Science 28(7)
Shneor R and Efrat K (2014) Analyzing the impact of culture on average time spent on social networking
sites. Journal of Promotion Management 20: 413–435.
Simis-Wilkinson MJ, Madden H, Lassen DS, Su LYF, Brossard D, Scheufele DA, et al. (2018) Scientists
joking on social media: An empirical analysis of #overlyhonestmethods. Science Communication 40(3):
Special Eurobarometer (2007) Scientific research in the media (Special Eurobarometer 282/ Wave 67.2—
TNS Opinion & Social). Available at:
ebs_282_en.pdf (accessed 19 February 2018).
Su LYF, Akin H, Brossard D, Scheufele DA and Xenos MA (2015) Science news consumption patterns and
their implications for public understanding of science. Journalism & Mass Communication Quarterly
92(3): 597–616.
Sundar S (2008) The MAIN model: A heuristic approach to understanding technology effects on credibility.
In: Metzger MJ and Flanagin AJ (eds) Digital Media, Youth, and Credibility. Cambridge, MA: MIT
Press, pp. 73–100.
Taddicken M (2013) Climate change from the user’s perspective: The impact of mass media and Internet
use and individual and moderating variables on knowledge and attitudes. Journal of Media Psychology
25(1): 39–52.
Taras V (2017) Cultural dimensions, Hofstede. In: Kim YY (ed.) International Encyclopedia of Intercultural
Communication. Hoboken, NJ: John Wiley & Sons, pp. 1–5.
The Media Insight Project (2017) “Who shared it?” How Americans decide what news to trust on social
media. Available at:
social-media/ (accessed 19 February 2018).
Thorson K and Wells C (2015) Curated flows: A framework for mapping media exposure in the digital age.
Communication Theory 26(3): 309–328.
Valenzuela S, Arriagada A and Scherman A (2012) The social media basis of youth protest behavior: The
case of Chile. Journal of Communication 62(2): 299–314.
Van der Vegt GS, van der Vliert E and Huang X (2005) Location-level links between diversity and
innovative climate depend on national power distance. The Academy of Management Journal 48(6):
Vasalou A, Joinson AN and Courvoisier D (2010) Cultural differences, experience with social networks and
the nature of “true commitment” in Facebook. International Journal of Human-Computer Studies 68:
Von Roten FC (2004) Gender differences in attitudes toward science in Switzerland. Public Understanding
of Science 13: 191–199.
Vraga EK and Bode L (2017) Using expert sources to correct health misinformation in social media. Science
Communication 39(5): 621–645.
Wang Y and Mark G (2013) Trust in online news: Comparing social media and official media use by Chinese
citizens. In: Conference on computer supported cooperative work (CSCW 2013), San Antonio, TX,
23–27 February. New York: ACM.
Wei L, Willnat L and Shao S (2012) Cultural differences in the use of web 1.0 and web 2.0: A comparative
analysis of Chinese and American youth. China Media Research 8(4): 77–89.
Weingart P and Guenther L (2016) Science communication and the issue of trust. Journal of Science
Communication 15(5): C01.
Yang KCC and Kang Y (2015) Exploring big data and privacy in strategic communication campaigns: A
cross-cultural study of mobile social media users’ daily experiences. International Journal of Strategic
Communication 9: 87–101.
Yuan S, Oshita T, AbiGhannam N, Dudo A, Besley JC and Koh HE (2017) Two-way communication between
scientists and the public: a view from science communication trainers in North America. International
Journal of Science Education, Part B 7: 341–355.
Ziman J (1991) Public understanding of science. Science, Technology, & Human Values 16(1): 99–105.
Huber et al. 777
Author biographies
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:
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:
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:
... Indirectly, a certain relationship could be hypothesized between power distance and the perceived intensity of exposure to fake news. In their analysis of public trust in science and the use of social media, Huber et al. (2019) conclude that a positive relationship between social media news use and trust in science will be relatively stronger in high power distance countries than it is in low power distance countries, but only in collectivistic countries. In fact, cultures with lower power distance tend to be more egalitarian in their relationships, and members of these cultures are more likely to question the legitimacy of authority. ...
... about the possible interactions of cultural dimensions with our sociodemographic variables (Lawrie et al., 2019;Ng & Lim-Soh, 2020), with social media use (Stump & Gong, 2020) or with media trust, a variable usually connected both with cultural values and disinformation (Huber et al., 2019;Humprecht et al., 2020;Ognyanova et al., 2020;Tsfati & Ariely, 2013). As a consequence, we cannot formulate specific hypothesis for these interactions and will analyze them in an exploratory manner. ...
[Abstract] This article analyzes the extent to which certain cultural dimensions explain the intensity with which citizens of different countries perceive the presence of fake news in their daily lives. The research is based on the Flash Eurobarometer survey conducted in 2018 about fake news and disinformation online in 25 European countries, and adopts the Hofstede cultural dimensions as a model of cultural analysis. The study uses multilevel regression analysis to test individual and macro-level indicators that explain variations in perceptions of fake news. The findings reveal a clear, direct relationship between uncertainty avoidance, masculinity, and fake news exposure, as well as an interaction of these cultural dimensions with age, but not with the other individual and media use related variables. These results have theoretical and practical implications, especially from the point of view of the design of public policies to fight disinformation in the European Union (EU).
... Trust in science is therefore "multidimensional", relating not simply to the perceived veracity of empirical claims or the competence of technicians, but also to their ethical integrity, commercial and political motivations (Achterberg et al., 2017;Miller, 2004). Indeed, prior research suggests that people make subtle distinctions in the trust they accord to scientists, scientific institutions, and scientific principles and methods (Huber et al., 2019). While public trust of scientific principles and methods tends to be high (Miller, 2004), among certain demographics there is a "science confidence gap" where trust in scientific methods is combined with distrust in scientists and the institutions in which they are embedded (Achterberg et al., 2017). ...
Purpose-: To respond to the COVID-19 "infodemic" and combat fraud and misinformation about the virus, social media platforms coordinated with government healthcare agencies around the world to elevate authoritative content about the novel coronavirus. These public health authorities included national and global public health organisations, such as the Centers for Disease Control and Prevention (CDC) and the World Health Organisation (WHO). In this article, the authors evaluate the effectiveness of this strategy by asking two key questions: (1) Did people engage with authoritative health content on social media? (2) Was this content trusted? Design/methodology/approach: The authors explore these issues by drawing on data from a global online questionnaire on "Public Trust in Experts" (n 5 429) conducted during the initial phase of the pandemic in May 2020, a crucial period when reliable information was urgently required to influence behaviour and minimise harm. Findings: The authors found that while the majority of those surveyed noticed authoritative health content online, there remained significant issues in terms of Internet users trusting the information shared by government healthcare agencies and public health authorities online. Originality/value: In what follows, the authors examine the role of trust in implementing this novel public health strategy and assess the capacity for such policies to reduce individual and social harm.
... 649); that is, there is both rational and irrational skepticism-an appropriate context for addressing trust and social media. In a 20-country survey, the relationship between trust and social media related to the medical sciences was found to be influenced by a country's culture, with respect to "individualism/collectivism and power distance" (Huber et al., 2019;p. 759). ...
Full-text available
This article establishes a rational, feasible, and necessary conclusion to reform high school science content into an equitable experience for its wide diversity of students' self‐identities. Research indicates that 85% of graduates would not normally have enrolled in any science course unless required. Their values are more aligned with their everyday world and/or the world of the humanities, to varying degrees. The 15% had already fulfilled their science prerequisite for postsecondary science‐related programs, to varying degrees. The article's conclusion rests mainly on historical and economic evidence, respectively: (1) The Sputnik crisis that instilled public fear and anxiety about the perceived technological gap between the United States and Soviet Union. This led to reforming high school science and implementing National Aeronautics and Space Administration. (2) The on‐growing climate‐change crisis for which the smart international money is increasingly investing in sustainable businesses and industries, which catalyze a shift in public values from the current “profit society” to a “sustainable society.” The article's rationale connects the two historical events. Over the past 30 years, the nature of normal science has evolved into post‐normal science. Today the public square also includes: (a) an international assessment project that receives a negative validity audit in this article; (b) a vocal small minority within the 85%, proud of their antiscience self‐identities and their leaders' hostile behavior (a problem to ameliorate by a reformed sustainable science education); and (c) instances of small‐scale, suitable reform examples developed over the last 70 years, often referred to as humanistic school science.
... Globally, many countries have reported the continued growth in social media as news sources (Newman et al., 2017) and most consumers obtain information about GMO via the internet (Cui and Shoemaker, 2018;Deng and Hu, 2019). Previous research examined the role of social media in news consumption and its potential impact on individual decision-making and behavior (Fletcher and Nielsen, 2018;Huber et al., 2019). On one hand, some scholars are excited about its positive impact, arguing that equal access and equality in information production and dissemination contribute to the formation and maturation of deliberative democracy (Rishel, 2011). ...
Full-text available
Background In China, controversy about genetically modified organisms (GMO) is ongoing and some regard GMO as a “product of a conspiracy,” which affects people’s attitudes (PAs) toward GMO. Beliefs in conspiracy theories (BCT) are formed from the information that people are exposed to. Information exposure not only constructs a pseudo-environment for individuals to perceive the world, but also generates external stimuli for their mental states and attitudes. People’s objective knowledge and self-assessed knowledge play an important moderating role in this process. Method The study adopted the stimulus-organism-response (SOR) model, with conspiracy beliefs as mediating variables, to test the mechanism of the independent variable of information exposure on the dependent variable of PAs toward GMO. Objective knowledge and self-assessed knowledge were introduced as moderator variables to explore the different roles of knowledge. A survey of Chinese adults was conducted in February 2022, and partial least squares structural equation modeling (PLS-SEM) was employed to estimate the multi-construct relationships. Results Information exposure was significantly and directly connected with PAs toward GMO. BCT also played a significant mediating role. Unofficial information exposure reinforced beliefs in conspiracy theories. Stronger beliefs in conspiracy theories reduced people’s willingness to consume GMO foods and made them pessimistic about the development prospects of GMO foods. In contrast, exposure to official information weakened people’s beliefs in conspiracy theories and increased their willingness to consume GMO foods. In addition, the level of knowledge had a moderating role. Individual’s objective knowledge can effectively reduce the negative relationship of conspiracy beliefs on attitudes toward GMO development. Conversely, individual’s self-assessed knowledge can enhance the negative relationship of conspiracy beliefs on attitudes toward GMO development. Conclusion Based on psychological and cognitive dimensions, this study provides a new perspective on how information exposure and people’s attitudes toward GMO are related to each other and enriches the variable measurement dimension of knowledge. Simultaneously, it provides a localized explanation of the factors affecting people’s attitudes toward GMO in China, providing a new theoretical basis for the subsequent development strategy of GMO foods.
... This is likely to generalize to other countries as well. We also note that Germany does not deviate significantly from the international scientific trust average, whereas the United States is below the international mean (Huber et al., 2019). ...
Full-text available
The COVID-19 pandemic has spotlighted the importance of high-quality data for empirical health research and evidence-based political decision-making. To leverage the full potential of these data, a better understanding of the determinants and conditions under which people are willing to share their health data is critical. Building on the privacy theory of contextual integrity, the privacy calculus, and previous findings regarding different data types and recipients, we argue that established social norms shape the acceptance of novel practices of data collection and use. To investigate the willingness to share health data, we conducted a preregistered vignette experiment. The scenarios experimentally varied the vignette dimensions by data type, recipient, and research purpose. While some findings contradict our hypotheses, the results indicate that all three dimensions affected respondents' data sharing decisions. Additional analyses suggest that institutional and social trust, privacy concerns, technical affinity, altruism, age, and device ownership influence the willingness to share health data.
Full-text available
Using moralization in anti-vaping public health messages as a persuasion strategy was recently recommended to address the current vaping epidemic. However, previous findings indicated this could lead to moralized attitudes in the general population, which can be very difficult to change and could severely affect social cohesion and distort risk perception. Since the safety and efficiency of using electronic cigarettes as smoking cessation devices are still being investigated, we conducted a cross-sectional, experimental study on a convenience sample of 612 Romanian never vapers, never smokers to assess how exposure to moralizing public health messages about vaping might influence their trust in future scientific results about this topic. Participants were randomized into six groups according to the type of message (“moral,” “immoral,” “neutral”) and the type of effects of vaping on smokers’ health, documented in a future fictitious study (“health benefits,” “health risks”). Results showed that the type of message moderated trust in future scientific results after controlling for participants’ general trust in science. When vaping was framed as immoral, trust in future scientific results showing health benefits was decreased, and vice versa. Implications are discussed for using moralization strategically in public health messaging to curtail or promote certain health behaviors.
Full-text available
One of today’s most controversial and consequential issues is whether the global uptake of digital media is causally related to a decline in democracy. We conducted a systematic review of causal and correlational evidence (N = 496 articles) on the link between digital media use and different political variables. Some associations, such as increasing political participation and information consumption, are likely to be beneficial for democracy and were often observed in autocracies and emerging democracies. Other associations, such as declining political trust, increasing populism and growing polarization, are likely to be detrimental to democracy and were more pronounced in established democracies. While the impact of digital media on political systems depends on the specific variable and system in question, several variables show clear directions of associations. The evidence calls for research efforts and vigilance by governments and civil societies to better understand, design and regulate the interplay of digital media and democracy.
Full-text available
Understanding the heterogeneous role of individuals for large-scale information spreading is essential to manage online behaviour as well as its potential offline consequences. To this end, most existing studies from diverse research domains focus on the disproportionate role played by highly-connected “hub” individuals. However, we demonstrate here that information spreading in online social media is best understood and predicted by simultaneously uncovering two individual-level behavioural traits: influence and susceptibility. Specifically, we derive a nonlinear network-based algorithm to quantify individuals’ influence and susceptibility from multiple spreading event data. By applying the algorithm to large-scale data from Twitter and Weibo, we demonstrate that both individuals’ influence and susceptibility are key determinants of peer-to-peer information propagation: neglecting one of the two properties leads to sub-optimal propagation predictions. We show that, as a consequence, considering both properties can significantly improve seeding policies aimed at broadly disseminating information.
Full-text available
Sustainability communication is of increasing importance. While sustainability communication in traditional media has already been well researched, more research is needed about social media platforms in this regard. By focusing on sustainability communication on TikTok, this study makes an important contribution to the literature. More specifically, we investigate how eco influencers communicate sustainability on TikTok. Findings from content analysis (n = 242) reveal that eco influencers cover a wide range of different topics. Individual responsibility attributions are dominant in short videos posted on the platform. Videos presenting broader perspectives are more likely to refer to empirical evidence. Implications for science and environmental communicators are discussed.
In developing Trustworthy Autonomous Systems (TAS), as in other domains of technology innovation and research, there is a need to make research processes and activities more accessible to external partners and to the wider public. In this article, we describe the rationale, background and potential for an “Open Laboratories” approach that complements current strategies in Responsible Research and Innovation and in Open Science, relating this to experience-based aspects of trust in new technologies. We also reflect on the value and benefits of robotic telepresence as an engagement tool that can provide direct access, and first-person experience, of research, in a manner that is scalable and safe, while mitigating some environmental and health concerns.
Full-text available
This study uses the online discourse surrounding an Austrian publicly-funded study about “Islamic kindergartens” as a case study to approach communication about the social sciences in the online public sphere. Results from a discourse analysis of 937 user comments in online forums of two Austrian daily newspapers show that the social sciences are often referred to as a “special case”. While some use this argument to neglect its societal relevance, others use it to highlight its role as societal problem solver. Moreover, users discuss characteristics of “true” social scientists and scrutinise the independence of institutionalised social science.
Full-text available
While considerable research has looked at how people use the Internet for sharing and engaging with various types of content from celebrity news to politics, very little of this work has considered how non-specialists interact with science and research material on social media. This article reviews literature on public engagement with science to note that this area is ripe for research on social-media-based engagement in particular. Drawing on a survey of American young adults’ online experiences, we show that using social media for science and research is at least as likely if not more so as engagement with other topics from similarly serious to lighter domains. We also find that platform matters with young adults much more likely to engage with such content on Facebook rather than on Twitter. We end by proposing more focus on this domain in the area of science communication and work on social media.
Full-text available
The #overlyhonestmethods trend on Twitter is a space used by many scientists to peel back the curtain on their work and share observations and insights into the research world. We employ computer-assisted coding to assess the themes of 58,125 #overlyhonestmethods posts from January 7, 2013—the hashtag’s inception—to January 6, 2016. We additionally manually code a random sample of the census of tweets to evaluate the types of humor employed, as well as the targets of jokes and exclusivity of language. We offer analyses of this self-deprecating, insider conversation and an assessment of the associated ethical implications.
Full-text available
This study examines the relationship between peoples' personality traits and social media uses with data from 20 societies (N = 21,314). A measure of the ''Big Five'' personality traits is tested on key social media dimensions: frequency of use, social interaction, and news consumption. Across diverse societies, findings suggest that while extraversion, agreeableness, and conscientiousness are all positive predictors of different types of social media use, emotional stability and openness are negatively related to them.
Full-text available
Thus far, few studies have examined how scientists choose different social media platforms, or how using multiple platforms of social media is related to public engagement with science. This article investigates the role of social media in China’s science communication and scientists’ selective use of them. We found that social media enabled Chinese scientists to avoid relying on legacy media and to develop more interdisciplinary collaborations. In the process, these scientists strategically chose different social media platforms to increase controllability. Despite their preference for the approach of knowledge dissemination rather than dialogues, Chinese scientists tried to avoid the bureaucratic practice of science communication, and instead, they promoted some level of public participation.
Conflict in online discussions of science has the potential to polarize individuals’ perceptions of science, yet science communication scholarship has paid little attention to systematic study of how verbal attacks play out in online discussions of science. This study analyzes sarcasm and incivility in Twitter discussions of climate change during an extreme weather event (n = 4,094). We found instances of incivility and sarcasm were low overall. Incivility was used in association with political topics, and both incivility and sarcasm were used alongside skeptical perspectives of climate change and by those who mention right-leaning politics in their profiles.
The growing reliance on social media as news platforms may lead to more passive news consumption, but also offers greater potential for engaging in news. This study investigates the role of engagement with news content on Facebook and Twitter between news exposure and current events knowledge. An online survey (N = 400) tests the relationships between social media news seeking, incidental exposure to news on social media, engagement in shared news content, cognitive elaboration, and current events knowledge. The results show that both active seeking of and incidental exposure to news on both sites are linked to engagement, which is linked to greater cognitive elaboration about the content. Furthermore, engagement mediates the relationship between both types of news exposure and cognitive elaboration. However, engagement and elaboration are not related to knowledge. These results indicate that the key role of social media in news content is not knowledge gain, but the ability to engage users who may be passively receiving news on these sites. This study extends the cognitive mediation model of learning from the news in the context of current social media, with updated news consumption norms such as engagement with news on these sites, and incidental news exposure.