人气
分类
编码(社会科学)
计算机科学
预测能力
数据科学
预测编码
质量(理念)
知识管理
营销
互联网隐私
心理学
行为经济学
人工智能
博弈论
定性研究
业务
机器学习
人际交往
跟随权
扎根理论
社会化媒体
前景理论
作者
Praharshita Krishna,Adrija Majumdar,Indranil Bose
标识
DOI:10.1177/10591478251405119
摘要
A developer's popularity plays a crucial role in their success within open source software (OSS) communities and their access to sponsorship opportunities. This study seeks to answer the question: which signals have the most predictive power for popularity and sponsorship volume on social coding platforms? Using algorithm-supported abductive theory generation supplemented by qualitative insights from observations and interviews, we arrive at a theory of peer evaluation in OSS communities. We examine a large number of signals and categorize them. The two categories are signaling via self-disclosure through profile signals and signaling via contribution quantity and quality through behavioral signals. The large amount of data available to us allows us to use machine learning techniques to arrive at top-ranking predictors within each category. We generate our theory by finding robust patterns and test our theory using a hold-out sample. Our findings indicate that easily observable credibility-enhancing and approachability-related developer profile signals hold greater predictive importance in shaping popularity. However, harder to observe and more complex behavioral signals show greater predictive importance for sponsorship volume. These results signify that OSS social coding platforms are not meritocratic, as developer self-disclosure significantly influences popularity. In contrast, sponsorship decisions, due to their high cost and irreversibility, depend on within-platform contribution-related signals. This research contributes to a deeper understanding of popularity and sponsorship within peer-to-peer followership networks in OSS communities. Through our research, platforms are better informed about the predictors of popularity and sponsorship and can introduce measures to enhance the meritocratic nature of these communities. Developers who seek influence and sponsorship on the platform can be more strategic about information disclosure and their contributions.
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