In this document, I have summarised all lectures and included the literature in blue text. For the lecture on Conspiracy Theories the literature is done in a different format, because the guest lecturer didn't talk about the articles
Data and (mis)information
Lecture 1 – Introduction
- Developing a critical attitude towards data and information in online professional messages
- Why do people keep believing in misinformation?
- We want to stick to the truth and to the facts (= a thing that is known to be true)
Facts?
- Facts vs beliefs (what you believe to be a fact/to be true)
- Despite evidence
- Objective truth (verified by abundant evidence, universally accepted, backed up by many
people) vs subjective truth (beliefs backed up by some evidence, e.g. theories and hypotheses,
often competing with other beliefs, conflicting theories)
Examples
- The world is not flat → objective
- The climate changes due to human interference → objective truth
- 2 + 2 = 4 → objective
- Everyone dies at some point → objective
- More than two hours of gaming is bad for your health → subjective!
Feelings over facts?
- Factual truth vs emotional truth (the information “feels true”)
- When in presidency elections 2016 in US
Post-truth
- We are not convinced by facts
= Relating to or denoting circumstances in which objective facts are less influential in shaping
public opinion than appeals to emotion and personal belief
- Often feelings opposite to actual facts
- Need to know what is really going on
- “If you can’t agree with each other what is true, then anyone and everyone can do whatever
they want with the ‘truth’”
- Need to find common ground about what is true
- To deal with information that comes in
- A lie can travel halfway around the world while the truth is putting on its shoes
- Social media
- Viral and cannot be debunked anymore
- Because of hyperconnectivity, false facts can travel easily
1
,Digital wildfires
- Massive digital misleading info
- Cannot retract it, damage is done
- Impact amplified by hyperconnectivity
- Rapid viral spread of info with potential serious consequences
- Former Conservative Party treasurer mistakenly linked to child abuse allegations by BBC
(because of Twitter)
- He filed lawsuit against everyone who spread the information and asked them to
donate to a charity
- Tweets of false shootouts cause panic in Mexico City
- There was nothing going on
Lies spread faster than the truth
- Data set of rumor cascaded on Twitter from 2006 to 2017
- About 12.600 rumors spread by about 3 million people
- False news reached more people than the truth
- The top 1% of false news cascades diffused to between 1000 and 100.000 people
- The truth rarely diffused to more than 1000 people
- Falsehood also diffused faster than the truth
Artificial amplification
- Fake followers and likes
- False trending: artificial implication of online traffic to create the illusion of popularity and
support
Disinformation vs misinformation
- Misleading information is umbrella term
- Disinformation = senders are deliberately trying to deceive/mislead
- I know that what I’m going to tell you is false
- Purpose of telling it anyway
- Misinformation = resulting from honest mistakes
- Interpreting academic research wrongly and report about it in journals
- No intention to deceive
Misinformation
- Many are misreporting hurricane Maria’s death toll
- Complicated and hard to get a clear overview of what was happening
- Three glasses of milk a day can lead to early death
- Linking milk to bone fractures and subtly mentioning death cases
- Exaggerated
- Clickbait title
2
,Disinformation
- Parenting experts warn screen time greatly increases risk of child becoming an influencer
- Satire: The Onion (vergelijkbaar met De Speld)
- Harmless
- Conspiracy theories
- Global warming is a socialist scam
- Corona & 5G
- Conspiracy theorists sometimes actually believe that it is true
- It starts with someone putting wrong information out there and then someone else
believes it to be true and spreads it (disinformation → misinformation)
Topics
- A week per topic
Fact-checking
- Social media messages by (self-acclaimed) experts on either COVID-19 or climate change
- How to fact check?
- Text, photos and videos
- People say there are experts but are not
- Same subtopic in group and everyone looks at different experts
1. Framing
= Select some aspects of a perceived reality and make them more salient in a communicating
text
- Put a frame around message
- Equivalence framing: most traditional type of framing
- Positive: running makes you happier (positive effect of doing X)
- Negative: not running makes you unhappier (negative effect of not doing X)
→ Semantically same information but it is perceived different
2. Misleading data
- Data often seen as “little nuggets of truth”
- But data can also be biased
- What can (and does) go wrong during the various stages of scientific research?
- How can researchers be biased?
- Researchers make mistakes sometimes too
- How questions in survey are being asked
3. (misleading) Visualizations and deepfakes
- Part 1: visualizations attraction our attention and help us understand complex patterns in
data
- Can’t see which part of graph is bigger because of perception and 3D
3
, - Part 2: deepfakes are videos of a person in which their face, voice, body has been digitally
altered so that they appear to be someone else, typically used to spread disinformation. They
are audiovisual forgeries
- Seems very believable
4. Conspiracy theories: guest lecture by PhD student
- Why do we believe in conspiracy theories?
- What are they exactly?
- How to tackle them?
5. Dealing with misleading information
- Why do we keep relying on misleading information?
- How to reduce the impact of misleading information?
Practicalities
- Can you choose which seminars to go to/give your preference? 10:45-12:30 on Wednesday
overlap with Persuasion & (dis)agreement
- Link where you can indicate if you have other lectures during seminar times of this
course
Grading
→ Need to score at least a 6 on all four parts
Assemble portfolio (individual: 30%)
- Write blogpost reflecting on the content of the lectures (20%)
- About one of the five topics of the course
- Essay style, popular scientific text
- To argue for a particular point that reflects your own insights, based on
references to literature and lecture and (at least) one real life example of a
problematic situation
- Visualizations example: politician tweet
- 700-1000 words
- Act like a real blogger
- Introduction that attracts interest
- Have a final statement to end the blogpost with!
- Starting point for discussion in presentation
- Present blogpost during the course (10%)
- 10 minutes blogpost presentation and 5 minutes for discussion
→ Within portfolio, the two parts can be compensated
Contribute to discussions (pass or fail)
- Respond to the blogposts of three fellow students
- Do this after week of your own blogpost
- React to three other people’s post on the same topic as you did
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