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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 SystemsInformation Cascades Prof. Dr. Steffen Staab
SocialInfluence • People connectedby a networkinfluenceeachother • Opinions • Buyingbehavior • Political positions • Activitiespursued • Technologies used • ...
Herding / Information Cascade • Choosingbetweentworestaurants • Onefull • Oneempty • Rational inferencesfrom limited information
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
Assumptions • Decisiontobemade • People makedecisionssequentiallyandobserveotherswhohavemadethe same decisionbefore • Eachpersonhassome private information/preferenceinfluencingthedecision • A personcannotobservewhatothersknow, but onlywhatothersdo
Simple Herding Experiment (Anderson&Holt) • Urnwithredandbluemarbles • Studentsaretold: • Eithertheurnhastworedmarblesandoneblueone • Ortheurnhastwobluemarblesandoneredone • Studentsareinstructed: • Tocomeone after theotherandrandomlydraw a marble • Tolookatthemarble, but not toshowthemarbletotheothers • Tomake a guessaboutthenumberofredmarbles • Toannouncetheirguess • Studentsaretoldthatsuccessfulguessersarerewarded
Tocomeone after theotherandrandomlydraw a marble • Tolookatthemarble, but not toshowthemarbletotheothers • Toguessaboutthenumberofredmarbles • Toannouncetheirguess • Decisiontobemade • People decidesequentiallyandobserveotherswhohavemadethe same decisionbefore • Eachpersonhassome private information • A personcannotobservewhatothersknow, but onlywhatothersdo
Effect 1. BLUE RED RED symmetricto BLUE, Let‘sonlyconsider BLUE
Effect 1. BLUE RED 2. BLUE 3. BLUE 3. BLUE
Effect 1. BLUE RED 2. BLUE 3. BLUE 3. BLUE 4. BLUE 4th studentknowsthat 3rd informationisuseless, thus he onlytruststhefirsttwopiecesofinformation...
Effect 1. BLUE RED 2. BLUE 3. BLUE 3. BLUE 4. BLUE 5th studentknowsthat 3rd and 4th informationisuseless, thus he onlytruststhefirsttwopiecesofinformation... 5. BLUE
Effect 1. BLUE RED 2. RED 3. BLUE 3. RED The firsttwoannouncementscreate a tie, hencethe 3rd studentreliesonly on hisownmarbletomake a guess
Effect 1. BLUE RED 2. RED 3. BLUE 3. RED The firsttwoannouncementscreate a tie, hencethe 4th is in a likewisesituationasthe 2nd student
Effect 1. BLUE RED 2. BLUE 2. RED 3. BLUE 3. BLUE 3. BLUE 3. RED 4. BLUE Information Cascade 5. BLUE
Conclusion on informationcascades • Structuralconditionsleadtoinformationcascades • Information cascadesleadtononoptimaloutcomes • Wrongguessingmorelikelyto happen withchance >1/9 evengivenvery large numberofstudents, • while a large sample in generalachievesextremelyhigh accuracycloseto 100% • Cascadecanbeoverturnedbytwonewpiecesofinformation
Klaas Dellschaft • Influenceoftaggers on othertaggers