TY - JOUR
T1 - Characterizing the hyperspecialists in the context of crowdsourcing software development
AU - de Neira, Anderson Bergamini
AU - Steinmacher, Igor
AU - Wiese, Igor Scaliante
N1 - Publisher Copyright:
© 2018, The Author(s).
PY - 2018/12/1
Y1 - 2018/12/1
N2 - 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.
AB - 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.
KW - Crowdsourcing
KW - Hyperspecialization
KW - Topcoder
UR - http://www.scopus.com/inward/record.url?scp=85059042364&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85059042364&partnerID=8YFLogxK
U2 - 10.1186/s13173-018-0082-2
DO - 10.1186/s13173-018-0082-2
M3 - Article
AN - SCOPUS:85059042364
SN - 0104-6500
VL - 24
JO - Journal of the Brazilian Computer Society
JF - Journal of the Brazilian Computer Society
IS - 1
M1 - 17
ER -