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Rasmus Kleis Nielsen
Misinfocon London, hosted by the Mozilla
Foundation and Hacks/Hackers
October 24, 2018
@risj_oxford
MISINFORMATION —
Public perceptions and
practical responses
2
Q10a_new2017_rc. Which of these was the
MAIN way in which you came across news in
the last week? Base: All/under 35s that used
a gateway to news in the last week: All
markets = 69246/19755.
See Newman et al (2018) 2018 Reuters Institute Digital News Report.
The rise of distributed discovery
All markets
Far from creating filter bubbles, distributed discovery
often exposes people to more sources
3
Automated serendipity means that
people who use search and social
media (and news aggregators)
tend to use more sources of news
and greater diversity of sources
than those that don’t
The effect of incidental exposure
to news on social media is
particularly clear for the young
and those least interested in news
See e.g. Fletcher and Nielsen (2018) “Are people incidentally exposed to news on
social media? A comparative analysis,” New Media & Society 20 (7): 2450-2468
4
“IT’S THEIR JOB … TO
REPORT THE FACTS”
Q2. You recently viewed a story with the headline X. On which of the following news websites did you read this story? If you read it on more than one, please
select all that apply. Showing share of correct brand attributions. Base: Direct 1,098/ Search 1,022/ Social 1,008 (Facebook 795, Twitter 194)
2X difference
But brand attribution is a problem …
Fewer than half can remember the news brand that produced a story when
coming from social media or search
See e.g. Kalogeropoulos et al (2018) “News brand attribution in distributed
environments: Do people know where they get their news?,” New Media & Society
5
ALL 37 MARKETS - % THAT TRUST EACH MOST OF THE TIME
Uncertainty in distributed environments, information
unchecked, hard to distinguish news from rumor...
Mostly this about trust in mainstream media
and in the sources that people use
Trust news
I use
44%
Trust news
overall
51%
Trust news
in search
34%
Trust news
in social
23%
See Newman et al (2018) 2018 Reuters Institute Digital News Report.
… as is trust
85%
71% 69% 66% 66% 66% 65% 64% 63% 63% 62% 61% 60% 60% 60% 60% 58% 57% 55% 53% 51% 50% 50% 49% 49% 48% 47% 46% 44% 43% 42% 41% 38% 37% 36% 36%
30%
54%
0%
20%
40%
60%
80%
6
Q_FAKE_NEWS_1. Please indicate your level of agreement with the following statement. “Thinking about online news, I am concerned about what is real and what is fake on the
internet.” Base: Total sample in each market
Brazil
Issue in the elections
Spain
Catalan independence
a flashpoint
Germany
Low level concern
post election
USA
Popularised by Trump
and the media itself
See Newman et al (2018) 2018 Reuters Institute Digital News Report.
Varied concern over whether online news is real or fake
See Nielsen and Graves (2017) “’News you don’t believe’: Audience Perspectives
on Fake News”.
Audience perspectives on “fake news”
8
What type of ‘f*ke news’ do people say they are EXPOSED to?
ALL MARKETS
see poor
journalism,
mistakes and
clickbait every
week
42% complain about
spin and agenda-
filled news
39% say they have
been exposed to
completely made
up news
26%
Only
See Newman et al (2018) 2018 Reuters Institute Digital News Report.
Audience definitions of problem are much wider
9
See Newman et al (2018) 2018 Reuters Institute Digital News Report.
Concern versus exposure to types of misinformation etc
Q_FAKE_NEWS_2. To what extent, if at all, are you concerned about the following and Q_FAKE_NEWS_3. In the LAST WEEK which of the following have you personally come across? Please select all that apply.
Base: All markets 2018 – USA: 2401; UK: 2117; Germany: 2038; France: 2006; Italy: 2040; Spain: 2023; Portugal: 2008; Ireland: 2007; Norway: 2027; Sweden: 2016; Finland: 2012; Denmark: 2025; Belgium: 2006; Netherlands: 2010; Switzerland: 2120; Austria: 2010; Hungary: 2005; Slovakia: 2006; Czech
Republic: 2020; Poland: 2005; Romania: 2048; Bulgaria: 2021; Croatia: 2010; Greece: 2014; Turkey:2019; Japan: 2033; Korea: 2010; Taiwan: 1008; Hong Kong: 2016; Malaysia: 2013; Singapore: 2018; Australia: 2026; Canada: 2022; Brazil: 2007; Argentina: 2012; Chile: 2008; Mexico: 2007
10
3. GOVERNMENT
61%
1. PUBLISHERS
75%
2. PLATFORMS
71%
41%60%
“It’s free speech right?
(F, 20-29, USA)
“content is now removed
within a few hours.”
(M, 30–45, Germany)
See Newman et al (2018) 2018 Reuters Institute Digital News Report.
Who bears the biggest responsibility to fix the problems?
Q14_2018a_combined2. News literacy scale. Q_FAKE_NEWS_4_2_1-3. Please indicate your agreement with the following statements. Technology companies/media companies/the government
should do more to make it easier to separate what is real and fake on the internet. Base: All with very low/low/high/very high news literacy: Selected markets = 11149/11898/8069/3790.
Key points
The move to
distributed
discovery is
demonstrably
expanding people’s
news diets…
… and in many
countries we see
high levels of
concern over what
is real and what is
fake in the news…
… concerns that are
fanned by
politicized use of
the term “f*ke
news” and wide
attention to it and
draw on deep-
seated and much
broader concerns…
… but people often
don’t recognize
brands, have low
levels of trust in
news overall, and
especially news in
search and
social…
… that lead many
to see publishers
as responsible
for main forms of
what they see as
misinformation.

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Misinformation: public perceptions and practical responses

  • 1. Rasmus Kleis Nielsen Misinfocon London, hosted by the Mozilla Foundation and Hacks/Hackers October 24, 2018 @risj_oxford MISINFORMATION — Public perceptions and practical responses
  • 2. 2 Q10a_new2017_rc. Which of these was the MAIN way in which you came across news in the last week? Base: All/under 35s that used a gateway to news in the last week: All markets = 69246/19755. See Newman et al (2018) 2018 Reuters Institute Digital News Report. The rise of distributed discovery All markets
  • 3. Far from creating filter bubbles, distributed discovery often exposes people to more sources 3 Automated serendipity means that people who use search and social media (and news aggregators) tend to use more sources of news and greater diversity of sources than those that don’t The effect of incidental exposure to news on social media is particularly clear for the young and those least interested in news See e.g. Fletcher and Nielsen (2018) “Are people incidentally exposed to news on social media? A comparative analysis,” New Media & Society 20 (7): 2450-2468
  • 4. 4 “IT’S THEIR JOB … TO REPORT THE FACTS” Q2. You recently viewed a story with the headline X. On which of the following news websites did you read this story? If you read it on more than one, please select all that apply. Showing share of correct brand attributions. Base: Direct 1,098/ Search 1,022/ Social 1,008 (Facebook 795, Twitter 194) 2X difference But brand attribution is a problem … Fewer than half can remember the news brand that produced a story when coming from social media or search See e.g. Kalogeropoulos et al (2018) “News brand attribution in distributed environments: Do people know where they get their news?,” New Media & Society
  • 5. 5 ALL 37 MARKETS - % THAT TRUST EACH MOST OF THE TIME Uncertainty in distributed environments, information unchecked, hard to distinguish news from rumor... Mostly this about trust in mainstream media and in the sources that people use Trust news I use 44% Trust news overall 51% Trust news in search 34% Trust news in social 23% See Newman et al (2018) 2018 Reuters Institute Digital News Report. … as is trust
  • 6. 85% 71% 69% 66% 66% 66% 65% 64% 63% 63% 62% 61% 60% 60% 60% 60% 58% 57% 55% 53% 51% 50% 50% 49% 49% 48% 47% 46% 44% 43% 42% 41% 38% 37% 36% 36% 30% 54% 0% 20% 40% 60% 80% 6 Q_FAKE_NEWS_1. Please indicate your level of agreement with the following statement. “Thinking about online news, I am concerned about what is real and what is fake on the internet.” Base: Total sample in each market Brazil Issue in the elections Spain Catalan independence a flashpoint Germany Low level concern post election USA Popularised by Trump and the media itself See Newman et al (2018) 2018 Reuters Institute Digital News Report. Varied concern over whether online news is real or fake
  • 7. See Nielsen and Graves (2017) “’News you don’t believe’: Audience Perspectives on Fake News”. Audience perspectives on “fake news”
  • 8. 8 What type of ‘f*ke news’ do people say they are EXPOSED to? ALL MARKETS see poor journalism, mistakes and clickbait every week 42% complain about spin and agenda- filled news 39% say they have been exposed to completely made up news 26% Only See Newman et al (2018) 2018 Reuters Institute Digital News Report. Audience definitions of problem are much wider
  • 9. 9 See Newman et al (2018) 2018 Reuters Institute Digital News Report. Concern versus exposure to types of misinformation etc Q_FAKE_NEWS_2. To what extent, if at all, are you concerned about the following and Q_FAKE_NEWS_3. In the LAST WEEK which of the following have you personally come across? Please select all that apply. Base: All markets 2018 – USA: 2401; UK: 2117; Germany: 2038; France: 2006; Italy: 2040; Spain: 2023; Portugal: 2008; Ireland: 2007; Norway: 2027; Sweden: 2016; Finland: 2012; Denmark: 2025; Belgium: 2006; Netherlands: 2010; Switzerland: 2120; Austria: 2010; Hungary: 2005; Slovakia: 2006; Czech Republic: 2020; Poland: 2005; Romania: 2048; Bulgaria: 2021; Croatia: 2010; Greece: 2014; Turkey:2019; Japan: 2033; Korea: 2010; Taiwan: 1008; Hong Kong: 2016; Malaysia: 2013; Singapore: 2018; Australia: 2026; Canada: 2022; Brazil: 2007; Argentina: 2012; Chile: 2008; Mexico: 2007
  • 10. 10 3. GOVERNMENT 61% 1. PUBLISHERS 75% 2. PLATFORMS 71% 41%60% “It’s free speech right? (F, 20-29, USA) “content is now removed within a few hours.” (M, 30–45, Germany) See Newman et al (2018) 2018 Reuters Institute Digital News Report. Who bears the biggest responsibility to fix the problems? Q14_2018a_combined2. News literacy scale. Q_FAKE_NEWS_4_2_1-3. Please indicate your agreement with the following statements. Technology companies/media companies/the government should do more to make it easier to separate what is real and fake on the internet. Base: All with very low/low/high/very high news literacy: Selected markets = 11149/11898/8069/3790.
  • 11. Key points The move to distributed discovery is demonstrably expanding people’s news diets… … and in many countries we see high levels of concern over what is real and what is fake in the news… … concerns that are fanned by politicized use of the term “f*ke news” and wide attention to it and draw on deep- seated and much broader concerns… … but people often don’t recognize brands, have low levels of trust in news overall, and especially news in search and social… … that lead many to see publishers as responsible for main forms of what they see as misinformation.