StarIn: An Approach to Predict the Popularity of GitHub Repository
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Publisher
Springer Singapore
Link
http://link.springer.com/content/pdf/10.1007/978-981-15-7984-4_20
Reference21 articles.
1. Bissyande, T.F., Thung, F., Lo, D., Jiang, L., Reveillere, L.: Popularity, interoperability, and impact of programming languages in 100,000 open source projects. In: 2013 IEEE 37th Annual Computer Software and Applications Conference, pp. 303–312. IEEE (2013)
2. Blincoe, K., Sheoran, J., Goggins, S., Petakovic, E., Damian, D.: Understanding the popular users: following, affiliation influence and leadership on GitHub. Inf. Softw. Technol. 70(1), 30–39 (2016)
3. Borges, H., Hora, A., Valente, M.T.: Predicting the popularity of GitHub repositories. In: Proceedings of the 12th International Conference on Predictive Models and Data Analytics in Software Engineering, p. 9. ACM (2016)
4. Borges, H., Hora, A., Valente, M.T.: Understanding the factors that impact the popularity of GitHub repositories. In: 2016 IEEE International Conference on Software Maintenance and Evolution (ICSME), pp. 334–344. IEEE (2016)
5. Borges, H., Valente, M.T.: What’s in a GitHub star? Understanding repository starring practices in a social coding platform. J. Syst. Softw. 146(10), 112–129 (2018)
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