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Network Theory and Dynamic Systems Information Cascades

Network Theory and Dynamic Systems Information Cascades. Prof. Dr. Steffen Staab. Social Influence. People connected by a network influence each other Opinions Buying behavior Political positions Activities pursued Technologies used . Herding / Information Cascade.

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Network Theory and Dynamic Systems Information Cascades

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  1. Network Theory and Dynamic SystemsInformation Cascades Prof. Dr. Steffen Staab

  2. SocialInfluence • People connectedby a networkinfluenceeachother • Opinions • Buyingbehavior • Political positions • Activitiespursued • Technologies used • ...

  3. Herding / Information Cascade • Choosingbetweentworestaurants • Onefull • Oneempty • Rational inferencesfrom limited information

  4. Cascading Effects Informationaleffect • Imitatingotherbehaviorsassumingtheyknowmore • Restaurant • Lookingupintosky • Reading a popularbook • Joining a fashion Direct-benefiteffects • Network benefits • Having a telephone • Using email • Joiningfacebook Mutual support: Joining a recommendedoperatingsystemmayimplyeasierexchangeoffileswithothers In conflict: Joining a popularrestaurantmayimplywaiting in a longline

  5. Assumptions • Decisiontobemade • People makedecisionssequentiallyandobserveotherswhohavemadethe same decisionbefore • Eachpersonhassome private information/preferenceinfluencingthedecision • A personcannotobservewhatothersknow, but onlywhatothersdo

  6. Simple Herding Experiment (Anderson&Holt) • Urnwithredandbluemarbles • Studentsaretold: • Eithertheurnhastworedmarblesandoneblueone • Ortheurnhastwobluemarblesandoneredone • Studentsareinstructed: • Tocomeone after theotherandrandomlydraw a marble • Tolookatthemarble, but not toshowthemarbletotheothers • Tomake a guessaboutthenumberofredmarbles • Toannouncetheirguess • Studentsaretoldthatsuccessfulguessersarerewarded

  7. Tocomeone after theotherandrandomlydraw a marble • Tolookatthemarble, but not toshowthemarbletotheothers • Toguessaboutthenumberofredmarbles • Toannouncetheirguess • Decisiontobemade • People decidesequentiallyandobserveotherswhohavemadethe same decisionbefore • Eachpersonhassome private information • A personcannotobservewhatothersknow, but onlywhatothersdo

  8. Effect 1. BLUE RED RED symmetricto BLUE, Let‘sonlyconsider BLUE

  9. Effect 1. BLUE RED 2. BLUE 3. BLUE 3. BLUE

  10. Effect 1. BLUE RED 2. BLUE 3. BLUE 3. BLUE 4. BLUE 4th studentknowsthat 3rd informationisuseless, thus he onlytruststhefirsttwopiecesofinformation...

  11. Effect 1. BLUE RED 2. BLUE 3. BLUE 3. BLUE 4. BLUE 5th studentknowsthat 3rd and 4th informationisuseless, thus he onlytruststhefirsttwopiecesofinformation... 5. BLUE

  12. Effect 1. BLUE RED 2. RED 3. BLUE 3. RED The firsttwoannouncementscreate a tie, hencethe 3rd studentreliesonly on hisownmarbletomake a guess

  13. Effect 1. BLUE RED 2. RED 3. BLUE 3. RED The firsttwoannouncementscreate a tie, hencethe 4th is in a likewisesituationasthe 2nd student

  14. Effect 1. BLUE RED 2. BLUE 2. RED 3. BLUE 3. BLUE 3. BLUE 3. RED 4. BLUE Information Cascade 5. BLUE

  15. Conclusion on informationcascades • Structuralconditionsleadtoinformationcascades • Information cascadesleadtononoptimaloutcomes • Wrongguessingmorelikelyto happen withchance >1/9 evengivenvery large numberofstudents, • while a large sample in generalachievesextremelyhigh accuracycloseto 100% • Cascadecanbeoverturnedbytwonewpiecesofinformation

  16. Klaas Dellschaft • Influenceoftaggers on othertaggers

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