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Biased Media
Hendy Irawan - 23214344
Advanced Matematics EL5000 / Game Theory
Is Unbiased Media Better?
Game, Players & Strategies
› Sequential Perfect-Information Randomless Game
› 2 players
– Advertiser
› Advertise: Get traf...
Outcomes for Advertiser
› Based on number of
Retweets of Media’s topic
› Statistics from
@dakwatuna
› If Advertiser choose...
Outcomes for Media
› Based on Click-Through Rate which determines
payout to the media company
– Statistics from: http://ww...
Payoff Matrix: Moves 1 & 2
Payoff Matrix: Moves 3 & 4
Game Tree
Advertiser moves first
Game Tree: Move A
(Advertiser Advertises)
Game Tree: Move F
(Advertiser Forfeits)
Maximins
ADVERTISER MEDIA
› Strategy _O_P and _P_O
maximizes minimum payoff
› Maximized minimum payoff is 0
› Strategy A_A...
Dominations
ADVERTISER MEDIA
› Moves A_A_ strongly
dominates other strategies
› Moves _O_P and _P_O
dominates other strate...
Pure Nash Equilibrium
› Single Pure Nash Equilibrium is moves AOAP (120, 1920)
Conclusion
› Media bias is a factor in success of advertiser’s click-
through rates
› Since advertiser cannot directly con...
References
› Viola Chen. Is Media Bias Bad? UCLA. 2007.
http://chenv.bol.ucla.edu/ChenV_Bias.pdf
› Gentzkow, Matthew, and ...
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Biased Media - Game Theory (EL5000) Course Project

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Is Unbiased Media Better?

Sequential Randomless Game
2 players
Advertiser
Advertise: Get traffic from media’s tweet
Forfeit: No traffic
Media
Pro: Favorable news of supported agenda
Neutral: Balanced news reporting
Contra: Criticizing opposing views
Overhyped: Anecdotes and variety of popular news
Game Tree Simulated for 4 moves (64 leaves)

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Biased Media - Game Theory (EL5000) Course Project

  1. 1. Biased Media Hendy Irawan - 23214344 Advanced Matematics EL5000 / Game Theory
  2. 2. Is Unbiased Media Better?
  3. 3. Game, Players & Strategies › Sequential Perfect-Information Randomless Game › 2 players – Advertiser › Advertise: Get traffic from media’s tweet › Forfeit: No traffic – Media › Pro: Favorable news of supported agenda › Neutral: Balanced news reporting › Contra: Criticizing opposing views › Overhyped: Anecdotes and variety of popular news › Game Tree Simulated for 4 moves (64 leaves)
  4. 4. Outcomes for Advertiser › Based on number of Retweets of Media’s topic › Statistics from @dakwatuna › If Advertiser chooses Forfeit then: 0 RTs › If chooses Advertise, based on Media’s topic: – Pro: 10 RTs – Neutral: 4 RTs – Contra: 70 RTs – Overhyped: 110 RTs
  5. 5. Outcomes for Media › Based on Click-Through Rate which determines payout to the media company – Statistics from: http://www.quora.com/What-is- the-average-CTR-on-Facebook-Ads › Payoff formula: CTR × number of Retweets › If 0 “Advertise” moves: 0% › If 1 “Advertise” move: – Pro: 0.02% – Neutral: 0.03% – Contra: 0.08% – Overhyped: 0.06% › If 2 “Advertise” moves, pick best CTR from: (viral effect) – Pro: 0.16% – Neutral: 0.11% – Contra: 0.09% – Overhyped: 0.07%
  6. 6. Payoff Matrix: Moves 1 & 2
  7. 7. Payoff Matrix: Moves 3 & 4
  8. 8. Game Tree Advertiser moves first
  9. 9. Game Tree: Move A (Advertiser Advertises)
  10. 10. Game Tree: Move F (Advertiser Forfeits)
  11. 11. Maximins ADVERTISER MEDIA › Strategy _O_P and _P_O maximizes minimum payoff › Maximized minimum payoff is 0 › Strategy A_A_ maximizes minimum payoff › Maximized minimum payoff is 8 (ANAN)
  12. 12. Dominations ADVERTISER MEDIA › Moves A_A_ strongly dominates other strategies › Moves _O_P and _P_O dominates other strategies
  13. 13. Pure Nash Equilibrium › Single Pure Nash Equilibrium is moves AOAP (120, 1920)
  14. 14. Conclusion › Media bias is a factor in success of advertiser’s click- through rates › Since advertiser cannot directly control media, the best move is to advertise – If ad performance is not satisfactory, advertise can switch to different media outlet, but still advertise › When the game is played sequentially, the viral effect of news article affects the total click-through rates – It’s preferable to advertise multiple times in a single media outlet than switching media outlets rapidly
  15. 15. References › Viola Chen. Is Media Bias Bad? UCLA. 2007. http://chenv.bol.ucla.edu/ChenV_Bias.pdf › Gentzkow, Matthew, and Jesse Shapiro. Media bias and reputation. No. w11664. National Bureau of Economic Research, 2005. › http://www.quora.com/What-is-the-average-CTR-on- Facebook-Ads

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