Characterizing the hyperspecialists in the context of crowdsourcing software development View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2018-12

AUTHORS

Anderson Bergamini de Neira, Igor Steinmacher, Igor Scaliante Wiese

ABSTRACT

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. More... »

PAGES

17

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s13173-018-0082-2

DOI

http://dx.doi.org/10.1186/s13173-018-0082-2

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1110815817


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