Summary Data & (mis)information – Tilburg University
- Master Information & communication sciences 2020-2021-
Content
Lecture 1. Introduction .......................................................................................................................2
Framing the origins of COVID-19 – Bolsen et al. 2020 ..........................................................................3
The state of framing research: a call for new directions – Scheufele, 2014 ..........................................4
Lecture 2. Framing ..............................................................................................................................5
Ch 1. The sin of bias – Chambers (2017) ..............................................................................................7
Degrees of freedom in planning, running, analyzing & reporting – Wicherts et al. 2016 ......................9
Lecture 3. Misleading data ................................................................................................................ 12
Lecture 4. Misleading data visualizations .......................................................................................... 15
Ch 5. Graphic lies, misleading visuals – Cairo ..................................................................................... 18
Lecture 5. Filter bubbles & conspiracy theories online ...................................................................... 19
Who controls public sphere in era of algorithms? – Caplan & Boyd, 2016 ......................................... 22
Conspiracy theories as stigmatized knowledge – Barkun, 2016 ......................................................... 23
Lecture 6. Dealing with misinformation............................................................................................. 24
Fake news, phishing & fraud – Lee (2018) ......................................................................................... 29
Beyond misinformation – Lewandowsky et al. (2017)........................................................................ 30
1
,Lecture 1. Introduction
Facts
- facts vs beliefs (= what you believe to be a fact)
objective truth= truth verified by abundant evidence, universally accepted
subjective truth= beliefs backed up by some evidence (e.g. theories, hypotheses) often competing
with other beliefs (= alternative facts)
examples: 2+2=4 or “the world is flat”
emotional truth= information “feels” true
Post-truth
= relating to or denoting circumstances in which objective facts are less influential in shaping public
opinion that appeals to emotion & personal beliefs
A false fact’s journey
- no gatekeepers, everything can be shared
hyperconnectivity: false info can be spread very easily
-lies spread faster than the truth
Digital wildfires
- massive digital misleading info
- impact amplified by hyperconnectivity
- rapid viral spread of information with potential serious consequences
Artificial amplification
= fake followers & likes
False trending: artificial amplification of online traffic to create illusion of popularity & support
Lies spread faster than the truth (Vosoughi, Ray & Aral, 2018)
- false news reached more people than the truth
> top 1% false news diffused to 1000-10 000 users
> truth rarely diffused to 1000+ people
- falsehood also diffused faster than the truth
Misleading information
1. Disinformation: resulting from deliberate intention to deceive (e.g. conspiracy theorists)
2. Misinformation: resulting from honest mistakes
2
, Framing the origins of COVID-19 – Bolsen et al. 2020
Origins of COVID-19
1. Zoonotic: virus transmitted “naturally” from bats to humans at Wuhan food market
2. Human-engineered: leaked deliberately or accidentally from research laboratory
> biological weapon = conspiracy frame
conspiracy theory: effort to explain some event/practice by reference to the machinations of
powerful people, who attempt to conceal their role
Emphasis framing & “original” beliefs
emphasis framing: when exposure to a framed message causes people to prioritize the emphasized
consideration(s) when forming a belief (Druckman, 2004)
e.g. messages that accentuate public/personal health benefits of COVID-19 prevention
> increased intentions to engage in these actions
- exposure to one-sided frames shape opinion formation
Scientific misinformation
= a claim that is unsupported/contradicted by scientific community’s best available information
> can undermine influence of science on public & policy makers
> can lead to collective decisions that are not in best interest of society
Blame attributions
blame: attribution of responsibility for an action/event > attitudes & behaviour
> when events are seen as intentional & outcomes are foreseeable
> contains 2 ideas: cause & responsibility (are not the same)
- attribution of blame strengthens response > more for narrowly attributed than diffused blame
- gain/loss & episodic/thematic frame influenced perceived responsibility
conspiracy effect: info stating it’s a hoax decrease individual’s willingness to engage in prosocial
actions
Results
- competitive framing didn’t differ from control group
- origin beliefs have downstream impacts on opinions about appropriate policy responses from
governments to address this & future pandemics + penalize
- more likely to believe conspiracy theories about events with serious consequences & in times of
crisis
- exposure to conspiracy theory > less importance prosocial behaviour
- frames shape perceptions of who is responsible & influence personal behaviours
3
- Master Information & communication sciences 2020-2021-
Content
Lecture 1. Introduction .......................................................................................................................2
Framing the origins of COVID-19 – Bolsen et al. 2020 ..........................................................................3
The state of framing research: a call for new directions – Scheufele, 2014 ..........................................4
Lecture 2. Framing ..............................................................................................................................5
Ch 1. The sin of bias – Chambers (2017) ..............................................................................................7
Degrees of freedom in planning, running, analyzing & reporting – Wicherts et al. 2016 ......................9
Lecture 3. Misleading data ................................................................................................................ 12
Lecture 4. Misleading data visualizations .......................................................................................... 15
Ch 5. Graphic lies, misleading visuals – Cairo ..................................................................................... 18
Lecture 5. Filter bubbles & conspiracy theories online ...................................................................... 19
Who controls public sphere in era of algorithms? – Caplan & Boyd, 2016 ......................................... 22
Conspiracy theories as stigmatized knowledge – Barkun, 2016 ......................................................... 23
Lecture 6. Dealing with misinformation............................................................................................. 24
Fake news, phishing & fraud – Lee (2018) ......................................................................................... 29
Beyond misinformation – Lewandowsky et al. (2017)........................................................................ 30
1
,Lecture 1. Introduction
Facts
- facts vs beliefs (= what you believe to be a fact)
objective truth= truth verified by abundant evidence, universally accepted
subjective truth= beliefs backed up by some evidence (e.g. theories, hypotheses) often competing
with other beliefs (= alternative facts)
examples: 2+2=4 or “the world is flat”
emotional truth= information “feels” true
Post-truth
= relating to or denoting circumstances in which objective facts are less influential in shaping public
opinion that appeals to emotion & personal beliefs
A false fact’s journey
- no gatekeepers, everything can be shared
hyperconnectivity: false info can be spread very easily
-lies spread faster than the truth
Digital wildfires
- massive digital misleading info
- impact amplified by hyperconnectivity
- rapid viral spread of information with potential serious consequences
Artificial amplification
= fake followers & likes
False trending: artificial amplification of online traffic to create illusion of popularity & support
Lies spread faster than the truth (Vosoughi, Ray & Aral, 2018)
- false news reached more people than the truth
> top 1% false news diffused to 1000-10 000 users
> truth rarely diffused to 1000+ people
- falsehood also diffused faster than the truth
Misleading information
1. Disinformation: resulting from deliberate intention to deceive (e.g. conspiracy theorists)
2. Misinformation: resulting from honest mistakes
2
, Framing the origins of COVID-19 – Bolsen et al. 2020
Origins of COVID-19
1. Zoonotic: virus transmitted “naturally” from bats to humans at Wuhan food market
2. Human-engineered: leaked deliberately or accidentally from research laboratory
> biological weapon = conspiracy frame
conspiracy theory: effort to explain some event/practice by reference to the machinations of
powerful people, who attempt to conceal their role
Emphasis framing & “original” beliefs
emphasis framing: when exposure to a framed message causes people to prioritize the emphasized
consideration(s) when forming a belief (Druckman, 2004)
e.g. messages that accentuate public/personal health benefits of COVID-19 prevention
> increased intentions to engage in these actions
- exposure to one-sided frames shape opinion formation
Scientific misinformation
= a claim that is unsupported/contradicted by scientific community’s best available information
> can undermine influence of science on public & policy makers
> can lead to collective decisions that are not in best interest of society
Blame attributions
blame: attribution of responsibility for an action/event > attitudes & behaviour
> when events are seen as intentional & outcomes are foreseeable
> contains 2 ideas: cause & responsibility (are not the same)
- attribution of blame strengthens response > more for narrowly attributed than diffused blame
- gain/loss & episodic/thematic frame influenced perceived responsibility
conspiracy effect: info stating it’s a hoax decrease individual’s willingness to engage in prosocial
actions
Results
- competitive framing didn’t differ from control group
- origin beliefs have downstream impacts on opinions about appropriate policy responses from
governments to address this & future pandemics + penalize
- more likely to believe conspiracy theories about events with serious consequences & in times of
crisis
- exposure to conspiracy theory > less importance prosocial behaviour
- frames shape perceptions of who is responsible & influence personal behaviours
3
