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Steffen Staab Opinion Formation and Spreading 1Institute for Web Science and Technologies · University of Koblenz-Landau, Germany
Web and Internet Science Group · ECS · University of Southampton, UK &
Opinion Formation and SpreadingSchafft Digitalisierung eine eigene Dynamik in der
Meinungsbildung?
Steffen Staab
@ststaab
http://west.uni-koblenz.de
http://wais.soton.ac.uk
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Steffen Staab Opinion Formation and Spreading 2
Individual Opinion Formation vs Opinion Spreading
(Staab, 2013)
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Individual online behavior and personality
(Buckels et al., Trolls just want to have fun, Personality and Individual Differences 2014)
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Herbert Simon: Satisficing = satisfying + sufficient
• Classification of information to be satisficing,
not to achieve optimal information organization
Individual Satisficing Information Processing
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• Experiment A: Classify web pages by bookmarks– Recommender A1: suggest classification by others
– Recommender A2: suggest earlier classification by yourself
• Experiment B: Construct optimal information structure
• Result:– A2 hides majority opinion
A2 yields results closer to optimal information structure
(Dellschaft & Staab, 2008, 2012)
Individual Satisficing Information Processing
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Herding Behaviour
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What makes something famous?
• Gangnam style?
• Mona Lisa?
• Trump tweets?
• Double rainbow?
Communication Internal Events vs.
Communication External Events
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Network structure – who follows whom?
From (Weng et al, Scientific Reports 2012)
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Majority Illusion
(Lerman et al., 2015)
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(Salganik, Dodds, Watts, Science 2006)
• Experiment
– 48 unknown songs
– Nine “worlds“ with
different users
– Songs start being liked
differently in each world
– A song that starts being
liked is liked even more
– Virtuous reinforcement
Unpredictability
Market share fluctuates heavily between
different worlds
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• Meme spreading
Limited Attention & Randomness
(Weng et al, Scientific Reports 2012)
(i) Network structure, (ii) limited screen & memory,
(iii) randomness explain macro observations
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Recipes for Spreading Misinformation
Quoting (Metaxas et al, WebSci 2010)
Comparison by (Metaxas et al, WebSci 2017)
Recipes handle unpredictability
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Herding Behaviour - Dislikes
1-2 €
per
1000
views
(CPM)
plus
extras
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Clickbait Economics
(Silverman & Alexander, Buzzfeed, November 2016)
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Media Economics
• Offline media publishes daily or twice daily
• Online media must publish every hour
– The message becomes the news
• Trump generates news by producing messages
Social Media
• (some) individuals become publishers
– Different participant types tend to have different personality profiles
Temporality
Faster republishing cycles beget
increasing dynamics beget
increasing competition for attention beget
increasing unpredictability
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Good or bad? (my subjective judgement)
Good
• Self-empowerment
– Political movements,
e.g. Campact
– Decentralized culture
Bad
• Group manipulation
– By economic players
(clickbait)
– By political players
(Breitbart)
– By consultancies
(Cambridge analytica)
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Wo aber Gefahr ist, wächst
das Rettende auch. Hölderlin
Where is danger, grows
salvation, too.
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• Confirmation bias
– Very hard to turn one‘s opinion
– Easier:
• Enforce belief
• Spread doubt
– Online viral marketing often does not work
• Everything is different the second time
– Election campaigns don‘t repeat themselves
– Facebook now is different than 5 years ago
– New online media on the rise
Individual Resilience
(Watts: Everything Is Obvious: *Once You Know the Answer)
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>100 Fact checking networks: IFCN
• Fact checking website: snopes.com
• Deleting shared content based on comments
https://fullfact.org/blog/2017/jun/general-election-2017-factchecked/
Societal Resilience: Fact Checking
(Friggeri et al,
ICWSM-2014)
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Technical Resilience: New tools
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• Who defines what resilience is beneficial?
• How to further resilience?
• Need for joint research of
– Social sciences, humanities, computer science, etc.
Conclusion: Individual, Network & Resilience
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Questions?
Comments?