Companies around the world use crowdsourcing platforms to complete simple tasks, collect product ideas, and launch advertising campaigns. Recently, crowdsourcing has also been used for software development to run tests, fix small defects, or perform small coding tasks. Among the pillars upholding the crowdsourcing business model are the platform participants, as they are responsible for accomplishing the requested tasks. Since successful crowdsourcing heavily relies on attracting and retaining participants, it is essential to understand how they behave. This exploratory study aims to understand a specific contributor profile: hyperspecialists. We analyzed developers’ participation on challenges in two ways. First, we analyzed the type of challenge that 664 Topcoder platform developers participated in during the first 18 months of their participation. Second, we focused on the profile of users who had more collaborations in the development challenges. After quantitative analysis, we observed that, in general, users who do not stop participating have behavioral traits that indicate hyper-specialization, since they participate in the majority of the same types of challenge. An interesting, though troubling, finding was the high dropout rate on the platform: 66% of participants discontinued their participation during the study period. The results also showed that hyperspecialization can be observed in terms of technologies required in the development challenges. We found that 60% of the 2,086 developers analyzed participated in at least 75% of challenges that required the same technology. We found hyperspecialists and non-specialists significantly differ in behavior and characteristics, including hyperspecialists’ lower winning rate when compared to non-specialists.

中文翻译：

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在众包软件开发的背景下表征超级专家

世界各地的公司都使用众包平台来完成简单的任务、收集产品创意和发起广告活动。最近，众包也被用于软件开发以运行测试、修复小缺陷或执行小的编码任务。支持众包商业模式的支柱之一是平台参与者，因为他们负责完成要求的任务。由于成功的众包很大程度上依赖于吸引和留住参与者，因此了解他们的行为至关重要。这项探索性研究旨在了解特定的贡献者概况：超级专家。我们从两个方面分析了开发者参与挑战的情况。第一的，我们分析了 664 名 Topcoder 平台开发人员在参与的前 18 个月内参与的挑战类型。其次，我们关注在开发挑战中合作较多的用户的资料。经过定量分析，我们观察到，一般来说，没有停止参与的用户具有表明超专业化的行为特征，因为他们参与了大多数相同类型的挑战。一个有趣但令人不安的发现是平台上的高辍学率：66% 的参与者在研究期间停止了参与。结果还表明，在发展挑战所需的技术方面可以观察到超专业化。我们发现 60% 的 2, 分析的 086 名开发人员参与了至少 75% 需要相同技术的挑战。我们发现超级专家和非专家在行为和特征上有显着差异，包括与非专家相比，超级专家的获胜率较低。