The Design of Reliable Trust Management Systems for Electronic Trading Communities

Transcription

1 The Degn of Relale Trut Management Sytem for Electronc Tradng Communte Chryantho Dellaroca Sloan School of Management Maachuett Inttute of Technology Room E Camrdge, MA Atract: The ojectve of th paper to contrute to the development of a rgorou dcplne for degnng trut management mechanm n onlne communte. The mportance of uch a dcplne for management cence wthout queton: trut a precondton for the contnued extence of any market and organzaton n general. Furthermore, everal properte of onlne nteracton are challengng the accumulated wdom of our communte on how to produce trut and requre the development of new mechanm and ytem. The paper ntroduce a mathematcal framework for defnng trutworthne and trut. Baed on that framework, t defne the related concept of reputaton and argue that reputaton reportng ytem one of the mot promng approache for producng trut n onlne communte. It alo provde a crtcal overvew of the current tate of the art n that area. Followng that, t dentfe a numer of mportant way n whch unfar uyer and eller ehavor can comprome the relalty of the current generaton of reputaton reportng ytem. It then propoe and analyze a numer of novel mmunzaton mechanm for addreng thoe rk and explan how varou parameter of an onlne marketplace mcrotructure, mot notaly the anonymty regme and the ntal reputaton polce for new eller, can nfluence ther effectvene. Fnally, t conclude y dcung the mplcaton of the fndng for the degn of current and future onlne tradng communte and dentfe ome mportant open ue for future reearch. Workng Paper.

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3 1. Introducton At the heart of any lateral exchange there a temptaton, for the party who move econd, to defect from the agreed upon term n way that reult n ndvdual gan for t (and loe for the other party). For example, n tranacton where the uyer pay frt, the eller tempted to not provde the agreed upon good or ervce or to provde them at a qualty whch nferor to what wa adverted to the uyer. Unle there are ome other guarantee, the uyer would then e tempted to hold ack on her de of the exchange a well. In uch tuaton, the trade wll never take place and oth parte wll end up eng wore off. Unecured lateral exchange thu have the tructure of a Proner Dlemma. Our ocety ha developed a wde range of nformal mechanm and formal nttuton for managng uch rk and thu facltatng trade. The mple act of meetng face-to-face to ettle a tranacton help reduce the lkelhood that one party wll end up emptyhanded. Wrtten contract, commercal law, credt card compane and ecrow ervce are addtonal example of nttuton wth exactly the ame goal. Although mechanm degn and nttutonal upport can help reduce tranacton rk, they can never elmnate them completely. One example the rk nvolvng the exchange of good whoe real qualty can only e aeed y the uyer a relatvely long tme after a trade ha een completed (e.g. ued car). Even where ocety doe provde remedal meaure to cover rk n uch cae (for example, the Maachuett lemon law ), thee are uually urdenome and cotly and mot uyer would very much rather not have to reort to them. Generally peakng, the more the two de of a tranacton are eparated n tme and pace, the greater the rk. In thoe cae, no tranacton wll take place unle the party who move frt poee ome uffcent degree of trut that the party who move econd wll ndeed honor t commtment. The producton of trut, therefore, a precondton for the extence of any market and cvlzed ocety n general (Dunn, 1984). In rck and mortar communte, the producton of trut aed on everal cue, often ratonal ut ometme purely ntutve. For example, we tend to trut or dtrut potental tradng partner aed on ther appearance, the tone of ther voce or ther ody language. We alo ak our already truted partner aout ther pror experence wth the new propect. Taken together, thee experence form the reputaton of our propectve partner. Fnally, once we tart dong une wth a partner who prove trutworthy, we tend to e reluctant to wtch, even f we dentfy omeody ele who clam that he can offer u etter deal. The producton of trut thu often act a a wtchng cot. The emergence of electronc market and other type of onlne tradng communte are changng the rule on many apect of dong une. Electronc market prome utantal gan n productvty and effcency y rngng together a much larger et of uyer and eller and utantally reducng the earch and tranacton cot (Bako, 1997; Bako, 1998). In theory, uyer can then look for the et pole deal and end up 3

4 tranactng wth a dfferent eller on every ngle tranacton. None of thee theoretcal gan wll e realzed, however, unle market maker and onlne communty manager fnd effectve way to produce trut among ther memer. The producton of trut thu emergng a an mportant management challenge n any organzaton that operate or partcpate n onlne tradng communte. Several properte of onlne communte challenge the accumulated wdom of our ocete on how to produce trut. Formal nttuton, uch a legal guarantee, are le effectve n gloal electronc market, whch pan multple jurdcton wth, often conflctng, legal ytem. For example, t very dffcult, and cotly, for a uyer who rede n the U.S.A. to reolve a tradng dpute wth a eller who lve n Indonea. The dffculty compounded y the fact that, n many electronc market, t relatvely eay for tradng partner to uddenly dappear and reappear under a dfferent onlne dentty (Fredman and Renck, 1999; Kollock, 1999). Furthermore, many of the cue aed on whch we tend to trut or dtrut other ndvdual are aent n electronc market where face-to-face contact the excepton. Fnally, one of the motvatng force ehnd electronc market the dere to open up the unvere of potental tradng partner and enale tranacton among parte who have never worked together n the pat. In uch a large tradng pace, mot of one already truted partner are unlkely to e ale to provde much nformaton aout the reputaton of many of the other propect that one may e conderng. A a counteralance to thoe challenge, electronc communte are capale of torng full and accurate nformaton aout all tranacton they medate. Several reearcher and practtoner have, therefore, tarted to look at way n whch th nformaton can e aggregated and proceed y the market maker or other truted thrd parte n order to produce the equvalent of trut. Th ha lead to a new reed of ytem, whch are quckly ecomng an ndpenale component of every ucceful dgtal communty: electronc trut management ytem. We are already eeng the frt generaton of uch ytem n the form of onlne ratng, feedack or recommender ytem (Renck and Varan, 1997). The ac dea that onlne communty memer are gven the alty to rate or provde feedack aout ther experence wth other communty memer. Feedack ytem am to uld trut y aggregatng uch ratng of pat ehavor of ther uer and makng them avalale to other uer a predctor of future ehavor. ebay ( for example, encourage oth parte of each tranacton to rate one another wth ether a potve (+1), neutral (0) or a negatve (-1) ratng plu a hort comment. ebay make the cumulatve ratng of t memer, a well a all ndvdual comment pulcly avalale to every regtered uer. The majorty of the current generaton of onlne feedack ytem have een developed y Internet entrepreneur and ther properte have not yet een ytematcally reearched (Weer 2000). A We uer grow to depend on them, onlne trut management ytem 4

5 deerve new crutny and the tudy of trut management n dgtal communte deerve to ecome a new addton to the urgeonng feld of Management Scence. Th paper make everal contruton n th drecton: Frt, t ntroduce a mathematcal framework for defnng trutworthne and trut (Secton 2). Baed on that framework t defne the related concept of reputaton and argue that reputaton reportng ytem one of the mot promng approache for producng trut n onlne communte (Secton 3). It alo provde a crtcal overvew of the current tate of the art n that area (Secton 4). Followng that, t dentfe a numer of mportant way n whch the relalty of the current generaton of reputaton reportng ytem can e compromed y unfar uyer and eller (Secton 5). It then propoe a numer of novel mmunzaton mechanm for addreng thoe rk and explan how varou parameter of the marketplace mcrotructure, mot notaly the anonymty regme and the ntal reputaton polce for new eller, can nfluence ther effectvene (Secton 6). Fnally, t conclude y dcung the mplcaton of the fndng for the degn of current and future onlne tradng communte and dentfe ome mportant open ue for future reearch (Secton 7). 2. What Trut Before we can attempt to degn and evaluate relale ytem whoe ojectve to help produce trut n onlne communte, t mportant to undertand the exact meanng of the underlyng noton of trutworthne, trut and reputaton. Th epecally mportant ecaue thee concept, although they are o uqutou and pervave n our daly lve, have een notorouly dffcult to formally defne. Trut a ac fact of human lfe. Depte that (or maye ecaue of that) there an evdent lack of coherence among reearcher n the defnton of trut. There a huge ody of lterature on trut n feld a dvere a evolutonary ology (Bateon, 1990), ocology (Luhmann, 1979; Luhmann, 1990), ocal pychology (Deutch, 1962), economc (Hart et al., 1990; Dagupta, 1990), htory (Gametta, 1990a; Pagden, 1990), and phloophy (Lagenpetz, 1992; Hertzerg, 1988; Wttgenten, 1977). For notale attempt to compare and ntegrate the varou vewpont, the ntereted reader referred to (Gametta, 1990; Marh 1994). Perhap the mot popular and wdely accepted defnton of trut that of Deutch (1962), whch tate that: (a) the ndvdual confronted wth an amguou path, a path that can lead to an event perceved to e enefcal ( V ) or to an event perceved to e harmful ( V ); + () he perceve that the occurrence of V or V contngent on the ehavor of another peron; + and (c) he perceve the trength of V to e greater than the trength of V. + If he chooe to take an amguou path wth uch properte, I hall ay he make a trutng choce; f he chooe not to take the path, he make a dtrutful choce. (Deutch, 1962, page 303) 5

6 The ue of the word perceve many tme n th defnton mple that trut a ujectve, or agent-centered noton, one n whch the choce that are made are aed on ujectve vew of the world. Th of mportance n the dcuon and defnton to follow. In the ret of th ecton we wll clarfy and formalze th defnton n the context of tranacton-orented agent communte: Let a,, c, e the unvere of autonomou agent. Agent can e human or machne. By autonomou we mean that no agent ha drect control and power over the acton of another agent. For the purpoe of th paper, we defne a communty of agent a a uet of the unvere of agent grouped together y the fact that they engage n frequent tranacton of cla T. For example, the ebay communty the et of agent that engage n ntance of the cla of tranacton defned a uyng and ellng through the ebay wete. In the followng dcuon we aume, for mplcty, that all tranacton are lateral, that, they only nvolve two agent. We wll ue the ymol (uyer) and (eller) to refer to the two parte of a lateral tranacton. It mportant to emphaze, however, that the defnton of th ecton apply not only to uy-ell tranacton, ut alo to any other type of lateral tranacton. Defnton 1 1 : A crtcal attrute of agent from the perpectve of agent n the context of a tranacton t T an attrute whoe value affect the utlty of agent and contngent upon the ehavor of agent n the coure of tranacton t. Snce crtcal attrute relate to an agent ndvdual utlty, they are purely ujectve and may dffer even among agent engaged n tranacton of the ame type. For example, t reaonale to expect a tuaton where the crtcal attrute et of an ebay eller from the perpectve of ebay uyer {day etween payment wa made and 1 ook wa delvered, fnal prce}, wherea the crtcal attrute et of the ame eller from the perpectve of a dfferent uyer {fnal prce, ook condton},.e. the econd 2 uyer doe not care aout delvery tme ut care aout the ook condton. We wll dcu the mportance of th oervaton n Secton 4. Note, alo, that crtcal attrute need not necearly correpond to ntrnc attrute of agent. For example, n a ued car trade, the mot crtcal attrute the qualty of the car telf. In all cae they mut e contngent upon the ehavor of agent n the context of tranacton t. 1 For revty, the defnton that follow wll only e gven from the perpectve of agent, wth the undertandng that the equvalent defnton from the perpectve of the other party (agent ) are ymmetrc. 6

7 Dependng on the nature of t doman, a crtcal attrute can e contnuou or dcrete. Prce an example of a contnuou attrute. Servce qualty, expreed on an nteger cale of 1-10 an example of a dcrete attrute. Bnary attrute are a pecal cae of dcrete attrute, where the doman cont only of two value. The attrute product delvered y agreed upon deadlne, whoe doman the et {ye, no}, an example of a nary attrute. Defnton 2: Let X, X,..., X e the crtcal attrute of agent from the perpectve of 1 2 n agent n the context of a lateral tranacton t T etween and. Further, let D, D,..., D e ther repectve doman et. The crtcal ratng vector 1 2 n R ( t ) D D... D, pecfe agent ujectve ratng of all crtcal attrute of 1 2 n agent at the end of tranacton t. In a way, R ( t ) defne the outcome of tranacton t from the perpectve of agent. Before we proceed to the defnton of trutworthne and trut, t ueful to ntroduce here a further dtncton of crtcal attrute that wll play an mportant role n our later dcuon of trut ytem relalty. Defnton 3: Let C e a communty of agent where X a crtcal attrute of agent n the context of tranacton cla T from the perpectve of all agent C. Let, C e two agent and t, t T denote tranacton of thoe repectve agent wth agent. j Fnally, let R ( t ), R ( t ) e the repectve ratng of attrute X from the perpectve of j agent and at the end of tranacton t j and t. We ay that attrute X ojectvely j meaurale f and only f, aumng truthful ratng, the followng property hold: t t R ( t ) = R ( t ) for all agent, C (1) j j where the ymol denote dentty of tranacton, n the ene that agent and j made dentcal requet and agent ehaved n an dentcal manner n oth. We ay that a crtcal attrute ujectvely meaurale f there ext at leat a par of agent, C for whch property (1) doe not hold. j Intutvely, an attrute of an agent ojectvely meaurale f, a gven agent ehavor reult n dentcal ratng from the perpectve of all other agent who may have nteracted wth t. An attrute ujectvely meaurale f dentcal ehavor may reult n dfferent ratng from the perpectve of dfferent tranacton partner. Fnal prce and tme of delvery are two example of ojectvely meaurale attrute. On the other hand, qualty of ervce and merchande condton are two example of ujectvely meaurale attrute. j j 7

8 In mot agent communte, at leat ome of the crtcal attrute are ujectvely meaurale. A we wll ee n Secton 4, 5, and 6, th create ome very mportant complcaton for the contructon of relale trut management ytem. We are now ready to ntroduce the mportant noton of trutworthne and the related noton of trut. In a communty of autonomou agent, agent cannot control the ehavor of agent. Therefore, when conderng a tranacton whch equenced n tme, agent confronted wth the polty that agent may ehave n way that wll reult n a tranacton outcome wth negatve (or potve, ut unacceptaly low) utlty for. In order for agent to e ale to decde whether to proceed wth the tranacton, t mportant that ha ome nformaton that wll enale t to ae agent lkely ehavor. We call that pror ujectve aement of ehavor the trutworthne of a perceved y agent. More formally: Defnton 4: The trutworthne ( τ R ( t )) of agent a perceved y agent n the context of a tranacton t T the a pror ujectve jont proalty dtruton functon of the crtcal ratng vector R ( t ) from the perpectve of agent. For the ake of notatonal mplcty, n the next of the paper trutworthne wll e denoted mply a τ R, t ). ( Armed wth an aement of another agent trutworthne, agent now ale to reaon aout the tranacton rk. If we aume that a ratonal utlty-maxmzng agent, wll only proceed wth the tranacton f t uffcently confdent that t utlty at the end of the tranacton wll e aove a, ujectvely defned, mnmum threhold: Defnton 5: The mnmum threhold of atfacton u for agent n the context of a 0 tranacton t T the mnmum utlty that agent wllng to accept at the end of the tranacton n order to conder t atfactory. At th pont we have all the ngredent neceary to defne trut: Defnton 6: The level of trut Τ ( t ) of agent for agent n the context of a tranacton t T the a pror proalty that the utlty of agent wll meet or exceed t mnmum threhold of atfacton u at the end of tranacton t 0, gven perceved trutworthne of agent. Smply tated, trut the level of confdence of agent that the outcome of a tranacton wth another agent wll e atfactory for t. More formally: Τ ( t ) = U ( R) u 0 τ ( R, t ) dr (2) 8

9 where U (R) the utlty functon of agent. Snce trut ha een defned a a proalty, t range from [0,1]. The aove defnton have a numer of nteretng properte, whch correpond ncely wth the ntutve properte of trut n our everyday lfe. Trutworthne ujectve. Dfferent agent may have dfferent aement of agent lkely ehavor n the ame type of tranacton. Trutworthne defned relatve to a partcular et of crtcal attrute. Agent can have very dfferent trutworthne functon for dfferent et of attrute. When agent conderng agent a a potental partner n a tranacton of type T, t very mportant that the rght trutworthne functon ued. Th correpond to the ntutve noton that the ame agent could e condered very trutworthy a a partner n one et of tranacton and very untrutworthy n another. Example: You may trut your mechanc to fx your car ut you mght not trut hm to teach your lecture! Trutworthne defned at a gven pont n tme. In the general cae, the trutworthne functon wll vary wth tme, a agent accumulate more nformaton aout agent or a agent genunely modfe t ehavor. In the ret of the paper we wll often replace the argument t n τ ( R, t ) wth t, denotng tme, and wll conder trutworthne a a functon of tme. Trutworthne defned a a proalty dtruton, not a a ngle value! In the general cae, the calculaton of trut n formula (2) requre the knowledge of the entre trutworthne dtruton. Th an extremely mportant oervaton, gven that many current-generaton onlne trut management ytem attempt to calculate a ngle, calar cumulatve meaure of reputaton and trut. We wll revt th lat oervaton n Secton 4. In the meantme, we wll dcu a numer of pecal cae where the calculaton of trut can e mplfed. Monotonc utlty functon In many communte, agent utlty functon are monotoncally ncreang (decreang) functon of a gven crtcal attrute. For example, n mot real-lfe cae, uyer utlty a monotoncally ncreang functon of product qualty and a monotoncally decreang functon of total prce. Let u aume, for further mplfcaton that th attrute the only crtcal attrute n a gven tranacton cla. Under thoe aumpton, formula (2) can e rewrtten a + R0 Τ ( t ) = τ ( R, t ) dr f U (R) monotoncally ncreang (3a) and R0 Τ ( t ) = τ ( R, t ) dr f U (R) monotoncally decreang (3) 9

10 where R = U 1 (u ) 0 0 Gauan trutworthne functon Let u aume, a aove, that U (R) a monotoncally ncreang (decreang) functon of R. If, n addton, τ ( R, t ) approxmate a normal (Gauan) dtruton N ( µ, σ ), then equaton (3) can e further mplfed. By applyng the well-known properte of normal proalty dtruton to equaton (3) we get: Τ Τ R0 µ R ( t ) = 1 τ ( R, t ) dr ( = Φ σ R0 R µ 0 ( t ) = τ ( R, t ) dr = Φ( ) σ where Φ(x) the tandard normal CDF. 0 ) f U (R) f U (R) monotoncally ncreang (4a) monotoncally decreang (4) One mportant oervaton that n the pecal cae of Gauan trutworthne functon, the calculaton of trut level only requre aement of the mean and tandard devaton of the trutworthne functon,.e. two calar value, a oppoed to the entre dtruton. Relatve trut In everal cae, agent ha already decded to engage n a tranacton of type T and confronted wth the prolem of electng the et tradng partner from etween a par of elgle propect and 2. Let u aume that agent alway elect the agent t 1 2 trut more. In other word, t calculate t level of trut for each agent and elect 1 2 propect f Τ ( t ) > Τ ( t ) and propect otherwe. In thoe cae, what matter 1 2 mot are not the aolute trut level ut rather, ther relatve magntude. In the pecal cae of monotoncally ncreang utlte and Gauan trutworthne functon τ 1 ( R, t ) ~ N µ, σ ) and 2 τ ( R, t ) ~ N µ, σ ) from equaton (4a) we get: 1 2 Τ ( 1 ( 2 µ R µ R µ R µ R ( t ) > Τ ( t ) Φ( ) > Φ( ) > (5) σ σ σ σ The analy can ealy e generalzed n the cae of n propect. 10

11 If, n addton to all the aove aumpton we further aume that σ σ then the aove 1 2 formula can e further mplfed and gve: 1 2 ( t ) > Τ ( t ) µ > µ 1 2 Τ (6) In th very pecal cae, relatve trut can e aed on the knowledge of the mean of the trutworthne dtruton only. If U (R) a monotoncally decreang functon of R then the reult are mlar wth the drecton of nequalte revered. Bnary attrute A lat notale pecal cae the cae where the crtcal attrute et cont of a ngle nary crtcal attrute X, whch can take one of two value V (enefcal outcome) and V (harmful outcome) wth proalte p and (1-p) repectvely. Then: Τ ( t ) = p (7) Th another pecal cae where a ngle calar value (p) uffcent n order to etmate trut level. It alo the cae that correpond to the Deutch defnton of trut mentoned at the egnnng of the chapter. By connectng ack to the defnton of trut that we tarted wth, we have come full crcle. Baed on th ecton defnton, the next ecton dcue the role of communte n helpng agent ae the varou quantte needed n order to etmate trut level. 3. Mechanm of trut producton From formula (2) we can nfer that the producton of trut ha three prerequte: an agent hould know t utlty functon an agent hould et a mnmum threhold of atfacton relatve to a tranacton an agent hould etmate the trutworthne of t propectve tradng partner Of the three element of trut computaton the frt uually nternal and prvate to an agent. The econd ether nternal or the explct reult of a negotaton proce that precede a tranacton. The lat one, trutworthne, the trcket one to ae. Accordng to the precedng dcuon, t, too, the reult of a ujectve proce, whch comne external nformaton wth an agent general trutng dpoton (Boon and Holme, 1991). The role of external nformaton very mportant n th cae however. A communty ucce n producng trut among t memer depend on t alty to + 11

12 help agent contruct relale aement of the trutworthne of other communty memer. There are three ac way that communte go aout dong th: norm acked up y nttutonal guarantee ndrect cue reputatonal nformaton Norm and nttutonal guarantee attempt to reduce the uncertanty on the ehavor of other agent y precrng pecfc allowed ehavoral range (whch, uually correpond to atfactory outcome V for the majorty of tranacton type and ocety + memer) and y provdng nttuton, whch prevent devaton or make them hghly unlkely ecaue of quck detecton and effectve ancton (Paron, 1964). Inttutonal guarantee reduce the prolem of trutng ndvdual agent to that of trutng the nttuton: f one trut that nttuton wll do ther jo, there le need to ae the trutworthne of every ngle ndvdual agent. In the cae of nary attrute, the tuaton can e decred mathematcally τ ( R) = p(r = V I) p(i) + p(r = V I ) ( 1 p( Ι )) (8) + + where I denote the aumpton that nttuton functon effectvely. In the context of the aove equaton, nttuton prome that p(r = V + I) = 1, whch gve: τ ( R) = p(i) + p(r = V I ) ( 1 p( Ι )) p( I ) when p(i) get cloe to 1 (9) + The ue of nttutonal guarantee ha a numer of mportant hortcomng when appled to dgtal communte. Aeng the effectvene of nttuton not alway trval, epecally for newcomer to a gven dgtal communty. Even more mportant, however, nttuton are le effectve n onlne communte than they are n more tradtonal rck and mortar communte. There are two man reaon for th: frt, the mot ucceful onlne communte pan the oundare of everal terrtorally-aed jurdcton and ther memer are governed y dfferent, and often conflctng, legal ytem (Johnon and Pot, 1996). Second, n many onlne communte t relatvely eay to change dentte (Fredman and Renck, 1999). Although the evoluton of Internet law may may change th n the future, the overall effect that nttutonal guarantee are generally weaker n onlne envronment and thu, there more need to accurately ae the trutworthne of other potental tradng partner efore engagng n a tranacton wth them. Indrect cue are attrute of an agent, whch we have aocated wth certan lkely ehavor aed on our experence, ntuton and tranng. For example, mot people tend to perceve a well-dreed, well-mannered uneperon a eng trutworther than an unkempt, unruly one. Formally, the tranlaton of cue nto trutworthne aement nvolve condtonal ujectve proalty dtruton of the form p(ehavor cue) that we or our communty ha accumulated over long tme and paed on to u through 12

13 tradton and formal educaton. Many people gve very hgh value to thoe cue and conder them mportant factor of ther decon-makng. However, t exactly th knd of cue that are uually aent n onlne communte. Alo, thee cue are uele n the emergng cla of mult-agent market where the trader are oftware program (Mae et. al., 1999; Dellaroca and Klen, 2000). Reputatonal nformaton nformaton aout or oervaton of an agent pat ehavor on mlar tuaton, aggregated and dtruted y mean of word-of-mouth or through truted thrd parte, uch a credt ratng agence, conumer report, etc. Reputatonal nformaton can help agent contruct etmate on another agent trutworthne under the aumpton that agent have an underlyng dtruton of ehavor, whch relatvely tale over tme 3. Then, nformaton aout pat ehavor can e ued a tattcal ample from whch to contruct an etmate of the trutworthne dtruton for the purpoe of predctng future ehavor. We have delerately ued the term reputatonal nformaton n order to dtnguh t from the noton of reputaton telf. A reputaton, a defned y Wlon (Wlon, 1985) a charactertc or attrute acred to one peron y another. Operatonally, th uually repreented a a predcton aout lkely future ehavor. It, however, prmarly an emprcal tatement. It predctve power depend on the uppoton that pat ehavor ndcatve of future ehavor. Wlon defnton of reputaton very cloe to our defnton of trutworthne n the pecal cae where trutworthne prmarly aeed on the a on pat ehavor data (a oppoed to nttutonal guarantee or ndrect cue). Th lead to the followng defnton: Defnton 7: The reputaton of an agent a perceved y agent n the context of tranacton t T wth crtcal attrute et R t trutworthne dtruton τ ( R, t ) n the pecal cae where the etmaton of τ ( R, t ) aed on nformaton aout the pat ehavor of n tranacton of cla T. In the ret of the paper we wll often ue the term reputaton and trutworthne nterchangealy. Reputatonal nformaton, a dtnct from reputaton, the pat ehavor data ued y an agent n order to derve another agent trutworthne/reputaton. Th nformaton can come n the form of olated oervaton ( lat tme I tranacted wth X, I wan t very happy wth the ervce I got ) or n the form of cumulatve trutworthne/reputaton aement from the perpectve of other agent ( agent Y can provde very good ervce, ut t qualty ha not een content n the pat few month ). In fact, one of the mot nteretng degn dmenon n onlne reputaton reportng ytem the decon aout whether reputatonal nformaton hould e provded n the form of raw ratng or cumulatve meaure (ee Secton 4). 3 By relatvely tale we mean that, even when th dtruton changng over tme, t rate of change low relatve to the rate of oervaton. 13

14 Reputaton ha een the oject of tudy of the ocal cence for a long tme (Rogeron, 1983; Schmalenee, 1978; Shapro, 1982; Smallwood and Conlk, 1979). Several economt and game theort have demontrated that, n the preence of mperfect nformaton, the formaton of reputaton an mportant force that help uyer manage tranacton rk, ut alo provde ncentve to eller to provde good ervce qualty. Reputaton mot effectve when uyer and eller pert n a tradng communty for a long tme (Wlon, 1985). Th pertence often trcky to guarantee n onlne communte. The relatve eae wth whch computer can capture, tore and proce huge amount of nformaton aout pat tranacton, make reputatonal nformaton a partcularly promng way on whch to ae the producton of trut n onlne communte. Th fact, together wth the fact that the other tradtonal way of producng trut (nttutonal guarantee, ndrect cue) do not work a well n cyerpace, ha prompted reearcher and practtoner to focu ther attenton on developng onlne trut uldng mechanm aed on reputatonal nformaton. The next ecton wll urvey the current tate of the art n onlne reputaton reportng mechanm. 4. Reputaton reportng mechanm n onlne communte Havng nteracted wth omeone n the pat, of coure, the mot relale ource of nformaton aout that agent reputaton ecaue then the oervaton ued to etmate omeone reputaton are drect ample of the ujectve varale R whoe dtruton we eek to etmate. But, relyng only on drect experence oth neffcent and dangerou. Ineffcent, ecaue an ndvdual wll e lmted n the numer of exchange partner he or he ha and dangerou ecaue one wll dcover untrutworthy partner only through hard experence (Kollock, 1999). Thee hortcomng are epecally evere n the context of onlne communte where the numer of potental partner huge and the nttutonal guarantee n cae of negatve experence are weaker. Great gan are pole f nformaton aout pat nteracton hared and aggregated wthn a group n the form of opnon, ratng or recommendaton. In the rck and mortar communte th can take many form: nformal gop network, nttutonalzed ratng agence, profeonal crtc, etc. In cyerpace, they take the form of onlne reputaton reportng ytem, alo known a onlne recommender ytem (Renck and Varan, 1997). The focu of th ecton to provde a ref, crtcal urvey of the mot mportant ue and categore of thee ytem. 4.1 Degn ue n onlne reputaton reportng ytem Although the effectve aggregaton of other agent opnon can e a very effectve way to gather nformaton aout the reputaton of propectve tradng partner, not wthout ptfall. The followng paragraph decre three mportant ue that need to e addreed y opnon-aed reputaton reportng mechanm: 14

15 Conenu on crtcal attrute. Reputaton defned relatve to a pecfc et of crtcal attrute. The ame agent may have very dfferent reputaton for dfferent attrute. When accumulatng other agent opnon, t, therefore, extremely mportant to acertan that all opnon refer to the ame crtcal attrute. Th requre careful reearch from the part of the ratng mechanm degner, n order to dentfy the complete et of crtcal attrute for a gven communty, a well a careful communcaton of thoe attrute to communty memer. Sujectvely meaurale attrute. For ujectvely meaurale crtcal attrute (ee Secton 2, Defnton 3) the ame ehavor of agent v-à-v two dfferent agent 1 and may reult n two dfferent ratng R 2 R. In order for agent to make ue 1 2 of thee conflctng ratng a a a for calculatng agent reputaton, t mut frt try to tranlate each of them nto t own value ytem. In tradtonal communte we addre the aove ue y prmarly acceptng recommendaton from people whom we know already. In thoe cae, our pror experence wth thee people help u gauge ther opnon and tranlate them nto our value ytem. For example, we may know from pat experence that Bll extremely demandng and o a ratng of acceptale on h cale would correpond to rllant on our cale. A a further example, we may know that Mary and we have mlar tate n move ut not n food, o we follow her opnon on move whle we gnore her recommendaton on retaurant. Due to the much larger numer of potental tradng partner, n onlne communte t, once agan, le lkely that our mmedate frend wll have had drect experence wth everal of the propect condered. It, therefore, more lkely that we wll have to rely on the opnon of tranger o gaugng uch opnon ecome much more dffcult. Fale opnon. For a numer of reaon agent may delerately provde fale opnon aout another agent, that, opnon, whch ear no relatonhp to ther truthful aement of ther experence wth that other agent. In contrat to ujectve opnon, for whch we have aumed that there can e a polty of tranlaton to omeody ele value ytem, fale opnon are uually delerately contructed to mlead ther recpent and the only enle way to treat them to gnore them. In order to e ale to gnore them, however, one ha to frt e ale to dentfy them. Before acceptng opnon, rater mut, therefore, alo ae the trutworthne of other agent wth repect to gvng honet opnon. (Yahalom et. al., 1993) correctly ponted out that the o-called recommender trutworthne of an agent orthogonal to t trutworthne a a ervce provder. In our framework, th fact a mple corollary of the defnton of trutworthne relatve to a pecfc et of crtcal attrute. 15

16 In the ret of the ecton we wll refly urvey the varou clae of propoed onlne reputaton reportng ytem and wll dcu how each of them addree the aove ue. 4.2 Recommendaton repotore Recommendaton repotore tore and make avalale recommendaton from a large numer of communty memer wthout attemptng to utantally proce or qualfy them. Th reduce the earch cot of ntereted agent, who can then fnd a large numer of recommendaton n a ngle place. The We ovouly very well uted for contructng uch repotore. In fact, mot current-generaton we-aed recommendaton ytem fall nto th category. A typcal repreentatve of th cla of ytem the feedack mechanm of aucton te ebay. Other popular aucton te, uch a Yahoo and Amazon employ very mlar mechanm. ebay encourage the uyer and eller of an ebay-medated tranacton to leave feedack for each other. Feedack cont of a numercal ratng, whch can e +1 (prae), 0 (neutral) or 1 (complant) plu a hort (80 character max.) text comment. ebay then make the lt of all umtted feedack ratng and comment accele to any other regtered uer of the ytem. ebay doe calculate ome rudmentary tattc of the umtted ratng for each uer (the um of potve, neutral and negatve ratng n the lat 7 day, pat month and 6 month) ut, otherwe, t doe not flter, modfy or proce the umtted ratng. Recommendaton repotore are a tep n the rght drecton. They make lot of nformaton aout other agent avalale to ntereted uer, ut they expect uer to make ene of thoe ratng themelve and draw ther own concluon. On the one hand, th vewpont content wth the fact that the aement of trutworthne and trut a ujectve proce. On the other hand, however, th aelne approach doe not cale very well. In tuaton where there are dozen or hundred of, poly conflctng, ratng, uer need to pend conderale effort readng etween the lne of ndvdual ratng n order to tranlate other people ratng to ther own value ytem or n order to decde whether a partcular ratng honet or not. What more, n communte where mot rater are complete tranger to one another, there no concrete evdence that relale readng etween the lne pole at all. Fnally, ratng repotore rely at th tage proaly more on textual comment than they do on numercal ratng. Th make them unutale for ue n oftware agent communte where the uyng and ellng performed y automated oftware program. A lot of thee hortcomng do not ext n cae where ratng are aed on ojectvely meaurale attrute (e.g. on-tme record of arlne, numer of lot aggage ncdent per month etc.). In thoe cae, mple ratng repotore can e very effectve. 16

17 4.3 Profeonal (pecalt) ratng te Specalt-aed recommendaton ytem employ truted and knowledgeale pecalt who then engage n frt-hand tranacton wth a numer of ervce provder and then pulh ther authortatve ratng. Other uer then ue thee ratng a a a for formng ther own aement of omeone trutworthne. Example of pecalt-aed recommendaton are retaurant crtc (Zagat ), credtratng agence (Moody ) and e-commerce profeonal ratng agence, uch a Gomez Advor, Inc. ( The gget advantage of pecalt-aed recommendaton ytem that t addree the prolem of fale ratng mentoned aove. In mot cae pecalt are profeonal and take great pan to uld and mantan ther trutworthne a dntereted, far ource of opnon. On the other hand, pecalt-aed recommendaton ytem have a numer of hortcomng, whch ecome even more evere n onlne communte: Frt, pecalt can only tet a relatvely mall numer of ervce provder. There tme and cot nvolved n performng thee tet and, the larger and the more volatle the populaton of one communty, the lower the percentage of certfed provder. Second, pecalt mut e ale to uccefully conceal ther dentty or ele there a danger that provder wll provde atypcally good ervce to the pecalt for the purpoe of recevng good ratng. Thrd, pecalt are ndvdual wth ther own tate and nternal ratng cale, whch do not necearly match that of any other uer of the ytem. Indvdual uer of pecalt ratng tll need to e ale to gauge a pecalt recommendaton, n order to derve ther own lkely aement. Lat ut not leat, pecalt typcally ae ther ratng on a very mall numer of ample nteracton wth the ervce provder (often jut one). Th make pecalt ratng a very weak a from whch to etmate the proalty dtruton of omeone ervce attrute whch what we have defned a trutworthne/reputaton. 4.4 Collaoratve flterng ytem Collaoratve flterng technque (Golderg et. al., 1992; Renck et. al., 1994; Shardanand and Mae, 1995; Bllu and Pazzan, 1998) attempt to proce raw ratng contaned n a recommendaton repotory n order to help rater focu ther attenton only on a uet of thoe ratng, whch are mot lkely to e ueful to them. The ac dea ehnd collaoratve flterng to ue pat ratng umtted y a uer a a a 0 for locatng other uer,,... whoe ratng are lkely to e mot ueful to uer n order to accurately predct omeone reputaton from t own ujectve perpectve. There are everal related technque: Clafcaton or cluterng approache rely on the aumpton that agent communte form a relatvely mall et of tate cluter, wth the property that ratng of agent of the 17

18 ame cluter for mlar thng are very mlar to each other. Each tate cluter ha the property that: t C then k t R ( t ) R ( t ) for all agent, C (10) j j Therefore, f the tate cluter of a uer can e dentfed, then ratng of other memer 0 of that cluter can e readly ued a tattcal ample for etmatng the ujectve proalty dtruton of R ( t ) from the perpectve of. 0 0 The prolem of dentfyng the rght tate cluter for a gven agent reduce to the welltuded prolem of clafcaton/data cluterng (Kaufman and Roueeuw, 1990; Jan et, al. 1999; Gordon, 1999). Collaoratve flterng reearcher have expermented wth a varety of approache, aed on tattcal mlarty meaure (Renck et. al., 1994; Breee et. al., 1998) a well a machne learnng technque (Bllu and Pazzan, 1998). Regreon approache rely on the aumpton that the ratng of an agent can often e related to the ratng of another agent through a lnear relatonhp of the form j j k R α R ( t + β j j j ( t ) = ) for all agent (11) Th aumpton motvated y the elef, wdely accepted y economt (Arrow, 1963; Sen, 1986) that, even when agent have mlar tate, one uer nternal cale not comparale to another uer cale. Accordng to th elef, n a gven communty the numer of trct nearet neghor wll e very lmted whle the aumpton of (11) open the polty of ung the recommendaton of a much larger numer of agent a the a for calculatng an agent trutworthne. In that cae, f we can etmate the parameter α, β for each par of agent, we can ue formula (11) to tranlate the ratng of agent j j to the nternal cale of agent j ( and then treat the tranlated ratng a tattcal ample of the dtruton of R t ) from the perpectve of agent The prolem of etmatng thoe parameter reduce to the well-tuded prolem of lnear regreon. There a huge lterature on the topc and a lot of effcent technque, whch are applcale to th context (Malnvaud, 1966; Pndyck and Runfeld, 1981) The ptfall of calculatng cumulatve meaure of reputaton Mot collaoratve flterng ytem do not mply compute mlarte or regreon coeffcent etween uer ratng. They go further and compute cumulatve meaure, whch are ntended to e nterpreted a etmate of reputaton of uer. 18

19 The mot commonly encountered cumulatve meaure have the form of a weghted average of ndvdual ratng. Dfferent propoed approache are ung dfferent way to calculate the weght. For example, Renck et. al (1994) propoe the ue of the Pearon correlaton coeffcent, whle Breee et. al. (1998) propoed the ue of vector mlarty meaure a well a everal heurtcally derved adjutment to weght. The computaton of cumulatve meaure of reputaton ueful ecaue t reduce the computatonal urden on the de of the agent. However, we eleve that, n the current generaton of ytem, t often a mleadng and dangerou nput for uldng trut. Frt of all, a ponted out y Bllu and Pazzan (1998), mot of the currently propoed cumulatve meaure are not upported y a ound theory of reputaton and trut. For example, a weghted average of ndvdual ratng where the weght are correlaton coeffcent doe not have a drect correpondence to any of the trut-related concept ntroduced n th paper. Furthermore, n Secton 2 we eleve that we have made a trong cae for the fact that the calculaton of trut level, whether aolute or relatve, requre the knowledge of the entre trutworthne/reputaton dtruton. A ngle calar cumulatve meaure uually not uffcent for decrng a dtruton except n very pecal cae, uch a the dtruton of nary attrute, or normal dtruton where the varance condered to e roughly the ame throughout the agent populaton. 4.6 Summary Th ecton ha urveyed a numer of dfferent clae of current-generaton reputaton reportng mechanm n onlne communte. Of the varou clae of ytem urveyed, our concluon that collaoratve flterng approache have the et potental for calalty and accuracy. Neverthele, further reearch requred n order for uch ytem to ecome relale and trutworthy enough. We have dentfed a numer of prolem that tll need to e addreed: achevng conenu on the crtcal attrute for whch ratng are tored dervng theoretcally ound cumulatve meaure of reputaton copng wth the polty of ntentonally fale ratng The ret of the paper focue on the lat prolem. 5. The effect of unfar ratng n onlne reputaton reportng ytem The precedng dcuon on trut uldng n onlne communte ha dentfed two mportant challenge for the effectve ue of reputatonal nformaton a a a for trut producton: Frt the ujectve nature of ratng on many commonly ued crtcal attrute and the need to tranlate omeody ele ratng to our own value ytem. Second, the polty that ome of the rater may provde unfar (ntentonally fale) ratng. Although collaoratve flterng reearcher have looked at the frt prolem, to 19

20 date the econd prolem ha receved very lttle attenton. Our goal n th ecton to tudy a numer of unfar ratng cenaro and analyze ther effect n compromng the relalty of a collaoratve-flterng-aed reputaton reportng ytem. To mplfy the dcuon, n the ret of the paper we are makng the followng aumpton: We aume a tradng communty whoe partcpant are dtnguhed nto uyer and eller. We further aume that only uyer can rate eller. In a future tudy we wll conder the mplcaton of -drectonal ratng. In a typcal tranacton, a uyer contract a eller for the provon of a ervce. Upon concluon of the tranacton, provde a numercal ratng R ( t ), reflectng ome attrute Q of the ervce offered y a perceved y (ratng can only e umtted n conjuncton wth a tranacton). Agan, for the ake of mplcty we aume that R ( t ) a calar quantty, although, a we noted n the prevou ecton, n mot tranacton there are more than one crtcal attrute and R t ) would e a vector. ( We further aume the extence of an onlne reputaton reportng mechanm, whoe goal to tore and proce pat ratng n order to calculate relale peronalzed reputaton etmate for eller upon requet of a propectve uyer. In ettng where the crtcal attrute Q for whch ratng are provded not ojectvely meaurale, there ext four cenaro where uyer and/or eller can ntentonally try to rg the ytem, reultng n aed reputaton etmate, whch do not reflect the true expected dtruton of attrute Q for a gven eller: a. Unfar ratng y uyer Unfarly hgh ratng ( allot tuffng ): A eller collude wth a group of uyer n order to e gven unfarly hgh ratng y them. Th wll have the effect of nflatng a eller reputaton, therefore allowng that eller to receve more order from uyer and at a hgher prce than he deerve. Unfarly low ratng ( ad-mouthng ): Seller can collude wth uyer n order to ad-mouth other eller that they want to drve out of the market. In uch a tuaton, the conprng uyer provde unfarly negatve ratng to the targeted eller, thu lowerng ther reputaton.. Dcrmnatory eller ehavor Negatve dcrmnaton: Seller provde good ervce to everyone except a few pecfc uyer that they don t lke. If the numer of uyer eng dcrmnated upon relatvely mall, the cumulatve reputaton of eller wll e good and an externalty wll e created agant the vctmzed uyer. Potve dcrmnaton: Seller provde exceptonally good ervce to a few elect ndvdual and average ervce to the ret. The effect of th equvalent to allot 20

21 tuffng. That, f the favored group uffcently large, ther favorale ratng wll nflate the reputaton of dcrmnatng eller and wll create an externalty agant the ret of the uyer. The oervale effect of all four aove cenaro that there wll e a dperon of ratng for a gven eller. If the rated attrute not ojectvely meaurale, t wll e very dffcult, or mpole to dtnguh ratng dperon due to genune tate dfference from that whch due to unfar ratng or dcrmnatory ehavor. Th create a moral hazard, whch requre addtonal mechanm n order to e ether avoded, or detected and reolved. In the followng analy, we aume the ue of collaoratve flterng technque n order to addre the ue of ujectve ratng. More pecfcally, we aume that, n order to etmate the peronalzed reputaton of from the perpectve of, ome collaoratve flterng technque ued to dentfy the nearet neghor et N of. N nclude uyer who have prevouly rated and who are the nearet neghor of, aed on the mlarty of ther ratng wth thoe of on other commonly rated eller 4. Sometme, th tep wll flter out all unfar uyer. Suppoe, however, that the colluder have taken collaoratve flterng nto account and have cleverly pcked uyer whoe tate are mlar to thoe of n everythng ele except ther ratng of. In that cae, the reultng et N wll nclude ome far rater and ome unfar rater. Effect when reputaton teady over tme The mplet cenaro to analyze one where we can aume that agent ehavor, and therefore reputaton, reman teady over tme. That mean that, collaoratve flterng algorthm can take nto account all ratng n ther dataae, no matter how old. In order to make our analy more concrete, we wll make the aumpton that far ratng can range etween [ R, R ] and that they follow a dtruton of the general mn max form: τ R) = max( R, mn( R, z)) where z ~ N ( µ, σ ) (12) ( mn max whch n the ret of the paper wll e approxmated to τ ( R) N( µ, σ ). The ntroducton of mnmum and maxmum ratng ound correpond ncely wth common practce. The aumpton of normally dtruted far ratng, requre more dcuon. It aed on the prevou aumpton that thoe ratng elong to the nearet neghor et of a gven uyer, and therefore repreent a ngle tate cluter. Wthn a tate cluter, t expected that far ratng wll e relatvely cloely clutered around ome value and hence the 4 In the cae of regreon-aed ytem the nearet neghor et of uyer a of the tranlated ratng R j = α R + β j j j would e computed on the 21

22 aumpton of normalty. In the near future we ntend to emprcally verfy th aumpton y analyzng ome extng ratng dataae. In Secton 2 we have hown that, n the pecal cae where τ ( R) N( µ, σ ), the calculaton of trut level only requre the etmaton of the two calar parameter µ, σ of the reputaton dtruton. In th paper we wll focu on the relale etmaton of the reputaton mean. The relale etmaton of the reputaton tandard devaton the topc of a forthcomng paper. Gven all the aove aumpton, the goal of a relale reputaton reportng ytem hould e the calculaton of a far mean reputaton etmate (MRE) whch equal to or very cloe to µ, the mean of the far ratng dtruton n the nearet neghor et. Ideally, therefore: ˆ = µ (13) R, far On the other hand, the goal of unfar rater to trategcally ntroduce unfar ratng n order to maxmze the dtance etween the actual MRE R ˆ, calculated y the actual reputaton ytem and the far MRE. More pecfcally the ojectve of allot-tuffng agent to maxmze the MRE whle ad-mouthng agent am to mnmze t. Note that, n contrat to the cae of far ratng, t not afe to make any aumpton aout the form of the dtruton of unfar ratng. Therefore, all analye n the ret of th paper wll calculate ytem ehavor under the mot druptve pole unfar ratng trategy. We wll only analyze the cae of allot-tuffng nce the cae of ad-mouthng ymmetrcal. Aume that the ntal collaoratve flterng tep contruct a nearet neghor et N, whch nclude (1 δ) 100% far rater and δ 100% unfar rater. Fnally, aume that the actual MRE R ˆ, taken to e the ample mean of the mot recent actual ratng gven to y each qualfyng rater n N. In that cae, the actual MRE wll approxmate: R ˆ (1 δ ) µ + δ µ (14), actual u where µ the mean value of unfar ratng. The trategy, whch maxmze the aove u MRE one where µ = R,.e. where all unfar uyer gve the maxmum pole u max ratng to the eller. We defne the mean reputaton etmate a for a contamnated et of ratng to e: ˆ B = R, actual ˆ (15) R, far In the aove cenaro, the maxmum MRE a gven y: 22

23 B = 1 δ ) µ + δ R µ = δ ( R ) (16) ( µ max max max Fgure 1 taulate ome value of Bmax for everal dfferent value µ and δ, n the pecal cae where ratng range from [0,9]. We have generally condered ae aove 5% of the ratng range (.e. ae greater than 0.5 pont on ratng whch range from 0-10) to e unacceptale. A can e een, formula (16) can reult n very gnfcant nflaton of a eller MRE, epecally for mall µ and large δ. Effect when reputaton vare over tme Th ecton expand our analy y dcung ome addtonal conderaton, whch are n envronment where eller ehavor, and therefore reputaton, may vary over tme. We dentfy ome addtonal unfar ratng tratege that can e very druptve n uch envronment. In real-lfe tradng communte, eller may vary ther ervce qualty over tme, mprovng t, deteroratng t, or even ocllatng etween phae of mprovement and phae of deteroraton. In h emnal analy of the economc effect of reputaton, (Shapro 1981) proved that, n uch envronment, the mot economcally effcent way to etmate a eller reputaton (.e. the way that nduce the eller to produce at the hghet qualty level) a a tme dcounted average of recent ratng. Shapro went even further to prove that effcency hgher (1) the hgher the weght placed on recent qualty ratng and (2) the hgher the dcount factor of older ratng. In th paper we are ang our analy on an approach, whch approxmate Shapro dederata, ut mpler to mplement and analyze. The prncpal dea to calculate tme varyng peronalzed MRE Rˆ ( t) a average of ratng umtted wthn the mot recent tme wndow W=[t-ε, t] only. Th equvalent to ung a tme dcounted average calculaton where weght are equal to 1 for ratng umtted wthn W and 0 otherwe. More pecfcally, n order to calculate a tme varyng peronalzed MRE Rˆ ( t), we frt ue collaoratve flterng n order to contruct an ntal nearet neghor et N ntal. Followng that we contruct the actve nearet neghor et N actve, contng only of thoe uyer u N ntal who have umtted at leat one ratng for wthn W. Fnally, we ae the calculaton of Rˆ ( t) on ratng (t) where u N actve and t W. R u Formula (16) make t clear that the maxmum reputaton a due to unfar ratng proportonal to the rato δ of unfar ratng, whch make t nto the actve nearet neghor et N actve. Therefore, an ovou trategy for unfar uyer to try to ncreae δ y floodng the ytem wth unfar ratng. (Zachara et. al. 1999) touch upon th ue and propoe keepng only the lat ratng gven y a gven uyer to a gven eller a a oluton. In envronment where reputaton etmate ue all avalale ratng, th mple trategy enure that eventually δ can never e more than the actual fracton of unfar rater n the communty, uually a very mall fracton. However, the trategy reak 23

24 down n envronment where reputaton etmate are aed on ratng umtted wthn a relatvely hort tme wndow (or where older ratng are heavly dcounted). The followng paragraph explan why. Let u aume that the ntal nearet neghor et N ntal contan m far rater and n unfar rater. In mot cae n << m. Aume further that the average nterarrval tme of far ratng for a gven eller λ and that peronalzed MRE Rˆ ( t) are aed only on ratng for umtted y uyer u N ntal wthn the tme wndow W = [t kλ, t]. Baed on the aove aumpton, the average numer of far ratng umtted wthn W would e equal to k. To enure accurate reputaton etmate, the wdth of the tme wndow W hould e relatvely mall; therefore k hould generally e a mall numer (ay, etween 5 and 20) 5. For k << m we can aume that every ratng umtted wthn W from a dtnct far rater. Aume now that unfar rater flood the ytem wth ratng at a frequency much hgher than the frequency of far ratng. If the unfar ratng frequency hgh enough, every one of the n unfar rater wll have umtted at leat one ratng wthn the tme wndow W. A uggeted y Zachara et. al., we keep only the lat ratng ent y each rater. Even ung that rule, however, the aove cenaro would reult n an actve nearet neghor et of rater where the fracton of unfar rater δ = n/(n+k). Th expreon reult n δ 0.5 for n k, ndependent of how mall n relatve to m. For example, f n=10 and k=5, δ = 10/(10+5) = We therefore ee that, for relatvely mall tme wndow, even a mall (e.g. 5-10) numer of colludng uyer can uccefully ue unfar ratng floodng to domnate the et of ratng ued to calculate MRE and completely a the etmate provded y the ytem. The reult of th ecton ndcate that even a relatvely mall numer of unfar rater can gnfcantly comprome the relalty of collaoratve-flterng-aed reputaton reportng ytem. Th requre the development of effectve meaure for addreng the prolem. Next ecton propoe and analyze everal uch meaure. 6. Mechanm for mmunzng onlne reputaton reportng ytem agant unfar rater ehavor Havng recognzed the prolem of unfar ratng a a real and mportant one, th ecton propoe a numer of mechanm for elmnatng or gnfcantly reducng t advere effect on the relalty of onlne reputaton reportng ytem. The handlng of any knd of harmful excepton, that, devaton from derale or normal ehavor, fundamentally nvolve two clae of mechanm: avodance mechanm, whch proactvely try to prevent th ehavor from occurrng at all and recovery mechanm, whch detect occurrence of th ehavor and attempt to reduce t harmful conequence for the ntereted parte and the communty at large (Dellaroca 5 Makng the wdth of the tme wndow mall approxmately equvalent to ung a hgher dcount factor for older ratng, whch, accordng to Shapro, reult n more effcent reputaton mechanm. 24

25 and Klen 2000a). Baed on th dtncton, we are clafyng our propoed mechanm nto avodance mechanm and recovery mechanm. 6.1 Avodng negatve unfar ratng ung controlled anonymty The man argument of th ecton that the anonymty regme of an onlne communty can nfluence the knd of reputaton ytem attack that are pole. A lghtly urprng reult the realzaton that a fully tranparent marketplace, where everyody know everyody ele true dentty ncur more danger of reputaton ytem fraud than a marketplace where the true dentte of trader are carefully concealed from each other ut are known to the market-maker. We tart y ntroducng ome concept that are needed n order to characterze the anonymty regme of a marketplace. Frt, we aume that agent, whether human or machne, are exactly that. That, they partcpate n communte and engage n tranacton on ehalf of ome real-lfe prncpal entty P. P can e an ndvdual or an organzaton. What mportant here that P ha a fxed and pertent real-world extence and dentty, whch we aume mpole to change. An dentfer I a pece of nformaton whch pulcly known wthn an onlne communty and whch ued n order to refer to an agent n the context that communty. At the mnmum, an dentfer hould provde a way for nformaton to reach an agent, a well a for an agent to end nformaton to other agent. IP addree and emal addree are example of dentfer wth th property. The authentcaton regme of an onlne communty pecfe the degree of certanty wth whch communty actvty performed ung dentfer I can e lnked to a unque prncpal entty P y ome partcpant of the communty. Perfectly authentcated communte guarantee that f anyody ue dentfer I to end or receve nformaton wthn a communty, that that omeody can only e prncpal P. The degn of effectve authentcaton regme and procee an mportant reearch topc wthn the feld of Computer Securty (Hutt et. al., 1995). Onlne communte form a pectrum wth regard to ther authentcaton regme, rangng from very well authentcated to nonauthentcated. In non-authentcated communte, prncpal are acally free to create multple dentfer or to dcontnue ung them, effectvely dappearng and reappearng at wll. The tranparency regme of an onlne communty pecfe whch memer of the communty have the rght to apply or acce the reult of a communty authentcaton proce. Otherwe tated, t pecfe who allowed to know the true dentty of the prncpal P related to an dentfer I. At one end of the pectrum, every memer of the communty gven that rght. In that cae, we have fully tranparent communte. At the other extreme, there are communte where the only entty who ha acce to the true dentty of communty memer the party who control the nfratructure reource of the communty. 25

26 Below we argue that, under the aumpton that the market maker can e truted, full tranparency ncur more danger than a cheme where dentte are authentcated ut carefully concealed. Bad-mouthng and negatve dcrmnaton are aed on the alty to pck a few pecfc vctm and gve them unfarly poor ratng or provde them wth poor ervce repectvely. Uually, vctm are elected aed on ome real-lfe attrute of ther aocated prncpal entte (for example, ecaue they are our compettor or ecaue of relgou or racal prejudce). Th advere electon proce can e avoded f the communty conceal the true dentte of the uyer and eller from each other. In uch a controlled anonymty cheme, the marketplace know the true dentty of all market partcpant y applyng ome effectve authentcaton proce efore t allow acce to any agent. In addton, t keep track of all tranacton and ratng. The marketplace pulhe the etmated reputaton of uyer and eller ut keep ther dentte concealed from each other (or agn them peudonym whch change from one tranacton to the next, n order to make dentty detecton very dffcult). In that way, uyer and eller make ther decon olely aed on the offered term of trade a well a the pulhed reputaton. Becaue they can no longer dentfy ther vctm, admouthng and negatve dcrmnaton can e avoded. It nteretng to oerve that, whle, n mot cae, the anonymty of onlne communte ha een vewed a a ource of addtonal rk (Kollock 1999; Fredman and Renck 1999), here we have an example of a tuaton where ome controlled degree of anonymty can e ued to elmnate ome tranacton rk. Concealng the dentte of uyer and eller not pole n all doman. For example, concealng the dentty of eller not pole n retaurant and hotel ratng (although concealng the dentty of uyer ). In other doman, t may requre the creatve nterventon of the marketplace. For example, n a marketplace of electronc component dtrutor, t may requre the marketplace to act a an ntermedary hppng hu that wll help erae nformaton aout the eller addre. If concealng the dentte of oth parte from each other not pole, then t may tll e ueful to conceal the dentty of one party only. More pecfcally, concealng the dentty of uyer ut not eller avod negatve dcrmnaton agant hand pcked uyer ut doe not avod ad-mouthng of hand pcked eller. In an analogou manner, concealng the dentty of eller ut not uyer avod ad-mouthng ut not negatve dcrmnaton. Thee reult are ummarzed n Fgure 2. Generally peakng, concealng the dentte of uyer uually eaer than concealng the dentte of eller (a mlar pont made n Cranor and Renck 1999). Th mean that negatve dcrmnaton eaer to avod than ad-mouthng. Furthermore, concealng the dentte of eller efore a ervce performed uually eaer than afterward. In doman wth th property, controlled anonymty can e ued at the eller electon tage n order to, at leat, protect eller from eng ntentonally pcked for 26

27 uequent ad-mouthng. For example, n the aove-mentoned marketplace of electronc component dtrutor, one could conceal the dentte of eller untl after the clong of a deal. Aumng that the numer of dtrutor for a gven component type relatvely large, th trategy would make t dffcult, or mpole, for malevolent uyer to ntentonally pck pecfc dtrutor for uequent ad-mouthng. It mportant to note at th pont that even when dentte of uyer and eller are concealed, uyer and eller who have an ncentve to gnal ther dentte to each other can alway fnd clever way to do o. For example, eller nvolved n a allot tuffng cheme can ue a partcular pattern n the amount that they d (e.g. amount endng n.33) n order to gnal ther preence to ther conprator. Therefore, whle controlled anonymty can avod ad-mouthng and negatve dcrmnaton, t cannot avod allot tuffng and potve dcrmnaton. The followng two ecton propoe ome flterng mechanm, whch are applcale n the cae of allot tuffng a well. 6.2 Reducng the effect of unfar ratng ung medan flterng In Secton 5 we have aed our calculaton of reputaton a on the aumpton that MRE are aed on the ample mean of the nearet neghor et. In th ecton we wll demontrate that the effect of unfar ratng can e gnfcantly reduced f, ntead of the ample mean, the calculaton of MRE aed on the ample medan 6. The feld of rout tattc ha devoted conderale attenton to the prolem of fndng etmator of locaton (mean value), whch are rout n the preence of contamnated ample (Huer, 1981). Neverthele, mot of that lterature treat contamnaton a nnocent noe and doe not addre the prolem of malcou rater who, aed on ther knowledge of the etmator ued, trategcally dtrute unfar ratng n order to maxmze the achevale a. To the knowledge of the author, the analy preented n th ecton novel. The ample medan Y ~ of n ordered oervaton Y Y... Y the mddle 1 2 n oervaton Y where k= (n+1)/2 f n odd. When n even then Y ~ condered to e k any value etween the two mddle oervaton Y and Y where k=n/2, although t k k + 1 mot often taken to e ther average. In the aence of unfar ratng (.e. when δ=0) we have prevouly aumed that τ ( R) N( µ, σ ). It well known (Hojo, 1931) that, a the ze n of the ample ncreae, the medan of a ample drawn from a normal dtruton converge rapdly to a normal dtruton wth mean equal to the medan of the parent dtruton. In normal 6 The ample medan turned out to e the et out of everal dfferent canddate rout etmator of MRE teted y the author. The detaled comparon among the varou meaure are outde the cope of th work and are decred n a forthcomng paper. 27

28 dtruton, the medan equal to the mean. Therefore, n tuaton where there are no unfar rater, the ue of the ample medan reult n unaed far MRE: ˆ µ (17) R, far Let u now aume that unfar rater know that MRE are aed on the ample medan. They wll trategcally try to ntroduce unfar ratng whoe value wll maxmze the aolute a etween the ample medan of the far et and the ample medan of the contamnated et. More pecfcally, allot tuffer wll try to maxmze that a whle ad-mouther wll try to mnmze t. In the followng analy we conder the cae of allot tuffng. The cae of ad-mouthng ymmetrc, wth the gn revered. Aumng that the nearet neghor et cont of n f = ( 1 δ ) n far ratng and n u = δ n unfar ratng, where 0 δ < 0. 5, the mot druptve unfar ratng trategy, n term of nfluencng the ample medan, one where all unfar ratng are hgher than the ample medan of the contamnated et. In that cae and for δ < 0. 5, all the ratng, whch are lower than or equal to the ample medan wll have to e far ratng. Then, the ample medan of the contamnated et, wll e dentcal to the k th order tattc of the et of n far ratng, where k=(n+1)/2. f It ha een hown (Cadwell 1952) that, a the ze n of the ample ncreae, the k th order tattc of a ample drawn from a normal dtruton N( µ, σ ) converge rapdly to a normal dtruton wth mean equal to the q th quantle of the parent dtruton where q=k/n. Therefore, for large ratng ample n, under the wort pole unfar ratng trategy, the ample medan of the contamnated et wll converge to x where x q q defned y: Pr[ R x q ] = q x q = σ Φ 1 ( q) + µ (18) where k n + 1 n q = = = (19) n n 2 n n 2 (1 δ ) 2 (1 δ ) f f and Φ 1 ( q) the nvere tandard normal CDF. Gven that R ˆ µ, the aymptotc formula for the average 7 reputaton a achevale far y δ 100% unfar ratng when far ratng are drawn from a normal dtruton 7 We are aumng here that unfar rater have knowledge of µ and σ ut do not have knowledge of the exact ndvdual value of far ratng, whch, n a tme-wndowed ytem, are rapdly changng anyway. Therefore ther ojectve to maxmze the expected value of the MRE a. 28

29 N( µ, σ ) and unfar ratng follow the mot druptve pole unfar ratng dtruton, gven y: ˆ ˆ 1 1 E [ B ] = E[ R R ] = σ Φ ( ) (20) max, actual, far 2 (1 δ ) Fgure 3 how ome of the value of E[ B ] for varou value of δ and σ n the max pecal cae where ratng range from 0 to 9 8. It ovou that the maxmum a ncreae wth the percentage of unfar ratng and drectly proportonal to the tandard devaton of the far ratng. A efore, we have aumng that a maxmum average a of 5% or le of the ratng range acceptale. Gven thee aumpton, the ue of the ample medan a a the a of calculatng MRE prove to e an acceptale and rout etmate for hgh level of contamnaton and a wde range of tandard devaton. In mot real-lfe context, nearet neghor reputaton etmate are aed on ample wth relatvely mall ze, typcally 5-15 ratng. Gven that the aove theoretcal reult are aymptotc, or large ample reult, t mportant to nvetgate how well they hold n the cae of mall ample ze. To fnd that out, we have performed mulaton experment. Our experment mulated a communty where far ratng are nteger from 0-9 drawn from a dtruton gven y: τ ( R) = max(0, mn(9, z )) where z ~ N ( µ, σ ) (21) The peudocode of the experment lted n Fgure 4. The reult, for ample ze n=5 and n=11 and for everal value of n and σ, are taulated n Fgure 5 and conttute a mall ample realty-check of the aymptotc value of Fgure 3. The correpondence etween theory and practce remarkale for oth teted mall ample ze. 6.3 Ung frequency flterng to elmnate unfar ratng floodng Formula (16) and (20) confrm the ntutve fact that the reputaton a due to unfar ratng ncreae wth the rato δ of unfar rater n a gven ample. In ettng where a eller crtcal attrute can vary over tme (mot realtc ettng), calculaton of reputaton hould e aed on recent ratng only ung tme dcountng or a tmewndow approach. In thoe cae, Secton 5 demontrated that y floodng the ytem wth ratng, a relatvely mall numer of unfar rater can manage to ncreae the rato δ of unfar ratng n any gven tme wndow aove 50% and completely comprome the relalty of the ytem. 8 Gven that we have aumed that all ratng n the nearet neghor et correpond to uer n the ame tate cluter, t expected that the tandard devaton of the far ratng wll e relatvely mall. Therefore, we dd not conder tandard devaton hgher than 10% of the ratng range. 29

30 Th ecton propoe an approach for effectvely mmunzng a reputaton reportng ytem agant unfar ratng floodng. The man dea to flter rater n the nearet neghor et aed on ther ratng umon frequency. Decrpton of frequency flterng Step 1: Frequency flterng depend on etmatng the average frequency of ratng umtted y each uyer for a gven eller. Snce th frequency a tme-varyng quantty (eller can ecome more or le popular wth the paage of tme), t, too need to e etmated ung a tme wndow approach. More pecfcally: 1. Calculate the et F (t) of uyer-pecfc average ratng umon frequence f (t) for eller, for each uyer that ha umtted ratng for durng the ratng umon frequency calculaton tme wndow W =[t-e, t]. More f precely, f (t) = (numer of ratng umtted for y durng W )/E (22) f 2. Set the cutoff frequency f (t) to e equal to the k-th order tattc of the et cutoff F (t) where k = ( 1 -D) n, n the numer of element of F (t) and D a conervatve etmate of the fracton of unfar rater n the total uyer populaton for eller. For example, f we aume that there are no more than 10% unfar rater among all the uyer for eller, then D=0.1. Aumng further that n=100,.e. that the et F (t) contan average ratng umon frequence from 100 uyer, then the cutoff frequency would e equal to the 90-th mallet frequency (the 10-th larget frequency) preent n the et F (t). The wdth E of the ratng umon frequency calculaton tme wndow W hould e f large enough n order to contan at leat a few ratng from all uyer for a gven eller 9. Step 2: Durng the calculaton of a MRE for eller, elmnate all rater n the nearet neghor et for whom f > f. In other word, elmnate all uyer whoe average cutoff ratng umon frequency for eller aove the frequency flterng cutoff frequency. 9 One uggeton to et E( t) = 3/ mn( f ( t 1), for all F ( t 1)),.e. et the wdth of the current tme wndow equal to three tme the larget uyer-pecfc ratng nter-arrval perod n the lat tme wndow. 30

31 Analy of frequency flterng We wll how that frequency flterng provde effectve protecton agant unfar ratng floodng y guaranteeng that the rato of unfar rater n the MRE calculaton et cannot e more than twce a large a the rato of unfar rater n the total uyer populaton. A efore, we wll aume that the entre uyer populaton n, unfar rater are δ n << n and the wdth of the reputaton etmaton tme wndow a relatvely mall W. (o that, each ratng wthn W typcally come from a dfferent rater). Then, after applyng frequency flterng to the nearet neghor et of rater, n a typcal tme wndow we expect to fnd f cutoff W ( 1 δ ) n u ϕ( u) du far ratng, where ϕ(u) the proalty denty functon of far ratng frequence, and at mot W δ n α f unfar ratng, where α the fracton of unfar rater wth cutoff umon frequence elow f. cutoff Therefore, the unfar/far ratng rato n the fnal et would e equal to: unfar ratng δ ' δ α f cutoff δ = = = I f far ratng 1 δ ' 1 δ cutoff 1 δ u ϕ( u) du where I denote the nflaton of the unfar/far ratng rato n the fnal et relatve to t value n the orgnal et. The goal of unfar rater to trategcally dtrute ther ratng frequence aove and elow the cutoff frequency n order to maxmze I. In contrat, the goal of the market degner to degn frequency flterng o a to mnmze I. The cutoff frequency ha een defned a the (1-D) n-th order tattc of the ample of uyer frequence. For relatvely large ample, th converge to the q-th quantle of the far ratng frequence dtruton, where q atfe the equaton: (23) δ ( 1 D ) n = q (1 δ ) n + α δ n q = 1 ( D + α 1) (24) 1 δ From th pont on, the exact analy requre ome aumpton aout the proalty denty functon of far ratng frequence. We tart y aumng a unform dtruton etween F = f /(1 + ) and F = f (1 + ). Let S = F mn 0 max 0 max F. Then, y applyng mn the properte of unform proalty dtruton to equaton (23), we get the followng expreon of the nflaton I of unfar ratng: I = 2 S α f f 2 cutoff F cutoff 2 mn (25a) 31

32 where f cutoff D + ( α 1) δ = F S (25) max 1 δ I I After ome algerac manpulaton we fnd that > 0 and > 0. Th mean that, α D unfar rater wll want to maxmze the fracton of ratng that are le than or equal to f, whle market maker wll want to mnmze D,.e. et D a cloe a pole to an cutoff accurate etmate of the rato of unfar rater n the total populaton. Therefore, at equlrum, α = 1, D = δ and: I 2 ( F = (1 ε) ( F max mn ε S) + F max ε S) δ where ε = (26) 1 δ The aove expreon for the unfar/far ratng nflaton depend on the pread S of far ratng frequence. At the lmtng cae we get: 1 2 lm I = and lm I = (27) S 0 1 ε S 1 ε By uttutng the aove lmtng value of I n equaton (23), we get the fnal formula for the equlrum relatonhp etween δ, the rato of unfar rater n the total populaton of uyer and δ the fnal rato of unfar ratng n the nearet neghor et ung tme wndowng and frequency flterng: δ /( 1 δ ) δ 2δ (28) Equaton (28) how that, no matter how hard unfar rater may try to flood the ytem wth ratng, the preence of frequency flterng guarantee that they cannot nflate ther preence n the fnal MRE calculaton et y more than a factor of 2. Th conclude the proof. One pole crtcm of the frequency flterng approach that t potentally elmnate thoe far uyer who tranact mot frequently wth a gven eller. In fact, n the aence of unfar rater, all rater who would e fltered out aed on ther hgh ratng umon frequency would e far rater. Neverthele, we do not eleve that th property conttute a weakne of the approach. We argue that the et cutomer of a gven eller often receve preferental treatment, whch n a way a form of potve dcrmnaton on ehalf of the eller. Therefore, we eleve that the potental elmnaton of uch rater from the fnal reputaton etmate n fact eneft the contructon of more unaed etmate for the eneft of frt-tme propectve uyer. 32

33 6.4 The effect of ntal reputaton polce n the preence of unfar rater Both the reputaton attack, a well a the mmunzaton technque decred n the prevou ecton, were analyzed n a teady-tate cenaro, where t wa aumed that, at the tme of attack, agent had already accumulated a far reputaton from a numer of far uyer who have had the opportunty to tranact wth t. Th ecton wll conder what happen f we aume that attack commence mmedately upon the appearance of a new eller n the marketplace. Our analy ha ome mportant mplcaton for the optmal ntal reputaton polcy of a communty n the preence of pole unfar rater. Fredman and Renck (1999) have propoed two alternatve ntal reputaton polce: (1) agn mnmum reputaton to all newcomer and let them gradually earn ther real reputaton y offerng good ervce, or (2) requre newcomer to pay entry fee a a way of purchang unt of reputaton from the market-maker. Purchaed reputaton unt are lot f a eller decde to dappear or change t dentty. Fredman and Renck were motly concerned wth the prolem of eller who can ealy dappear from a marketplace after offerng poor ervce and then reappear under a new dentty. They have hown that, n the aence of unfar rater, oth polce are effectve n ncurrng reappearance cot whch dcourage uch eller ehavor. In th ecton, our concern to analyze the effect of each ntal reputaton polcy n the preence of unfar rater. More pecfcally, we wll analyze how each polcy affect the effectvene of medan and frequency flterng f we aume that reputaton attack commence mmedately upon the appearance of a new eller n the marketplace. A we wll how, the agnment of mnmum ntal reputaton le rout than the agnment of average ntal reputaton (wth payment of entry fee f dentte cannot e perfectly authentcated). Polcy 1: Newcomer are agned mnmum ntal reputaton Ballot tuffng When the goal of unfar rater to nflate a eller reputaton, upon appearance of a new eller, colludng uyer wll mmedately egn engagng n (poly fake) tranacton wth t n order to umt very potve ratng. Snce, at the very egnnng, all ratng wll e unfar ratng ( δ = 1), the applcaton of medan flterng and frequency flterng wll have no effect and the MRE wll e hghly nflated. Th wll nduce far uyer to tart tranactng wth a well. The frt few uyer who wll tranact wth wll receve nferor ervce qualty to that mpled y the eller reputaton and wll, therefore, e very unhappy wth the communty reputaton reportng accuracy. When enough far eller have nteracted wth at leat once, then the tuaton converge to the teady-tate cae and the flterng approache dcued aove egn to e effectve. The aove cenaro equvalent to an ntal reputaton polcy, whch agn the maxmum pole reputaton to newcomer for free. From (Fredman and Renck, 1999) we know that th not an optmal polcy. Furthermore, n ettng where eller can 33

34 ealy change dentty, they can dappear from the communty efore ther reputaton converge to t far value, reappear wth a new dentty and tart the aove proce all over agan ad nfntum. Bad-mouthng If ad-mouthng agent mmedately attack a newcomer wth mnmum ntal reputaton, t reputaton wll reman at mnmum level. Th lkely to dcourage far agent from engagng n tranacton wth the new eller. Therefore, the rato of unfar rater tranactng wth th eller lkely to reman hgh, t reputaton wll reman unfarly low and the eller wll mot lkely then oon go out of une. Agan, ecaueδ large, the flterng technque decred n the prevou ecton cannot help n th cenaro. Clearly, th ntal reputaton polcy not atfactory n the preence of unfar rater. Polcy 2: Entry fee and average ntal reputaton ung artfcal ratng We denote the entrance tme of a new eller y t 0. Let u propoe the followng concrete ntal reputaton trategy: 1. All new eller are requred to pay an entry fee All new eller are agned an ntal reputaton R equal to the average reputaton of all eller n the communty at tme t 0. Th done a follow: the ytem generate k artfcal ratng of value R and place them n unformly dtruted random pont wthn the tme wndow [ t 0 -ε, t 0 ]. The numer of artfcal ratng gven y k = f t ) ε, where f t ) the average ratng umon ( 0 ( 0 ( 0 0 frequency for any eller y any uyer: f t ) = Average( f ( t ),all ) where f ( t 0 ) calculated ung (23). The aove ntal reputaton polcy eentally et f ( t ) = f ( t ). Th make frequency 0 0 flterng mmedately effectve and therefore lmt the fracton of unfar ratng that make t nto the fnal calculaton of the MRE. Th, n turn, alo mmedately make medan flterng effectve. The net reult that the MRE of wll quckly converge to t far level, relatvely unaffected y the preence of unfar rater. Furthermore, the extence of an entry fee ncur a cot, whch prevent eller whoe far reputaton elow R from attemptng to quckly dappear and reappear nto the marketplace efore ther MRE reache t far level. 10 To allevate the concern raed y Fredman and Renck aout the advere effect of an entry fee, the fee could e condered a a ond, or ecurty depot, to e refunded to a eller f, upon ext from the communty, t reputaton equal to or greater to t ntally agned level. 34

35 The reult of th ecton that, n the preence of unfar rater, an ntal reputaton polcy whch charge entry fee and agn average ntal reputaton to all newcomer va the generaton of artfcal ratng preferale to a mnmum ntal reputaton entry trategy. 6.5 Iue n communte where uyer dentty not authentcated The effectvene of frequency flterng rele on the aumpton that a gven prncpal entty can only have one uyer agent actng on t ehalf n a gven marketplace. The technque alo vald n tuaton where prncpal entte have multple uyer agent wth authentcated dentfer. In that cae, frequency flterng work f we conder all agent of a gven prncpal entty a a ngle uyer for frequency flterng purpoe. In non-authentcated onlne communte (communte where peudonym are cheap, to ue the term of Fredman and Renck) wth tme-wndowed reputaton etmaton, unfar uyer can tll manage to flood the ytem wth unfar ratng y creatng a large numer of peudonymouly known uyer agent actng on ther ehalf. In that cae the total rato δ of unfar agent relatve to the entre uyer populaton can e made artrarly hgh. If each of the unfar agent take care of umttng unfar ratng for eller wth frequency f f, ecaue δ wll e hgh, even n the preence of cutoff frequency flterng, unfar rater can tll manage to everely contamnate a eller far reputaton. Evdently, further reearch needed n order to develop mmunzaton technque that are effectve n communte where the true dentty of uyer agent cannot e authentcated. In the meantme, the oervaton of th ecton make a trong argument for ung ome reaonaly effectve authentcaton regme for uyer (for example, requrng that all newly regterng uyer upply a vald credt card for authentcaton purpoe) n all onlne communte where trut aed on reputatonal nformaton. 7. Summary and Concluon The ojectve of th paper to contrute to the development of a rgorou dcplne for degnng trut management mechanm n onlne communte. The mportance of uch a dcplne wthout queton: trut a precondton for the contnued extence of any market and cvlzed communty n general. Furthermore, everal properte of onlne nteracton are challengng the accumulated wdom of our communte on how to produce trut and requre the development of new mechanm and ytem. In order to tudy the producton of trut, we thought t neceary to frt precely defne what trut mean. For that reaon, n Secton 2, we have ntroduced a mathematcal framework for defnng trut n the context of a tranacton-orented communty. We have found that the mot central noton n trut producton that of trutworthne, whch we have defned a an agent ujectve aement of the proalty dtruton of another agent future ehavor n the context of a cla of tranacton. 35

36 From a communty perpectve, the producton of trut, therefore, requre the extence of mechanm that help agent accurately ae the trutworthne of other agent. Brck and mortar communte employ a varety of mechanm for th purpoe, ncludng the etalhment of ehavoral norm acked up y nttutonal guarantee, the ue of ndrect cue and the demnaton of pat ehavor data a a way of predctng an agent future ehavor. Of thoe mechanm clae, nttutonal guarantee and relance on ndrect cue are le approprate at th tage of evoluton of onlne communte. On the other hand, the alty of onlne communte to tore and proce complete and accurate nformaton aout all tranacton medated y them, make them deally uted for ung of pat ehavor data (reputatonal nformaton) a the a for uldng trut. We have defned reputaton to e omeone trutworthne, n the pecal cae where t aeed on the a of pat ehavor data. A numer of reearcher and practtoner have already ult the frt generaton of onlne reputaton reportng ytem. However, mot of thee ytem have not een ult on the a of a rgorou framework of trut and trut uldng. In Secton 4 we have urveyed the current tate-of-the-art n reputaton reportng ytem from the perpectve of the framework ntroduced n th paper. We have concluded that, n order to uld relale onlne reputaton reportng ue, a numer of ue need to e atfactorly addreed. Thee ue nclude: the need to uld conenu among the communty on the attrute aout whch reputatonal nformaton eng collected and reported the need to help uer of reputatonal nformaton draw accurate concluon n the cae of attrute, whch are not ojectvely meaurale the need to develop cumulatve meaure of reputaton whch are acked up y theory the need to addre the polty of unfar ratng aout other agent Of the four ue, the frt requre careful ytem degn and communcaton wth communty memer. The econd eng addreed y the et of technque commonly known a collaoratve flterng. Th paper ha focued on the thrd, and partcularly on the fourth ue. We have remarked that a lot of the cumulatve meaure of reputaton propoed y other reearcher are not aed on rgorou defnton of trut and trutworthne. In our model, the producton of trut requre the aement of omeone entre trutworthne proalty dtruton. In the mportant pecal cae where we can aume normally dtruted trutworthne, we have hown that the producton of trut requre etmate of the mean and tandard devaton of that dtruton only. In Secton 5, we have dcued the motvaton for umttng unfar ratng and have analyzed ther effect on ang a reputaton reportng ytem etmate of the mean of omeone trutworthne. We have concluded that evere dtorton are pole, epecally n tuaton where etmaton of reputaton aed on recently umtted ratng only. 36

37 One of the central contruton of th paper the propoal and analy of a numer of novel technque for mmunzng onlne reputaton reportng ytem agant unfar ratng. The propoed mechanm are ummarzed n Fgure 6. The analy of the propoed technque ha reulted n a numer of mportant gudelne for the degn of current and future electronc marketplace: It mportant to e ale to authentcate the dentty of ratng provder. Unauthentcated communte are vulnerale to unfar ratng floodng attack. Concealng the (authentcated) dentty of uyer and eller from one another can prevent negatve unfar ratng and dcrmnatory ehavor. Electronc marketplace and B2B hu can conder addng th functon nto the et of ervce they provde to ther memer. The ntal reputaton polcy for new eller crucal n the preence of unfar rater. A mnmum ntal reputaton polcy make newcomer vulnerale to ad-mouthng attack. On the other hand a polcy, whch nvolve entry fee (or ecurty depot) and an average ntal reputaton work well n conjuncton wth the propoed mmunzaton technque. Th paper ha mply cratched the urface of an mportant et of prolem. The calculaton of rout etmate of reputaton tandard devaton and the development of mmunzaton technque that avod unfar ratng floodng n non-authentcated communte are jut two of the ue left open y th paper. It our hope that the framework and technque propoed y th work wll provde a ueful a that wll tmulate further reearch n the mportant and exctng area of onlne trut management ytem. 37

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42 Percentage of Far Mean Reputaton Etmate (R mn =0, R max =9) unfar ratng % % % % % Fgure 1. Some value of maxmum MRE a when MRE are aed on the mean of the ratng et. Shaded cell ndcate unacceptaly hgh ae. Anonymty Regme Clae of pole unfar ehavor Buyer dentty known to eller Seller dentty known to uyer Bad-mouthng pole Negatve dcrmnaton pole Ballot-tuffng pole Potve dcrmnaton pole Ye Ye!!!! Ye No!!! No Ye!!! No No!! Fgure 2. Effect of controlled anonymty n preventng certan clae of unfar ehavor. 42

43 Percentage of Standard Devaton of Far Ratng unfar ratng % % % % % Fgure 3. Aymptotc upper ound of average reputaton a when MRE are aed on the medan of the ratng et (ratng range from 0-9). Shaded cell ndcate unacceptaly hgh ae. To calculate the maxmum average reputaton a achevale y n unfar rater n a ample of u ze n = n + n, where far ratng have tandard devaton σ : f u 1. Calculate the et U of all pole unfar ratng tratege. U the et of all dfferent way n whch n nteger value can e dtruted etween 0 and 9. u 2. For each unfar ratng trategy U U a. For each pole µ =0,1,,9 generate 100,000 random et F of n far j f ratng drawn from (21). Calculate the reputaton a of the total ratng et U F aed on the j ample medan approach: B = Medan( U F ) Medan( F ) j j c. Calculate the average reputaton a B = Average( B ) achevale y unfar ratng dtruton U over all 100,000 random et j j F of far ratng. j 3. Calculate the maxmum average reputaton a B = Max( B ) over all pole max unfar ratng tratege U U Fgure 4. Peudocode of the expermental procedure ued to tet the mall ample medan-aed maxmum average MRE a ehavor. 43

44 n=5 Aymptotc Numer and percentage of Standard Devaton of Far Ratng unfar ratng % % Expermental Numer and percentage of Standard Devaton of Far Ratng unfar ratng % % n=11 Aymptotc Numer and percentage of Standard Devaton of Far Ratng unfar ratng Expermental 1 9% % % % % Numer and percentage of Standard Devaton of Far Ratng unfar ratng % % % % % Fgure 5. Comparon etween aymptotc and expermentally derved maxmum average medan-aed MRE a for ratng ample ze n=5 and n=11. Shaded cell ndcate unacceptaly hgh ae. 44

45 Technque Decrpton Effect Prerequte Controlled anonymty Medan flterng Frequency flterng Market-maker conceal the true dentte of uyer and eller from one another Calculaton of mean reputaton etmate ung the medan of the ratng et Ignore rater whoe ratng umon frequency for a gven eller gnfcantly aove average Prevent ad-mouthng and negatve dcrmnaton Reult n rout etmaton n the preence of hgh percentage of unfar ratng Elmnate rater who attempt to flood the ytem wth unfar ratng; mantan the fnal rato of unfar rater at low level Alty to practcally mplement wth reaonale cot Rato of unfar ratng le than 50% Alty to authentcate the true dentty of onlne rater Fgure 6. Summary of propoed mmunzaton technque. 45