The Strength of Social Coding Collaboration on GitHub
Resumo
Social coding is an approach of software development that enables cooperation among developers. Specially, GitHub can be modeled as a social coding network and its study allows the discovery of relevant patterns, e.g., the collaborations strength. Finding such patterns may help to improve the recommendation of developers and the evaluation of team formation. Here, our goal is to analyze the correlation between network properties and such strength.
Palavras-chave:
Social coding network, Network properties, Relation strength
Referências
Barabási, A. and Albert, R. (1999). Emergence of scaling in random networks. Science, 286(5439):509–512.
Bartusiak, R. et al. (2016). Cooperation prediction in github developers network with restricted boltzmann machine. In ACIIDS, pages 96–107.
Brandão, M., Moro, M. M., and Almeida, J. M. (2013). Análise de fatores impactantes na recomendação de colaborações acadêmicas utilizando projeto fatorial. In SBBD Short Papers, pages 1–6.
Brandão, M. A., Diniz, M. A., and Moro, M. M. (2016). Using topological properties to measure the strength of co-authorship ties. In BRASNAM/CSBC, pages 199–210.
Brandão, M. A., Moro, M. M., and Almeida, J. M. (2014). Experimental evaluation of academic collaboration recommendation using factorial design. JIDM, 5(1):52.
Casalnuovo, C., Vasilescu, B., Devanbu, P., and Filkov, V. (2015). Developer onboarding in github: The role of prior social links and language experience. In ESEC/FSE, pages 817–828.
Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences. Lawrence Erlbaum Associates, second edition.
Dabbish, L., Stuart, C., Tsay, J., and Herbsleb, J. (2012). Social coding in github: transparency and collaboration in an open software repository. In CSCW, pages 1277–1286.
de Oliveira, D. M. et al. (2015). Uma estratégia não supervisionada para previsão de eventos usando redes sociais. In SBBD, pages 137–148.
Easley, D. and Kleinberg, J. (2010). Networks, crowds, and markets: Reasoning about a highly connected world. Cambridge University Press.
Gousios, G. (2013). The ghtorrent dataset and tool suite. In MSR, pages 233–236.
Newman, M. E. (2001). The structure of scientific collaboration networks. NAS, 98(2):404–409.
Silva, T. H. P., Rocha, L. M. A., Silva, A. P. C., and Moro, M. M. (2016). 3c-index: Research contribution across communities as an influence indicator. JIDM, 6(3):192–205.
Tsay, J., Dabbishand, L., and Herbsleb, J. (2014). Influence of social and technical factors for evaluating contribution in github. In ICSE, pages 356–366.
Bartusiak, R. et al. (2016). Cooperation prediction in github developers network with restricted boltzmann machine. In ACIIDS, pages 96–107.
Brandão, M., Moro, M. M., and Almeida, J. M. (2013). Análise de fatores impactantes na recomendação de colaborações acadêmicas utilizando projeto fatorial. In SBBD Short Papers, pages 1–6.
Brandão, M. A., Diniz, M. A., and Moro, M. M. (2016). Using topological properties to measure the strength of co-authorship ties. In BRASNAM/CSBC, pages 199–210.
Brandão, M. A., Moro, M. M., and Almeida, J. M. (2014). Experimental evaluation of academic collaboration recommendation using factorial design. JIDM, 5(1):52.
Casalnuovo, C., Vasilescu, B., Devanbu, P., and Filkov, V. (2015). Developer onboarding in github: The role of prior social links and language experience. In ESEC/FSE, pages 817–828.
Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences. Lawrence Erlbaum Associates, second edition.
Dabbish, L., Stuart, C., Tsay, J., and Herbsleb, J. (2012). Social coding in github: transparency and collaboration in an open software repository. In CSCW, pages 1277–1286.
de Oliveira, D. M. et al. (2015). Uma estratégia não supervisionada para previsão de eventos usando redes sociais. In SBBD, pages 137–148.
Easley, D. and Kleinberg, J. (2010). Networks, crowds, and markets: Reasoning about a highly connected world. Cambridge University Press.
Gousios, G. (2013). The ghtorrent dataset and tool suite. In MSR, pages 233–236.
Newman, M. E. (2001). The structure of scientific collaboration networks. NAS, 98(2):404–409.
Silva, T. H. P., Rocha, L. M. A., Silva, A. P. C., and Moro, M. M. (2016). 3c-index: Research contribution across communities as an influence indicator. JIDM, 6(3):192–205.
Tsay, J., Dabbishand, L., and Herbsleb, J. (2014). Influence of social and technical factors for evaluating contribution in github. In ICSE, pages 356–366.
Publicado
04/10/2016
Como Citar
ALVES, Gabriela B.; BRANDÃO, Michele A.; SANTANA, Diogo M.; DA SILVA, Ana Paula C.; MORO, Mirella M..
The Strength of Social Coding Collaboration on GitHub. In: SIMPÓSIO BRASILEIRO DE BANCO DE DADOS (SBBD), 31. , 2016, Salvador/BA.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2016
.
p. 247-252.
ISSN 2763-8979.
DOI: https://doi.org/10.5753/sbbd.2016.24336.
