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Biased Media Hendy Irawan -23214344 Advanced Matematics EL5000 / Game Theory

Biased Media - Game Theory (EL5000) Course Project

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Page 1: Biased Media - Game Theory (EL5000) Course Project

Biased MediaHendy Irawan - 23214344Advanced Matematics EL5000 / Game Theory

Page 2: Biased Media - Game Theory (EL5000) Course Project

Is Unbiased Media Better?

Page 3: Biased Media - Game Theory (EL5000) Course Project

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)

Page 4: Biased Media - Game Theory (EL5000) Course Project

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

Page 5: Biased Media - Game Theory (EL5000) Course Project

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%

Page 6: Biased Media - Game Theory (EL5000) Course Project

Payoff Matrix: Moves 1 & 2

Page 7: Biased Media - Game Theory (EL5000) Course Project

Payoff Matrix: Moves 3 & 4

Page 8: Biased Media - Game Theory (EL5000) Course Project

Game Tree

Advertiser moves first

Page 9: Biased Media - Game Theory (EL5000) Course Project

Game Tree: Move A(Advertiser Advertises)

Page 10: Biased Media - Game Theory (EL5000) Course Project

Game Tree: Move F(Advertiser Forfeits)

Page 11: Biased Media - Game Theory (EL5000) Course Project

Maximins

ADVERTISER MEDIA

› Strategy _O_P and _P_Omaximizes minimum payoff

› Maximized minimum payoff is 0

› Strategy A_A_ maximizes minimum payoff

› Maximized minimum payoff is 8 (ANAN)

Page 12: Biased Media - Game Theory (EL5000) Course Project

Dominations

ADVERTISER MEDIA

› Moves A_A_ strongly dominates other strategies

› Moves _O_P and _P_Odominates other strategies

Page 13: Biased Media - Game Theory (EL5000) Course Project

Pure Nash Equilibrium

› Single Pure Nash Equilibrium is moves AOAP (120, 1920)

Page 14: Biased Media - Game Theory (EL5000) Course Project

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

Page 15: Biased Media - Game Theory (EL5000) Course Project

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