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Abstract

Social media are increasingly being used by young and old as a source of information. Fake news is also on the rise. The role played by age in the consumption of fake news on social media, however, is unclear. This paper explores the generational differences in the consumption of fake news, first by discussing previous empirical studies in this field and then on the basis of an empirical study carried out between the beginning of February 2018 and the end of June of 2018. In that empirical study, 14 political fake news articles (e.g., relating to Brexit and Donald Trump) were disseminated in the form of advertisements on Facebook. User interaction with the fake content was tracked in order to analyze the number of users in the age groups 13-17, 18-24, 25-34, 35-44, 45-54, 55-64, 65+. The results of the empirical study show that the articles had a higher reach amongst the older age groups, as well as that many people likely took the headlines at face value without clicking on the link. The number of emotional responses posted by the pro-Brexit and pro-Trump groups was greater than those posted by the pro-remain and anti-Trump groups. All of the posts were permitted to run as advertisements on Facebook despite Facebook’s efforts to limit the spread of fake news on their platform. In the final section, conclusions are drawn, limitations described and implications for future research are outlined.
Loos, E., & Nijenhuis, J. (2020). Consuming Fake News: A Matter of Age? The
perception of political fake news stories in Facebook ads. In J. Zhou & Q. Gao (Eds.),
Human Aspects of IT for the Aged Population, Technology and Society, Design and
User Experience 6th International Conference, ITAP 2020, Held as Part of the 22nd
HCI International Conference, HCII 2020, Copenhagen, July, 19-24. Proceedings,
Part III (pp. 69-88), Springer International Publishing.
Consuming Fake News: A Matter of Age? The perception
of political fake news stories in Facebook ads
Eugène Loos1 and Jordy Nijenhuis2
1Utrecht University, Bijlhouwerstraat 6, 3511 ZC, Utrecht, The Netherlands
e.f.loos@uu.nl
2Impact Consultancy, Amsterdamsestraatweg 959A, 3555 HR, Utrecht, The Netherlands
jordy@dtbg.nl
Abstract. Social media are increasingly being used by young and old as a
source of information. Fake news is also on the rise. The role played by age in
the consumption of fake news on social media, however, is unclear. This paper
explores the generational differences in the consumption of fake news, first by
discussing previous empirical studies in this field and then on the basis of an
empirical study carried out between the beginning of February 2018 and the end
of June of 2018. In that empirical study, 14 political fake news articles (e.g.,
relating to Brexit and Donald Trump) were disseminated in the form of
advertisements on Facebook. User interaction with the fake content was tracked
in order to analyze the number of users in the age groups 13-17, 18-24, 25-34,
35-44, 45-54, 55-64, 65+. The results of the empirical study show that the
articles had a higher reach amongst the older age groups, as well as that many
people likely took the headlines at face value without clicking on the link. The
number of emotional responses posted by the pro-Brexit and pro-Trump groups
was greater than those posted by the pro-remain and anti-Trump groups. All of
the posts were permitted to run as advertisements on Facebook despite
Facebook’s efforts to limit the spread of fake news on their platform. In the
final section, conclusions are drawn, limitations described and implications for
future research are outlined.
Keywords: Fake News · Social media · Facebook · Age · Generations ·
Disinformation · Misinformation
1. Introduction
Looking up information about medical treatments, comparing programs of political
parties at election time, browsing reviews to find a good restaurant: these are just a
few examples from everyday life showing how often we rely on being able to find
reliable information. In the past, we depended on family members, friends, neighbors
and traditional media such as radio, television and printed versions of newspapers for
such information. In today’s digitized society, a host of new media are available,
providing information about any topic we wish. Yet how can we be sure that the
information we read online can be trusted, so that we find the right treatment, the
right politician to represent us or the right place to have a good dinner at a fair price in
a nearby restaurant?
The problem of information credibility is nothing new [1-7]. As Obadă (2019) [7, p.
148] states: “Fake news is not a new phenomenon [8, 9] because the partisan press
has always peddled biased opinions and stories lacking factual basis” [9]. New
technologies, from the telegraph in the 19th century to contemporary social media
algorithms, have led to the proliferation of fake news [8]. For example, Gelfert (2018)
[8] refers to an article that appeared in the Arena journal written by J. B.
Montgomery-McGovern in 1898, entitled “An important phase of gutter journalism:
Faking”, to outline the challenges of fake news in the 19th century. In his article,
Montgomery-McGovern (1898) complains about “fake journalism”, considered to be
“the most sensational stories” published by news organizations (1898, 240), and he
explains the “stand-for” technique used by “fakers” to deceive: they recruited a
reputable member of the community (e.g., a doctor, dentist, architect, or other
professional or business man) who, against payment, would corroborate the fake
story.
Though the problem of news credibility is from time immemorial, the role of
traditional information gatekeepers such as doctors, news agencies and restaurant
critics has been diminished. Media displacement [10] has brought about the rise of
social media networks, allowing everybody to post and read unfiltered information on
social media networks such as Facebook and Twitter 24/7. Obadă (2019) [7, p. 148)
states: “Gelfert (2018) [8] considers nowadays fake news creators eliminated the
“middle-men” and address the readers directly, by sharing the sensational stories on
social media.” This leads to an increased risk of fake news, which has been defined by
Aldwairi and Alwahedi (2018) [11, p. 215] as “fictitious articles deliberately
fabricated to deceive readers”. Commercial gain (profit through clickbaits or to make
a competitor look bad), power (winning elections) are just some of the reasons for the
production and distribution of fake news.
This is a dangerous development for our civil society, constituting as it does a
threat to access to reliable information as a ‘primary good’ (Rawls (1993) [12], as
referred to by Van den Hoven (1994, p. 369) [13]. Bovens (2002) [14] and Bovens
and Loos (2002) [15] even suggest that the equal right of access to information
should be considered a basic right of all citizens, comparable to the classic (human)
rights (see also De Jong and Rizvi, 2008 [16]). The European Commission states that
“the exposure of citizens to large scale disinformation, including misleading or
outright false information, is a major challenge for Europe. The Commission is
working to implement a clear, comprehensive and broad set of actions to tackle the
spread and impact of online disinformation in Europe and ensure the protection of
European values and democratic systems.” Humprecht et al (2018) [17] analyzed how
the content of fake news differ across Western democracies. They conclude: “(…) the
current study (…) compares online disinformation republished by fact checkers from
four Western democracies (the US, the UK, Germany, and Austria). The findings
reveal significant differences between English-speaking and German-speaking
countries. In the US and the UK, the largest shares of partisan disinformation are
found, while in Germany and Austria sensationalist stories prevail. Moreover, in
English-speaking countries, disinformation frequently attacks political actors, whereas
in German-speaking countries, immigrants are most frequently targeted. Across all of
the countries, topics of false stories strongly mirror national news agendas.” If we
want to guarantee the right of access to reliable digital information for all citizens, it
is important to be aware of the role generational differences could play.
Though age-related limitations such as declining vision, hearing, cognition, and
visual-motor functions may affect the use of ICT devices by older old people [18], the
enhanced user friendliness of such devices (e.g., iPads) have, at the same time, made
them accessible to this same age group. Moreover, compared to a decade ago, older
people today are also more familiar with the new media, which has led to more ICT
and internet experience [19-22]. Perceived benefits [23] by seeing examples of use by
younger people may have also increased older adults’ new media use and probably
also convinced many older laggards [24] to start using ICT devices. Whatever the
reason, the fact remains that over the past years, the number of older people using
new media has clearly been on the rise in western societies. A survey conducted by
Pew Research Center [25] revealed that in the USA in 2017 “roughly two-thirds of
those ages 65 and older go online and a record share now own smartphones –
although many seniors remain relatively divorced from digital life”. Statistics from
the EU show that 51% of people aged 55 and older used the internet at least once a
week in 2017 [26, p. 16].
Older people’s social media use has also grown in recent years. According to the
results of a Pew Research Center survey conducted from January 8 to February 7,
2019 in the USA, 46% of people aged 60+ used Facebook in 2018. Despite this rise in
social media use, the social media adoption rate among adults aged 60+ is still
relatively low compared to other age groups (18-29: 79%, 30-49: 79%, 50-64: 68%)
[27]. Further discussion of this topic is beyond the scope of this paper; we refer to
Quinn [23], for a clear overview of studies presenting possible explanations. We also
refer to Holt et al. [28, p. 31], who performed a four-wave panel study conducted
during the 2010 Swedish national election campaign that found that “although
younger people pay less attention to political news in traditional media than older
people, they simultaneously are more frequent users of social media for political
purposes.”
Social media allow us to connect and share information with others, but it appears
that social media users are increasingly shielding themselves from opinions which
differ from their own. Ofcom’s Adults: Media use and attitudes report 2019 shows
that “compared to 2017, social media users are less likely to say they see views they
disagree with; a quarter say they ‘rarely’ see views on social media they disagree with
(vs. 18% in 2017). As such, more social media users say they ‘rarely’ see views they
disagree with (24%) than say they ‘often’ see views they disagree with (17%).” [29,
p .9) And the Reuters Institute digital news report 2017 states that “only a quarter
(24%) of our respondents think social media do a good job in separating fact from
fiction, compared to 40% for the news media. Our qualitative data suggest that users
feel the combination of a lack of rules and viral algorithms are encouraging low
quality and ‘fake news’ to spread quickly.” [30, p. 8]
The vulnerability to fake news often focuses on younger people (e.g., [31-33]), as
the following quote also illustrates: “(…) the [European] Commission will encourage
fact-checkers and civil society organizations to provide educational material to
schools and educators and include targeted initiatives on disinformation online in the
#SaferInternet4EU Campaign.” [34]
As we have made clear in this section, it is important that all citizens, regardless of
their age, have access to reliable digital information, and that we gain insight into the
vulnerability of older adults to fake news on social media. In this paper, therefore, we
address the role of age in the susceptibility to fake news and will explore the
following research question: What is the role of age in fake news consumption on
social media? To that end, we will not only discuss previous empirical studies in this
field but also present an empirical study carried out by ourselves, in which we
disseminated 14 political fake news articles (e.g., relating to Brexit and Donald
Trump) in the form of advertisements on Facebook. We then tracked the number of
users consuming fake news in the age groups 13-17, 18-24, 25-34, 35-44, 45-54, 55-
64, 65+ consumed Fake News. The methods results are presented in sections 3 and 4.
In the final section, conclusions are drawn, limitations described and implications for
future research outlined.
2. Fake news on social media
2.1. Introduction
While a detailed discussion of the dynamics of fake news on social media is beyond
the scope of this article, we nonetheless refer to a number of empirical studies
providing background information in order to set a context for our topic: the role of
age in fake news consumption on social media.
Allcott et al. (2019) [35, p. 1] offer a clear view on trends in the diffusion of what
they call misinformation on social media: “In recent years, there has been widespread
concern that misinformation on social media is damaging societies and democratic
institutions. In response, social media platforms have announced actions to limit the
spread of false content. We measure trends in the diffusion of content from 569 Fake
News websites and 9540 Fake News stories on Facebook and Twitter between
January 2015 and July 2018. User interactions with false content rose steadily on both
Facebook and Twitter through the end of 2016. Since then, however, interactions with
false content have fallen sharply on Facebook while continuing to rise on Twitter,
with the ratio of Facebook engagements to Twitter shares decreasing by 60%. In
comparison, interactions with other news, business, or culture sites have followed
similar trends on both platforms. Our results suggest that the relative magnitude of the
misinformation problem on Facebook has declined since its peak.”
For a current state-of-the-art study on fake news detection, we recommend
Mosinzova et al. (2019) [36]. More information about the consumption of news via
Facebook can be found in the work of Flintham et al. (2018) [37] and Quintanilha et
al. (2019) [38]. Resende et al. (2019) [39] provide insight into the characteristics of
shared textual (mis)information in WhatsApp groups, while Meinert et al. (2019) [40]
outline the development of fake news in the communication on social media
platforms.
For more information on the role of fake news in journalism we refer to Waisbord
(2018) [41]. Good examples of empirical studies focusing on fake news during the
2016 US presidential elections, are those conducted by Allcott and Gentzkow (2017)
[42], Bakir and McStay (2018) [43], Guo and Vargo (2018) [44] and Guess et al.
(2018, 2019) [45, 46]. Mehta and Guzmán (2018) [47, p. 111] analyzed news media
discourses around those same elections by looking at their use of quantitative visual
rhetoric (persuasive multimodal moves that draw on quantification through visual,
spatial, and textual manipulation). Pierri et al. (2019) [48] analyzed the role of Twitter
in Italian disinformation spreading during the European elections, Morstatter et al.
(2018) [49] present a Twitter analysis of the 2017 German federal election in which
they also address fake news, while Broersma and Graham (2012) [50] analyzed the
role to Tweets as a news source during the 2010 British and Dutch elections. Dutton et
al. [51, p. 5] conducted an online survey of Internet users in seven nations: Britain,
France, Germany, Italy, Poland, Spain, and the US, to examine how Internet users
“use search, social media, and other important media to get information about
political candidates, issues, and politics generally, as well as what difference it makes
for individuals participating in democratic processes.” Finally, Fedeli (2018) [52]
focuses on the phenomenon of fake news in the context of travel and tourism.
2.2. Generational differences
Neither in the edited volume Detecting Fake News on social media [53] nor in The
Handbook of Research on Deception, Fake News, and Misinformation Online [54]
nor in the Reuters Institute digital news report 2017 [30] is any attention paid to
generational differences relating to the consumption of fake news. A google scholar
search (01.02.2020) using the key words ‘social media’ AND ‘Fake News’ AND
‘generation’ OR ‘Age’ OR ‘young’ OR ‘old’ also failed to return any hits for scientific
papers on this topic.
While handbooks, manuals, reports and empirical studies offering insight into the
role that age differences play in the consumption of fake news on social media would
appear to be unavailable, a limited number of reports have been published that shed
some light on the topic, albeit in relation to only one specific age group (mainly
younger people).
In Net Children Go Mobile: The UK Report, Livingstone et al. [55, p. 30] showed
that in 2013, 61% of the UK respondents aged 11+ reported that they compare
websites to decide whether information is true. It should be noted that these finding
are based on self-reported data that might or might not reflect real behavior, and that
they relate to websites in general and not to social network sites specifically.
Marchi (2012) [56, p. 257] used individual interviews and focus groups with 61 US
high schoolers aged 14 to 19 to explore how teenagers view news, and found that
“teens gravitate toward fake news, “snarky” talk radio, and opinionated current events
shows more than official news, and do so not because they are disinterested in news,
but because these kinds of sites often offer more substantive discussions of the news
and its implications.” This is another example of a study based on self-reported data.
A report released in 2016 by the Stanford History Education Group [57, 58]
focused on students’ capability to judge the credibility of information. It described
how several online tasks were administered to 7,804 students in middle school
through college to reason about information found on the internet, and particularly on
social media sites. The main conclusion regarding their social media use was: “Our
“digital natives” may be able to flit between Facebook and Twitter while
simultaneously uploading a selfie to Instagram and texting a friend. But when it
comes to evaluating information that flows to social media channels, they are easily
dupe [57, p. 4].
Another empirical study [59, p. 407], which focused on university students in
Spain (Andalusia) yielded the following: “In order to ascertain the degree of
credibility that young users in Andalucía give to information, this study presents the
results of the evaluation of online news by university students pursuing degrees in
communication and education (N = 188), using the CRAAP test. The data reveal
differences in gender and degree program in the credibility assigned to the news. The
conclusion is that university students have difficulty differentiating the veracity of the
sources, in line with previous studies, with fake news earning higher ratings than real
news.”
Gottfried and Shearer (2016) [60] report that in the US, 62% of adults get their
news from social media and that about one third say they trust the information they
get from social media ‘some’ or ‘a lot’. Once again, these findings are based on self-
reported statements.
Regarding the role of generational differences in the dissemination of fake news,
we found one recent study by Guess et al. [46, p. 1], who write that they examined
the individual-level characteristics associated with sharing false articles during the
2016 U.S. presidential campaign. “To do so, we uniquely link an original survey with
respondents’ sharing activity as recorded in Facebook profile data. First and foremost,
we find that sharing this content was a relatively rare activity. Conservatives were
more likely to share articles from fake news domains, which in 2016 were largely pro-
Trump in orientation, than liberals or moderates. We also find a strong age effect,
which persists after controlling for partisanship and ideology: On average, users over
65 shared nearly seven times as many articles from fake news domains as the
youngest age group.”
Finally, we refer to an original empirical study conducted by Roozenbeek and Van
der Linden [61] who developed a game drawing on “an inoculation metaphor, where
preemptively exposing, warning, and familiarizing people with the strategies used in
the production of fake news helps confer cognitive immunity when exposed to real
misinformation. We conducted a large-scale evaluation of the game with N=15,000
participants in a pre-post gameplay design. We provide initial evidence that people’s
ability to spot and resist misinformation improves after gameplay, irrespective of
education, age, political ideology, and cognitive style. (…) There was a significant
difference for age so that older players adjusted their reliability ratings somewhat less
(…), although the standardized difference was so small that it can be considered
negligible.”
As the findings of the empirical studies discussed in this section demonstrate,
there is a lack of research into the role of age regarding the consumption of Fake
News on social media. We therefore decided to conduct an empirical study ourselves,
with the aim of generating more insight into this field.
3. Materials and Methods
To gain a better understanding of the generational dynamics in the online
consumption of fake news and the perception of fake news by its audiences (e.g.,
[62]), the second author of this paper created, together with a Belgian fact checker
(see acknowledgements), a fake news website of their own. We copied the approach
of ‘real’ fake news websites and chose Facebook as the social media platform to
disseminate the stories. Facebook offers page owners insights into their audiences and
makes it possible to analyze who that audience is. Moreover, Facebook is the platform
of choice for many fake news websites because it offers the opportunity to create
targeted advertisements and increase their post reach by ‘boosting’ the posts,
enabling larger audiences to be reached. We launched a fake news website, that
closely mimicked ‘real’ fake news websites, making use of click-bait styled articles
featuring the same type of language and tactics as ‘real’ fake news websites (e.g.
playing into preexistent biases, sparking outrage, making absurd claims). We used a
simple Wordpress website and a Facebook account to disseminate our articles, just as
fake news websites do. The only difference with ‘real’ fake news was that our posted
articles contained a surprise message about fake news for readers actually clicking on
the link (see Appendix1 and 2 for the text of the post).
Our posts followed the usual structure: a clickbait headline with a clear image was
posted on Facebook; users clicking on the link were redirected to our website where
they could read the first paragraph/introduction of the article with the made-up news.
In the middle of the article, a question was asked (or we stopped halfway through a
sentence), which was first followed by a few blank lines or an image and then came
the surprise message aimed at educating users about fake news.
Facebook offers page users the opportunity to ‘boost’ posts, which is basically a
feature that turns Facebook posts into online advertisements. This can be used to
reach a greater audience, and to appear on the timeline of people who do not follow
the page the article is published on. The feature also includes a menu with specific
audience targeting options based on demographic information like location, age,
gender and interests.
We posted 14 political fake news articles (see below for more information) and
used €50 per article to create the advertisements, which we targeted at different
audiences. All of our audiences were based in the UK and/or the USA and included
people who had shown interest in the topic of the article (i.e., the political articles
were targeted at people who, according to Facebook, were ‘Likely to engage with
political content’ (conservative)’, ‘Likely to engage with political content (liberal)’ or
‘Likely to engage with political content (moderate)’. The age group option was set to
13-17, 18-24, 25-34, 35-44, 45-54, 55-64, 65+.
Once the advertisements were created and approved by an automated Facebook
tool, the ads ran for seven days. During these seven days, the Facebook algorithms
showed the advertisements to different audiences (based on non-specified
demographics to avoid any bias) in an effort to maximize the reach for the dedicated
budget. The articles were not published on different pages or platforms, but were
written in as ‘clickbaity’ style as possible, after which we let the Facebook algorithm
do the work for us. Facebooks algorithms tend to include previous user behavior and
current engagement with similar content in order to optimize the reach (appearances
on peoples timelines) of each advertisement.
Regarding the content of the articles, we observed the following ethical guidelines:
No use of racism, hate speech or real conspiracies. Use vague language so people can
fill in the blanks (‘they’, ‘experts’, etc.). Don’t show ads on the website. Don’t use
spam tactics, such as bought likes and fake profiles. Show a surprise educational
message about fake news once people click on the link.
For the topics of our fake news Facebook posts we decided to write articles playing
into the biases of two groups within a polarized debate. The following two examples
illustrate this approach: 1. We posted an article on the Big Ben, the famous British
monument, reporting that it would allegedly be moved from London to Brussels
because of Brexit. We expected this news to antagonize both the remain camp (it’s the
fault of Brexit) and the Brexit camp (it’s the fault of Brussels). 2. Our posted article
on Donald Trump’s Wall, who allegedly had to pay royalties to China for using the
words ‘the wall’. We expected this to spark outrage amongst his supporters, and glee
amongst his opponents.
We hoped to discover whether age was a factor in the extent to which these
political groups became outraged by this political fake news, without even clicking on
the link or doing some simple fact-checking. We come back to these two cases in
section 4 (see also Appendix 1 and 2).
These two posted articles were part of a total of 14 articles bearing, in no particular
order, the following headlines: ‘BREAKING: Plans revealed to skip National anthem
during superbowl!!’; ‘Is Valentine’s Day a communist holiday?!’; ‘Horrific! Can You
See Why This Local Pedophile Got Exactly What He Deserved?’; ‘Experts: Trump
must pay royalties to Chinese government for the ‘Wall’.’; ‘Big Ben to be moved to
Brussels because of Brexit?!’; ‘Breaking: Reservation of Proud Native Tribe Declares
Independence!’; ‘Huge Cambridge Analytica Data Leak! Is Your Data Affected?’;
‘Tables Turned: Personal info of every US company leaked!!’; ‘JUST IN: You Won’t
Believe Who Is Scrambling In Full Panic Mode After The Shocking Truth Is
Revealed’; ‘Experts: Blocking Website Visitors For GDPR Reasons Is Illegal Under
GDPR’; ‘BREAKING: this celebrity just got arrested for domestic violence!!’;
‘Russian influence suspected in 2018 FIFA World Cup!!’; ‘New Treatment Kills
Cancer Cells From 500 Yards Away’; and ‘Campaign to save the Pacific Northwest
tree octopus is gaining momentum’.
We spent 700 euros to boost these articles, while using different topics in order to
diversify our audiences as much as possible. Strikingly, Facebook permitted all of the
posts to be turned into advertisements. We collected our data with the help of the
Facebook ‘insights’ tool, and Facebook’s ‘ad center’ in the period from the beginning
of February 2018 to the end of June of 2018.
4. Results
We reached 119,982 people with the 14 articles we posted, 41.2% of whom were
women and 58.8% men. A mere 12.7% of those reached actually clicked on the link to
our website, while the rest only saw the headline of the article on Facebook. In other
words, 87.3% did not have the opportunity to read our surprise educational message
about fake news. We reached the following age groups (following Facebook’s age
segmentation based on the following age-groups): 13-17: 5,293 (4.4%), 18-24: 6,856
(5.7%), 25-34: 14,265 (11.9%), 35-44: 15,928 (13.3%), 45-54: 22,051 (18.4%), 55-
64: 29,603 (24.7%), 65+: 25,736 (21.5%).
Fig. 1. Fake news consumption by age group (N) for all 14 posted articles
Fig. 1. shows that persons of all ages consumed the 14 posted articles. This is an
important finding, as intervention programs such as the #SaferInternet4EU Campaign
by the European Commission [34] (see also section 1) are specifically targeted at
schools. Media literacy programs in primary and secondary education are often
mentioned as a way to combat fake news (e.g., [31-33]), but Fig. 1 clearly
demonstrates the need to target older people as well.
The headlines triggered many emotions and drew much comment in the comment
section below the post on Facebook (see Appendix 1 and 2 for some examples). A
closer look at two of our more popular and antagonizing posts reveals more about the
Facebook audience these attracted.
Our posted article on the Big Ben (see also Appendix 1) reached 11,094 people
(women: 29.3%, men: 70.7%), and collected 178 comments directly on the post. Of
these, 12.92% had read the article and got the joke, 19.22% responded emotionally
with a pro-Brexit stance; 3.37% responded emotionally with an anti-Brexit stance;
24.73% responded emotionally without a clear political affiliation; 28.56% responded
with skepticism, and 10.67% responded in other ways. Fig. 1 shows that the posted
articles had a higher reach amongst older age groups than the younger ones, which
could be due to the type of news (political).
Table. 1 Fake news consumption by age group (%) for the post on the Big Ben
13-17: 0%
18-24: 0%
25-34: 8%
35-44: 11%
45-54: 18%
55-64: 27%
65+: 36%
Fig. 2. Fake news consumption by age group (N) for the posted article on the Big Ben
Interestingly, while this post failed completely to reach the two youngest age groups,
we found that all the other age groups consumed the news of this post.
Our posted article on Donald Trump’s Wall (see also Appendix 2) reached 7,500
people (women: 29.8%, men: 70.2%), and got 108 comments. Of these, 12.04% had
read the article and got the joke; 20.37% responded emotionally with a pro-Trump
stance; 5.56% responded emotionally with an anti-Trump stance; 12.96% responded
emotionally without a clear political affiliation; 44.44% responded with skepticism;
and 4.63% responded in other ways.
Table 2. Fake news consumption by age group (%) for the post on Donald Trump’s
Wall
13-17: 0%
18-24: 3%
25-34: 8%
35-44: 11%
45-54: 19%
55-64: 31%
65+: 28%
Fig. 3. Fake news consumption by age group (N) for the post on Donald Trump’s
Wall
As Fig. 3 shows, the youngest age group was wholly uninterested, and the 18-24-
year-olds in this audience were only barely interested in this post. However, the other
age groups were clearly interested in the news of this post.
Hence these two items proved to act as emotional triggers for people, who were
then happy to broadcast their political views even without clicking on the link to read
the entire article (see also Appendix 1 and 2). Of those who commented, only 12.04%
and 12.92% had clearly read the article and understood that it was meant as a lesson
on Fake News. Some 28.56% and 44.44% respectively displayed an instinctive
skepticism without elaborating on a lesson having been learned. They may very well
have therefore not clicked on the link as they disbelieved the headline of the article to
begin with. Those responding emotionally (whether with anger, insults or with
satisfaction at the news) showed no indication of having learned any lesson or of
having understood the purpose of the article. They are likely not to have clicked on
the article for further reading and simply to have taken the headline at face value. Of
those with emotional responses, 19.22% were pro-Brexit and 20.37% pro-Trump
versus 3.37% who were anti-Brexit and 5.56% anti-Trump. This might imply that the
pro-Brexit and pro-Trump groups are both more likely to believe and actively
comment on fake news and are more easily emotionally triggered.
5. Conclusions, Limitations and Implications for Future
Research
This paper focused on the following research question: What is the role of age in fake
news consumption on social media? Our review of previous empirical studies in this
field showed that prior to this study, generational differences had not yet been studied
in relation to this topic. A limited number of empirical studies had collected data on
the way younger people consumed this kind of news. The overall conclusion was that
the media literacy of the young in relation to fake news is not yet very well
developed. Or, in the words of Wineburg and McGrew (2016) [58]: “Our “digital
natives” may be able to flit between Facebook and Twitter while simultaneously
uploading a selfie to Instagram and texting a friend. But when it comes to evaluating
information that flows to social media channels, they are easily duped. (SHEG, 2016,
p .4) [57].” The one study (conducted by Gottfried and Shearer, 2016 [60]) we found
that looked at older adults reports that in the US, 62% of adults get their news from
social media, and that about one third say they trust the information they get from
social media ‘some’ or ‘a lot’. These findings, it should be noted, are based on self-
reported statements.
The lack of empirical studies comparing the extent to which different generations
consume fake news on social media was the reason for conducting an empirical study
aimed at providing insight into such generational differences. We posted 14 political
fake news articles containing a surprise educational message about fake news, as
advertisements on Facebook. User interaction with the fake content was tracked in
order to analyze the number of users in the age groups 13-17, 18-24, 25-34, 35-44,
45-54, 55-64, 65+. Fig. 1, 2 and 3 in section 4 show that the posted articles had a
higher reach amongst older age groups than the younger ones, which could well be
due to the kind of political news posted.
While the algorithms of Facebook are somewhat of a ‘black box’, using the same
tactics and articles should produce a similar reach of these fake news pages amongst
these age groups. Whether the algorithm pushed these stories based on previous
behavior of the target audience or because the level of engagement was higher
amongst the older age groups is not important for the end result; the fact remains that
the stories had a higher reach amongst older age groups.
This is an important finding, as intervention programs such as the
#SaferInternet4EU Campaign [34] by the European Commission (see also section 1)
are targeted at schools, while our empirical study shows that we also need to target
people who are older.
Also noteworthy is the fact that only 12.7% of the people our posts reached
actually clicked on the link. Given the number of emotional responses, it seems likely
that many persons took the headlines at face value. Of the people who responded
emotionally, those in both the pro-Brexit and pro-Trump groups were more likely to
believe and actively comment on fake news, and were more easily emotionally
triggered.
A limitation of our study is that we do not know whether, in a real life situation,
people would have distributed the post to others. Future empirical studies should
address this point (for example by conducting a controlled experiment) and should
also include the role of gender, educational level and nationality. In addition, other
types of articles than political fake news articles alone should be posted: age groups
could differ in their preferences regarding types of articles. The Facebook
advertisement tool allowed all of the articles to be published, but under the new
regulations introduced after we conducted our study, this is no longer likely to be the
case. The set-up of the present empirical study could be used as a guideline for the
design of future evidence-based empirical studies to gain more insight into the
generational dynamics of fake news consumption on social media, the audience’s
perception and the effectiveness of Facebook’s tools in combatting fake news.
Another limitation is that we did not track the interactions of the audiences with the
website. A tracking tool based on cookies or the ‘Facebook Pixel’ could have helped
to learn more about who actually clicked on the headlines to find out more. For future
studies we would recommend implementing tracking tools on the website to identify
the role of age in source verification (fact-checking). A more thorough analysis (with
the inclusion of a variety of age groups) of the comments is also recommended, as,
due to privacy restrictions, this was not possible on a public Facebook page.
6. Acknowledgements
We would like to thank Belgian fact-checker Maarten Schenk, who created the Fake
News website together with the second author of this paper, which made it possible
to disseminate the fake news stories on Facebook. This paper is part of the research
project BConnect@Home (https://www.jp-demographic.eu/wp-
content/uploads/2017/01/ BCONNECT_2017_conf2018_brochure.pdf ), funded by the
JTP 2017 - JPI More Years, Better Lives (Grant Agreement 363850) - the
Netherlands, ZONMW (Project 9003037411).
References
1. Carey, K.M.: Fake News: How Propaganda Influenced the 2016 Election, a Historical
Comparison to 1930's Germany. Marzenhale Publishing, Snow Hill: Maryland (2017)
2. Swart, J., Peters, C., Broersma, M.: Shedding light on the dark social: The connective role
of news and journalism in social media communities. New Media & Society 20(11), 4329-
4345 (2018)
3. Van der Horst, H. (2018). Nepnieuws. Een wereld van desinformatie [Fake News: A world
of disinformation]. Scriptum, Schiedam (2018)
4. Edgerly, S., Mourão, R.R., Thorson, E., Tham, S.M.: When Do Audiences Verify? How
Perceptions About Message and Source Influence Audience Verifica-tion of News
Headlines. Journalism & Mass Communication Quarterly, 1077699019864680 (2019)
5. Goyanes, M. (2019): Antecedents of Incidental News Exposure: The Role of Media
Preference, Use and Trust. Journalism Practice, 1-16.
6. Must ţea, M., Balaban, D.C.: News Sharing on Social Media Platforms. Theoreticalǎ
Approaches: In Iancu, I., Balaban, D.C., I. Hosu, I. (eds.) Communication. Strategic
Perspectives, pp. 66-80. Babeș-Bolyai University Cluj-Napoca PR Trend International
Conference February the 26th–the 27th 2018. Accent, Cluj-Napoca, Romania (2019)
7. Obadă, R.: Sharing Fake News about Brands on Social Media: a New Conceptual Model
Based on Flow Theory Argumentum. Journal of the Seminar of Discursive Logic, Argu-
mentation Theory and Rhetoric 17(2): 144-166 (2019)
8. Gelfert, A.: Fake News: A Definition. Informal Logic 38(1), 84-117 (2018)
9. McGonagle, T.: Fake news: False fears or real concerns?. Netherlands Quarterly of Human
Rights 35(4): 203-209 (2017)
10. Nimrod, G.: Older audiences in the digital media environment. Information,
Communication & Society 20(2), 233-249 (2017)
11. Aldwairi, M., Alwahedi, A.: Detecting Fake News in Social Media Networks. Procedia
Computer Science 141, 215-222 (2018)
12. Rawls, J.: Political liberalism. New York, Columbian University Press (1993)
13. Van den Hoven, M.J. (1994), “Towards ethical principles for designing politico-
administrative information systems”, Informatization and the public sector , Vol. 3 No.3/4,
pp. 353-373 (1994)
14. Bovens, M.A.P.: Information rights. Citizenship in the information society. Journal of
Political Philosophy 10(9), 317-341 (2002)
15. Bovens, M.A.P., Loos, E.F.: The digital constitutional state: democracy and law in the
information society. Information Polity 7(4) 185-197 (2002)
16. De Jong, J., Rizvi, G.: The State of access. Success and Failure of Democracies to Create
Equal Opportunities. Brookings Institution Press, Washington (2008)
17. Humprecht, E.: Where ‘fake news’ flourishes: a comparison across four Western
democracies. Information, Communication & Society 22(13), 1973-1988 (2019)
18. Loos, E.F., Romano Bergstrom, J. (2014). Older adults. In: J. Romano Bergstrom and A.J.
Schall (Eds.), Eye Tracking in User Experience Design, pp. 313-329. Elsevier, Amsterdam
19. Loos, E.F.: In Search of Information on Websites: A Question of Age? In: C. Stephanidis
(Ed.), Universal Access in HCI, Part II, pp. 196-204. Springer, Berlin (2011)
20. Hill, R., Dickinson, A., Arnott, J., Gregor, P., McIver, L.: Older users’ eye movements:
Experience counts, CHI 2011, May 7-12 Vancouver, British Colombia, Canada (2011)
21. Loos, E.F.: Senior citizens: Digital immigrants in their own country?, Observatorio
(OBS*) Journal 6 (1), 1-23 (2012)
22. Loos, E.F.: De oudere: een digitale immigrant in eigen land? Een terreinverkenning naar
toegankelijke informatievoorziening. [oratie] Older people: Digital Immigrants in their
own country? Exploring accessible information delivery [inaugural lecture]. Den Haag:
Boom/Lemma, Den Haag (2010)
23. Quinn, K.: Older adults and social media. In: P.G. Nixon, R. Rawal and A. Funk (Eds.).
Digital media usage across the life course, pp. 132-145. Routledge, Abingdon, Oxon,
(2016)
24. Rogers, E.M.: Diffusion of Innovations. Free Press, New York (2003)#
25. PEW: Tech Adoption Climbs Among Older Adults, May, 17, 2017,
https://www.pewinternet.org/2017/05/17/tech-adoption-climbs-among-older-adults/ (2017)
26. Standard Eurobarometer: Media use in the European Union (2017)
https://www.google.com/url?
sa=t&rct=j&q=&esrc=s&source=web&cd=1&ved=2ahUKEwicu-
fIrtziAhUFJ1AKHZRPBbUQFjAAegQIAxAC&url=https%3A%2F%2Fec.europa.eu
%2Fcommfrontoffice%2Fpublicopinion%2Findex.cfm%2FResultDoc%2Fdownload
%2FDocumentKy%2F82786&usg=AOvVaw17UrDp_hb6W7jBAMXEa6Ic
27. PEW: Share of U.S. adults using social media, including Facebook, is mostly unchanged
since 2018, April, 10, 2019 (https://www.pewresearch.org/fact-tank/2019/04/10/share-of-u-
s-adults-using-social-media-including-facebook-is-mostly-unchanged-since-2018/) (2019)
28. Holt, K., Shehata, A., Strömbäck, J., Ljungberg, E.: Age and the effects of news media
attention and social media use on political interest and participation: Do social media
function as leveller? European Journal of Communication, 28(1), 19-34 (2013)
29. Ofcom: Adults: Media use and attitudes report 2019,
https://www.ofcom.org.uk/__data/assets/pdf_file/0021/149124/adults-media-use-and-
attitudes-report.pdf (2019)
30. Newman, N., Fletcher, R., Kalogeropoulos, A., Levy, D., Nielsen, R.K.: Reuters Institute
digital news report 2017 (2017)
31. Leu, D.J., Reinking, D., Carter, A.,Castek, J., Coiro, J., Henry, L.A.,Maloy, J., Robins, K.,
Rogers, A., Zawilinski, L.: “Defining online reading comprehension: using think aloud
verbal protocols to refine a preliminary model of Internet reading comprehension
processes”, D. Alvermann (Chair) 21st Century Literacy: What is It, How do Students Get
It, and How do We Know if They have It (2007)
32. Loos, E. F., Ivan, L., Leu. D.: “Save The Pacific Northwest Tree Octopus”: a hoax
revisited. Or: how vulnerable are school children to Fake News? Information and Learning
Science 119(9, 10) (2018)
33. Pilgrim, J., Vasinda, S., Bledsoe, C., Martinez, E.: Critical Thinking Is Critical: Octopuses,
Online Sources, and Reliability Reasoning. The Reading Teacher 73(1), 85-93 (2019)
34. European Commission: Tackling online disinformation, https://ec.europa.eu/digital-single-
market/en/tackling-online-disinformation (accessed 08.08.2019)
35. Allcott, H., Gentzkow, M., Yu, C. (2019). Trends in the diffusion of misinformation on
social media. Research & Politics 6(2), 2053168019848554.
36. Mosinzova, V., Fabian, B., Ermakova, T., Baumann, A. (2019). Fake News, Conspiracies
and Myth Debunking in Social Media-A Literature Survey Across Disciplines.
Conspiracies and Myth Debunking in Social Media-A Literature Survey Across Disciplines
(February 3, 2019).
37. Flintham, M., Karner, C., Bachour, K., Creswick, H., Gupta, N., Moran, S. (2018, April).
Falling for fake news: investigating the consumption of news via social media. In
Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (p.
376). ACM.
38. Quintanilha, T.L., Silva, M.T.D., Lapa, T.: Fake news and its impact on trust in the news.
Using the portuguese case to establish lines of differentiation. Fake news and its impact on
trust in the news. Using the portuguese case to establish lines of differentiation, (3), 17-33
(2019)
39. Resende, G., Melo, P., Reis, J. C., Vasconcelos, M., Almeida, J. M., Benevenuto, F.
(preprint): Analyzing Textual (Mis) Information Shared in WhatsApp Groups. (2019)
40. Meinert, J., Mirbabaie, M., Dungs, S., Aker, A.: Is it really fake?–Towards an
understanding of fake news in social media communication. In International Conference
on Social Computing and Social Media, pp. 484-497). Springer, Cham (2018)
41. Waisbord, S. (2018). Truth is what happens to news: On journalism, fake news, and post-
truth. Journalism studies 19(13), 1866-1878.
42. Allcott, H., Gentzkow, M. (2017). Social media and fake news in the 2016 election.
Journal of economic perspectives 31(2), 211-36.
43. Bakir, V., McStay, A.: Fake news and the economy of emotions: Problems, causes,
solutions. Digital journalism 6(2), 154-175 (2018)
44. Guo, L., Vargo, C.: “Fake News” and Emerging Online Media Ecosystem: An Integrated
Intermedia Agenda-Setting Analysis of the 2016 US Presidential Election. Communication
Research, 0093650218777177 (2018)
45. Guess, A., Nyhan, B., Reifler, J.: Selective exposure to misinformation: Evidence
from the consumption of fake news during the 2016 US presidential campaign. European
Research Council, 9 (2018)
46. Guess, A., Nagler, J., Tucker, J.: Less than you think: Prevalence and predictors of fake
news dissemination on Facebook. Science advances 5(1), eaau4586 (2019)
47. Mehta, R., Guzmán, L.D.: Fake or Visual Trickery? Understanding the Quantitative Visual
Rhetoric in the News. Journal of Media Literacy Education 10(2), 104-122 (2018)
48. Pierri, F., Artoni, A., Ceri, S.: Investigating Italian disinformation spreading on Twitter in
the context of 2019 European elections. arXiv preprint arXiv:1907.08170. (2019)
49. Morstatter, F., Shao, Y., Galstyan, A., Karunasekera, S.: From alt-right to alt-rechts: Twitter
analysis of the 2017 german federal election. In: Companion Proceedings of the The Web
Conference 2018, pp. 621-628). International World Wide Web Conferences Steering
Committee, April 2018 (2018)
50. Broersma, M., Graham, T. (2012). Social media as beat: Tweets as a news source during
the 2010 British and Dutch elections. Journalism practice 6(3), 403-419 (2012)
51. Dutton, W. H., Reisdorf, B., Dubois, E., Blank, G.: Search and politics: The uses
and impacts of search in Britain, France, Germany, Italy, Poland, Spain, and the United
States (2017)
52. Fedeli, G.: Fake news’ meets tourism: a proposed research agenda. Annals of Tourism
Research (2019).
53. Shu, K., Liu, H.: Detecting Fake News on Social Media. Morgan & Claypool, Williston
(2019)
54. Chiluwa, I.E., Samoilenko, S.A.: Handbook of Research on Deception, Fake News, and
Misinformation Online. IGI Global (2019)
55. Livingstone, S., Haddon, L., Vincent, J., Mascheroni, G.; Ólafsson, K.: Net children go
mobile: The UK report, available at: http://eprints.lse.ac.uk/59098/ (2014)
56. Marchi, R.: With Facebook, blogs, and fake news, teens reject journalistic “objectivity”.
Journal of Communication Inquiry 36(3), 246-262 (2012)
57. SHEG (Stanford History Education Group: Evaluating information: The cornerstone of
civil online reasoning. Research Report, available at: www.sheg.tandford.edu (2016)
58. Wineburg, S., McGrew, S.: Why students can't google their way to the truth. Education
Week 36 (11), 22-28.
59. Herrero-Diz, P., Conde-Jiménez, J., Tapia-Frade, A., Varona-Aramburu, D.: The credibility
of online news: an evaluation of the information by university students/La credibilidad de
las noticias en Internet: una evaluación de la información por estudiantes universitarios.
Cultura y Educación 31(2), 407-435 (2019)
60. Gottfried, J., Shearer, E.: News use across social media platforms 2016”. Pew Research
Center, 26, available at: http://www.journalism.org/2016/05/26/ (2016)
61. Roozenbeek, J., Van der Linden, S.: Fake news game confers psychological resistance
against online misinformation. Palgrave Communications 5(1), 12 (2019)
62. Tandoc Jr, E. C., Ling, R., Westlund, O., Duffy, A., Goh, D., Zheng Wei, L.: Audiences’
acts of authentication in the age of fake news: A conceptual framework. New Media &
Society 20(8), 2745-2763 (2018)
Appendix 1
Fake News post on the Big Ben
Since the EU paid for the current renovation of the Big Ben tower in London some
people are claiming that the tower should be moved to Brussels. The UK has voted to
leave the European Union and is scheduled to depart on Friday 29 March, 2019. The
UK and EU have provisionally agreed on the three “divorce” issues of how much the
UK owes the EU, what happens to the Northern Ireland border and what happens to
UK citizens living elsewhere in the EU and EU citizens living in the UK. Talks are
now moving on to future relations, and the Big Ben tower in London could become
part of those talks. 80% of the funding for the renovation of the tower is contributed
by the EU and now people want their money back!
Which people, you might ask..
Well.. None!!
Because this article is Fake!
It is written to show you how easy it is to create false headlines, and how dangerous
they are. Websites that post click-baity headlines often fill their pages with ads, and
are making a shitload of money. These headlines often include outrageous claims
which are not supported by evidence. By clicking on unfounded sensational news you
contribute to the spreading of fake news. The only thing we can do is undermining
their business model!
So next time you see a headline like ours? Think twice about clicking on the link!
Target audience for advertisement (Facebook options)
Living in: United Kingdom
Age: 13-65+
People who match: Interests: Theresa May, Big Ben, Boris Johnson, London or
UNILAD and Politics: Likely to engage with political content (conservative) or
Likely to engage with political content (liberal)
Facebook results (some examples)
- Headline: ‘Big Ben to be moved to Brussels because of Brexit?!’
- Persons reached: 11.094 persons (women: 29,3%, men: 70,7%)
- 355 reactions (104 likes, 1 love, 226 haha, 4 wow, 20 angry)
- 206 comments (178 on post, 28 on shares)
- 47 shares
- 1.515 Post clicks (redirects to website) = 13.66%
178 comments directly on post (including some examples)
Read the article and got the joke: 23 (12.92%)
- “If you read it. It says that it fake news. Made up to see how things spread on
the internet.”
- “Amazing comments on here. Does anyone actually read the full article these
days? Or are you all happy just to read a headline and get angry?”
Emotional pro-Brexit: 35 (19.66%)
- “Teresa may is giving the EU all our other assets and freedoms they may as
well have this to”
- “Might as well as the bells will be in the way of the call of prayer 5 times a
day . . One they cleared out free speech”
Emotional anti-Brexit: 6 (3.37%)
- “Can you imagine the look on brexiters faces if this had to happen? Would
be comedy moment of the century.”
- “Aww crying Brexiters really perk up my day...”
Emotional without clear affiliation: 44 (24.73%)
- “O fuck off”
- “Yep & take all the corrupt pigs in the troth with it , weak government , no
morals all on the take , time to sort em out !”
Skeptical: 51 (28.65%)
- “yeah sure”
- “Sounds like April fool”
Other: 19 (10.67%)
- Reply to friend: “With you I'm always right
- “And apparently we are going to have to keep the maroon Passports as we
cannot make blue ones in the UK!!!”
Appendix 2
Fake News post on Donald Trump’s Wall
Experts claim that Donald J. Trump has to pay royalties to the Chinese government
for the ‘Wall’.
President Donald Trump has set in motion his plan to build an “impenetrable,
physical, tall, powerful, beautiful, southern border wall” between the US and Mexico.
This border is about 1,900 miles (3,100 km) long and traverses all sorts of terrain. But
what he does not know, is that the collection of fortifications known as the ‘Great
Wall of China’ has exclusive rights on the term “Wall”.
In Chinese histories, the term “Long Wall(s)” (長長) appears in Sima Qian’s Records of
the Grand Historian, where it referred to both the separate great walls built between
and north of the Warring States and to the more unified construction of the First
Emperor. The longer Chinese name “Ten-Thousand Mile Long Wall” (長長長長) came
from Sima Qian’s description of it in the Records, though he did not name the walls as
such. The ad 493 Book of Song quotes the frontier general Tan Daoji referring to “the
long wall of 10,000 miles” Because of the wall’s association with the First Emperor’s
supposed tyranny, the Chinese dynasties after Qin usually avoided referring to their
own additions to the wall by the name “Long Wall”.
The current English name evolved from accounts of “the Chinese wall” from early
modern European travelers. By the 19th century, “The Great Wall of China” had
become standard in English, French, and German, although other European languages
continued to refer to it as “the Chinese wall”. Since then a copyright has been
imposed on Wall-like structures by the Chinese government. And now they are
preparing a lawsuit against Donald Trump.
They’ll see him in court!
The court date has been set for never.. Because, this article is a lot of bogus. We wrote
this article to show you how easy it is to make people believe in wild stories.. You
probably clicked on this link because you thought it was funny, it made you angry or
sparked your interest.
We are sorry to break it to you, but articles that are too crazy to believe, are probably
not true!
Keep that in mind next time you see a headline like ours ;-)
Target audience for advertisement (Facebook options)
Living in: United States
Age: 13-65+
People who match: Politics: Likely to engage with political content (conservative),
Likely to engage with political content (liberal) or Likely to engage with political
content (moderate)
Facebook results (some examples)
- Headline: ‘Experts claim that Donald J. Trump has to pay royalties to the
Chinese government for the ‘Wall’. They’ll see him in court!’
- Persons reached: 7.500 people (women: 29.8%, men: 70,2%)
- 355 reactions (189 likes, 11 love, 344 haha, 10 wow, 1 sad, 28 angry)
- 118 comments (108 on post, 10 on shares)
- 121 shares
- 491 Post clicks (redirects to website) = 6.55%
108 comments directly on the post (including some examples):
Read the article and got the joke: 13 (12.04%)
- “Yeah. Good joke”
- “It’s nothing Other than a humorous joke😂😂
Emotional pro-Trump: 22 (20.37%)
- “Maybe we can hire Chinese labor to build the wall that Mexico is going to
build.”
- “Oh my! Liberals will try anything to make our President look bad! Give it
up already!”
Emotional anti-Trump: 6 (5.56%)
- “Good luck! He filed Bankruptcy on the million his Dad lent him. Never
paid Daddy back either. His Attorneys will handle it.”
- “Trump sucks on all levels.”
Emotional without clear affiliation: 14 (12.96%)
- “BULLSHIT, NOTTA going to happen.”
- “STOP YOUR BULL. CHINA DIDN’T INVENT WALLS.”
Skeptical: 48 (44.44%)
- “Fake all the way. America doesn’t pay China for any wall. Only total idiots
would believe this”
- “I guess I will also have to pay there is a “wall” in my backyard and the one
inside
Other: 5 (4.63%)
- “[Tag of a friend]”
- “[GIF]”
ResearchGate has not been able to resolve any citations for this publication.
ResearchGate has not been able to resolve any references for this publication.