Abstract
The emergence of data mining has helped improve our understanding of social contagion in networks. The magnitude of contagion in networks such as Facebook and Twitter has been studied in detail. Study of social contagion in software development networks can provide interesting findings in order to increase return on investment and improve quality of software. For example, developers could be incentivised and the time to start an open-source projects optimized by analyzing social contagion in online repositories. In this study, open-source repositories’ data was analyzed and it was observed that highly followed developers tend to attract more contributors to a project. Also, the number of commits was aggregated on a yearly basis to provide insight into the question of the best time to start a project. GitHub online repository data was collected since its inception until 2014. The number of commits in the online repository was found to follow the “power law”. By considering only large projects, a correlation between the number of followers a user has and the contagion rate of their commits was observed. Understanding these questions and social contagion can help software companies to leverage on the open-source community and improve their own internal social networks.
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Shoroye, Z., Yaqub, W., Mohammed, A.A., Aung, Z., Svetinovic, D. (2015). Exploring Social Contagion in Open-Source Communities by Mining Software Repositories. In: Arik, S., Huang, T., Lai, W., Liu, Q. (eds) Neural Information Processing. ICONIP 2015. Lecture Notes in Computer Science(), vol 9492. Springer, Cham. https://doi.org/10.1007/978-3-319-26561-2_15
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DOI: https://doi.org/10.1007/978-3-319-26561-2_15
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