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Article . 2020
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Game Theoretic Analysis of Clickbait or Fake News and Real News

Authors: Hausken, Kjell;

Game Theoretic Analysis of Clickbait or Fake News and Real News

Abstract

A decision and game theoretic model is developed for how one and two news organisations strike balances between producing clickbait or fake news, and real news. Each news organisation seeks to attract gullible consumers who consume more clickbait or fake news than real news, and non-gullible consumers who conscientiously consume only real news. Increasing a news organisation budget results in obtaining both more clickbait or fake news, and more real news. More clickbait or fake news is produced if the news organisation’s unit cost of effort to produce real news, the production efficiency for clickbait or fake news, and the fraction of consumers consuming clickbait or fake news, increase. In contrast, less clickbait or fake news is produced if a news organisation’s unit cost of effort to produce clickbait or fake news, and the production efficiency for real news, increase, and the gullible consumers consume real news with a higher frequency. Lower unit effort costs and higher budget and production efficiencies cause higher utility for a news organisation and lower utility for the competing news or- ganisation. Higher weight assigned to the contest over clickbait or fake news induces both news organ- isations to exert higher effort to produce clickbait or fake news. When the gullible consumers of a news organisation consume a relatively large amount of real news in comparison to the consumers of another news organisation, then the first news organisation exerts higher effort to produce real news and obtains higher utility than the other news organisation.

Country
Norway
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Keywords

VDP::Teknologi: 500

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green
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