CyberAgent,Inc.

新参者は如何にして新たなグループになじむのか？ソーシャルゲームにおける分析事例

株式会社 サイバーエージェント技術本部 秋葉原ラボ 高野雅典,和田計也,福田一郎

15/11/16 1

WEBDBForum2015

CyberAgent,Inc. 2

CyberAgent,Inc.

技術本部 秋葉原ラボ

ミッション: 大規模データ処理、機械学習、検索、統計解析などの技術を 用いた（主に）自社サービスの発展

対象: スマフォゲーム、音楽/動画関連サービス、SNS、広告など全社横断

315/11/16

•  大規模データを集約し活かすための組織•  2011/4に開設、現在27名が所属

1.  PDCAサイクルのためのKPIの設計・集計・可視化

2.  ユーザ体験向上のための推薦・検索・分類などの機能提供

3.  サービス健全化のためのスパム検知・フィルタリング

4.  課題発見・解決のための統計解析

CyberAgent,Inc.

サイバーエージェント 技術本部 秋葉原ラボ

415/11/16

国内口頭発表は開設当初から継続的に実施

査読付き論文や書籍・学会誌への執筆・寄稿も増加中！！

•  対外発表も（全社的に）推奨されている

– 博士号所持者・在学者も増加傾向 ⤴–  秋葉原ラボの発表一覧:hEp://www.cyberagent.co.jp/techinfo/labo/research_list/

※2015/11現在

CyberAgent,Inc.

新参者は如何にして新たなグループになじむのか？ソーシャルゲームにおける分析事例

株式会社 サイバーエージェント技術本部 秋葉原ラボ 高野雅典,和田計也,福田一郎

15/11/16 5

WEBDBForum2015

本題

CyberAgent,Inc.

CooperaOveBehavior

Coopera(vebehaviorcostsactors,butbenefitsrecipients.Importantfactorsforhumansociety.BigQues(oninEvolu(on.

15/11/20 6

CyberAgent,Inc.

ParadoxofCooperaOon

MutualcooperaOonincreasesourbenefit.WhyisitthequesOon?

715/11/16

CooperaOngeachother

Thebothgetbenefits

CyberAgent,Inc.

ParadoxofCooperaOon

MutualcooperaOonincreasesourbenefit.WhyisitthequesOon?

815/11/20

Butifonedefects

Thedefectorgetshigherbenefitthananother(cooperator).

Defect

Cooperate

CyberAgent,Inc.

ParadoxofCooperaOon

MutualcooperaOonmakebenefitforall.Butone-sideddefecOonmakemorebenefitstodefectors.→Coopera(vepopula(onwillbecomedefec(vepopula(on

915/11/16

HighBenefit

LowBenefit

GoodrelaOonship,butunstable.

Stable,butbadrelaOonship

CyberAgent,Inc.

ParadoxofCooperaOon

However,wecooperateeachother

HumanshouldhavegoEencoopera(onmechanismsduringtheevoluOonary process

15/11/16 10

CyberAgent,Inc.

MechanismsofCooperaOon

•  KinSelecOon•  DirectReciprocity•  IndirectReciprocity•  SpaOalSelecOon•  MulO-levelSelecOon

ref.DavidGRand,etal.,HumancooperaOon.TrendsincogniOvesciences,Vol.17,No.8,pp.413-25,2013.

ThesemechanismsgenerateassortmentsbetweenfellowsandstrangerstokeepinteracOonbetweencooperators.•  i.e.,cooperaOonmechanismsexcludestrangersfromcooperaOvegroups.

1115/11/20

CyberAgent,Inc.

ProblemofCooperaOonMechanisms•  KinSelecOon•  DirectReciprocity•  IndirectReciprocity•  SpaOalSelecOon•  MulO-levelSelecOon

Thereciprocalmechanismsrequirecoopera(veinterac(oninfirst(memee(ng,becausereciprocalcooperatorscooperateotherswhohavecooperatedthemtoavoidtocooperatedefectors.•  i.e.,toincreasereciprocalrelaOonships,infirstOmemeeOng,they

shouldcooperate(notexclude)strangerstoconstructgoodrelaOonships.

Thereareinterac(onrisks,becausetheyareunfamiliareachother.

→Howdohumanstakeinstrangers?

1215/11/20

CyberAgent,Inc.

OurApproach

Weapproachedthisproblembasedondataanalysisofasocialnetworkgame.SocialNetworkGame(SNG):•  OnetypeoftheOnlineGames.•  Alotofplayers.•  Playersbelongtogroups(tensofplayers),theycooperateinthegroups,andcompetewithallothers.

1315/11/20

CyberAgent,Inc.

PreviousStudiesandOurApproach

1415/11/20

ParOalandBiasedDataHardtoUnderstand

CleanandDetailedDataEasytoUnderstand

MathemaOcalModelSimulaOon

ExperimentsinLab

✊ ✋

Data Analysis of SNGs ObservaOonStudy

SNGsismoreopen-endedthansimulaOonsandlabexperiments,andwecangetallplayers'behaviorlogs→Wemayexpecttofind newevidencesforhumansociality.

CyberAgent,Inc.

SocialNetworkGame

1515/11/16

URL:hEp://vcard.ameba.jpLang:JapaneseSince2012/10

CyberAgent,Inc.

TheGameRules

15/11/22 16

•  Playersaimtogetpointsandtorisearankingbasedonthepoints•  Playersbelongedtogroups

•  Thegroupsize:1〜50players•  Playerscooperateeachgroupmembertogetadvantagesin

thegame.•  Aplayercanmigratefromagrouptoanothergroupatany

Ome.•  Playerscommunicatebysendingsimplemessage(30Japanese

characters).

1:Smith（12040pt）

2:MarOn（11010pt）

3:Anderson（11005pt）

4:Ken（9015pt）

・・・

Migra(on

Ranking

Simplemessaging

Coopera(on

CyberAgent,Inc.

CooperaOveBehavior

•  WefocusonagamesituaOonlikeLeadergame–  IntheSNG,playersbehavevariously.– WecannottrackallcooperaOvebehavior.→Weregarded

Aplayer'sthiscooperaOonfrequencyintheSNG ≒theplayer'scooperaOveness

•  PayoffMatrixofthesituaOonlikeLeadergame

1715/11/20

Cooperate Defect

Cooperate -,- 1,3

Defect 3,1 0,0

Cooperatorget1point.Defectorget3point.

CyberAgent,Inc.

InteracOonofFirstTimeMeeOng

•  AplayercanmigratefromagrouptoanothergroupatanyOme.

•  Weobservedplayers'behaviorattheajermigraOon–  Didthenewcomersblendintoanewgroupmembers?–  Howdidthenewcomersinteractwiththethegroupmembers?

–  Howdidthenewcomersreacttothegroupmembers'behavior?

•  Inourpreviousworks,weshowed–  CooperatorsconstructedreciprocalrelaOonshipsintheirgroups.•  MasanoriTakano,KazuyaWada,andIchiroFukuda,"ReciprocalAltruism-basedCooperaOonina

SocialNetworkGame",NewGeneraOonCompuOng(inpress).hEp://arxiv.org/abs/1510.06197

1815/11/20

CyberAgent,Inc.

Results

15/11/16 19

WEBDBForum2015

CyberAgent,Inc.

TwoRegressionModels

•  AModelforCoopera(veBehavior– WerenewcomerscooperaOve?– Howwerenewcomersinfluencedbygroupmembers'behavior?

•  AModelfortheReceiptofCoopera(on– Werenewcomerscooperated?– Howwereplayersinfluencebynewcomers'behavior?

2015/11/22

CyberAgent,Inc.

NegaOveBinomialRegressionModel(GLM)

2115/11/22

AModelforCooperaOveBehavior•  Thismodelisintendedtoexplainthenumberofcoopera(onbyplayers'experiencesandaUributes

ResponseVariable:NumberofCooperaOon

ExplanatoryVariables:ExperiencesandAEributes

CyberAgent,Inc.

NegaOveBinomialRegressionModel(GLM)

2215/11/22

AModelforCooperaOveBehavior•  Didnewcomerscooperate?

ResponseVariable:NumberofCooperaOon

f:Flag(0or1)ofAjerMigraOon(NewcomerFlag)•  f=1:Newcomer•  f=0:ExisOngGroupMembers

Ifβ4>0thenitshowsthatnewcomersmoreojen cooperatethanexis(nggroupmembers.

CyberAgent,Inc.

NegaOveBinomialRegressionModel(GLM)

2315/11/16

AModelforCooperaOveBehavior•  Howdidnewcomersreactothersmessaging?

ResponseVariable:NumberofCooperaOon

C'(1-f):NumberofExis(ngGroupMember'sReceiptofCooperaOon

Ifβ6>β5>0thenitshowsnewcomersmoresuscepObletootherscooperaOonthanexis(nggroupmembers.

C'f:NumberofNewcomer'sReceiptofCooperaOon

CyberAgent,Inc.

NegaOveBinomialRegressionModel(GLM)

2415/11/16

AModelforCooperaOveBehavior•  Howdidnewcomersreactotherscoopera(on?

ResponseVariable:NumberofCooperaOon

C'(1-f):NumberofExis(ngGroupMember'sReceiptofMessaging

Ifβ8>β7>0thenitshowsnewcomersmoresuscepObletoothersmessagingthanexis(nggroupmembers.

C'f:NumberofNewcomer'sReceiptofMessaging

CyberAgent,Inc.

NegaOveBinomialRegressionModel(GLM)

2515/11/19

AModelforCooperaOveBehavior•  Theotherswereenteredascovariatestocontrolfortheotherfactors.

ResponseVariable:NumberofCooperaOon Theothersarecovariates

CyberAgent,Inc.

Results

•  β4>0–  Newcomersojencooperatedgroupmembers.

•  β5>β6>0,β7>β8>0–  NewcomerswerelesssuscepObletosocialinteracOon.

•  NewcomerstendedtocooperateotherswithoutotherscooperaOonandmessaging.

2615/11/24

β4β5β6β7β8

CyberAgent,Inc.

NegaOveBinomialRegressionModel(GLM)

2715/11/19

AModelfortheReceiptofCooperaOon•  Thismodelisintendedthenumberofthereceiptofcoopera(onbyotherbehaviorandaUributes

ResponseVariable:NumberoftheReceiptofCooperaOon

ExplanatoryVariables:OtherBehaviorsandAEributes

CyberAgent,Inc.

ResponseVariable:NumberoftheReceiptofCooperaOon

NegaOveBinomialRegressionModel(GLM)

2815/11/19

AModelfortheReceiptofCooperaOon•  Werenewcomerscooperated?

f:Flag(0or1)ofAjerMigraOon(NewcomerFlag)•  f=1:Newcomer•  f=0:ExisOngGroupMembers

Ifβ4>0thenitshowsthatnewcomersmoreojenreceivecooperaOonthanexis(nggroupmembers.

CyberAgent,Inc.

NegaOveBinomialRegressionModel(GLM)

2915/11/19

AModelfortheReceiptofCooperaOon•  Howdidnewcomersreactotherscoopera(on?

C(1-f):NumberofExis(ngGroupMember'sCooperaOon

Ifβ6>β5>0thenitshowsnewcomersweremoresensiOvetoothers'cooperaOonthanexis(nggroupmembers.

Cf:NumberofNewcomer'sCooperaOon

ResponseVariable:NumberoftheReceiptofCooperaOon

CyberAgent,Inc.

NegaOveBinomialRegressionModel(GLM)

3015/11/19

AModelfortheReceiptofCooperaOon•  Howdidnewcomersreactothersmessaging?

C'(1-f):NumberofExis(ngGroupMember'sMessaging

Ifβ8>β7>0then itshowsnewcomersweremoresensiOvetoothers'messagingthanexis(nggroupmembers.

C'f:NumberofNewcomer'sMessaging

ResponseVariable:NumberoftheReceiptofCooperaOon

CyberAgent,Inc.

NegaOveBinomialRegressionModel(GLM)

3115/11/19

AModelfortheReceiptofCooperaOon•  Theotherswereenteredascovariatestocontrolfortheotherfactors.

Theothersarecovariates

ResponseVariable:NumberoftheReceiptofCooperaOon

CyberAgent,Inc.

Results

•  β4>0–  Newcomerswereojencooperatedbygroupmembers.

•  β5>β6>0–  PlayerswerelesssensiOvetonewcomers'cooperaOonthan

exis(nggroupmembers'cooperaOon.

•  β8>β7>0•  PlayersweremoresensiOvetonewcomers'messagesthan

exis(nggroupmembers'messages.

3215/11/20

β4β5β6β7β8

CyberAgent,Inc.

Summary

•  TheSNGplayersresolvedinteracOonriskinfirstOmemeeOng.– Infirst(memee(ng,theyo\encooperatedeachother.

→TheymayhaveconstructedreciprocalrelaOonships.–  ref.ReciprocalrelaOonshipsinthisSNG.

•  MasanoriTakano,KazuyaWada,andIchiroFukuda,"ReciprocalAltruism-basedCooperaOoninaSocialNetworkGame",NewGeneraOonCompuOng(inpress).hEp://arxiv.org/abs/1510.06197

3315/11/20

CyberAgent,Inc.

Summary

•  Thedifferencebetweennewcomersandexis(nggroupmembersinmessaging– PlayersweremoresensiOvenewcomers'messagingthanexis(ngmembers'messaging.

– Themessagingmayhaveworkedassocialgrooming•  SocialgroomingistooltomakeandmaintainsocialrelaOonships.

•  ItincludescooperaOon,unproducOveconversaOons(gossips),andvarioussocialbehaviors.

Especiallyinfirst(memee(ng,socialgroomingwasimportanttoresolvetheriskinfirst(memee(ng.

3415/11/20