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

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?