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Believe it when you see it: Dyadic embeddedness and reputation effects on trust in cryptomarkets for illegal drugs
Social Networks ( IF 4.144 ) Pub Date : 2020-07-14 , DOI: 10.1016/j.socnet.2020.07.003
Lukas Norbutas , Stijn Ruiter , Rense Corten

Large-scale online marketplace data have been repeatedly used to test sociological theories on trust between strangers. Most studies focus on sellers’ aggregate reputation scores, rather than on buyers’ individual decisions to trust. Theoretical predictions on how repeated exchanges affect trust within dyads and how buyers weigh individual experience against reputation feedback from other actors have not been tested directly in detail. What do buyers do when they are warned not to trust someone they have trusted many times before? We analyze reputation effects on trust at the dyadic and network levels using data from an illegal online drug marketplace. We find that buyers’ trust decisions are primarily explained by dyadic embeddedness - cooperative sellers get awarded by repeated exchanges. Although buyers take third-party information into account, this effect is weaker and more important for first-time buyers. Buyers tend to choose market exit instead of retaliation against sellers after negative experiences.



中文翻译:

当您看到它时,请相信:二进位嵌入和声誉对非法药物对加密市场的信任的影响

大规模的在线市场数据已被反复用来测试关于陌生人之间信任的社会学理论。大多数研究着眼于卖方的整体声誉得分,而不是买方对信任的个人决定。关于重复交流如何影响二分体内部信任以及购买者如何权衡个人经验与其他参与者的声誉反馈的理论预测尚未直接进行详细测试。当警告购买者不要信任他们曾经多次信任的人时,他们会怎么做?我们使用来自非法在线毒品市场的数据来分析声誉对信任和信任关系的影响。我们发现买家的信任决定主要是由二元嵌入来解释的-合作卖家通过反复交流而获得奖励。尽管买家考虑了第三方信息,对于初次购买者而言,这种影响较弱,并且更为重要。负面经历之后,买方倾向于选择市场退出而不是对卖方进行报复。

更新日期:2020-07-14
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