Exploring Sentiment Analysis to understand Software Crowdsourcing Challenges
Resumo
Companies are increasingly using crowdsourcing to accomplish specific software development tasks. This paper describes the initial results from a exploratory study using sentiment analysis in a software crowdsourcing context from a crowd perspective. We classify the polarity of the messages exchanged in challenge forums. Although there are not applications for sentiment analysis of messages in the software crowdsourcing context, our ultimate goal is to understand how good or bad the crowd is talking about and explore if negative messages can be factors that influence the decrease in motivation, especially among the crowd and if positive sentiments can help to encourage contribution to challenges.
Referências
Ågerfalk, P. J., Fitzgerald, B., and Stol, K. J. (2015). Software Sourcing in the Age of Open: Leveraging the Unknown Workforce. Springer, 71p.
Alamsyah, A., Nuruz, F. (2017). “Measuring Public Sentiment Towards Service Level in Online Forum using Naïve Bayes Classifier Method and Word Cloud”. In CRSForMIND International Conference and Workshop 2017.
Araujo, M.; Reis, J.; Pereira, A.; Benevenuto, F. “An Evaluation of Machine Translation for Multilingual Sentence-level Sentiment Analysis”. In: ACM Symposium on Applied Computing (SAC), 2016, ACM Press, Pisa, Italy.
Bhatia, S., Biyani, P., &Mitra, P. (2012). “Classifying user messages for managing web forum data”. In Fifteenth International Workshop on the Web and Databases, WebDB pp. pp.13-18. Scottsdale, AZ: ACM.
Dubey, A.; Abhinav, K.; Taneja, S.; Virdi, G.; Dwarakanath, A.; Kass, A.; Kuriakose, M.S. Dynamics of software development crowdsourcing. In: ICGSE, 2016, pp. 49-58.
Esuli, A., & Sebastiani, F. (2006). SENTIWORDNET: A Publicly Available Lexical Resource for Opinion Mining. LREC.
Gray, L. Suri, S., Ali, S., Kulkarni, D. (2016) “The crowd is a collaborative network”. In: Proceedings of the 19th CSCW Conference. ACM. p. 134-147.
Karim, M.R.; Saremi, R.; Ruhe, G. “Who should take this task? Dynamic decision support for crowd workers”. In: ESEM ACM/IEEE, 2016, p. 8.
LaToza, T.D.; Chen, M.; Jiang, L.; Zhao, M.; Van Der Hoek, A. “Borrowing from the crowd: A study of recombination in software design competitions”. In: 37th International Conference on Software Engineering, v1, 2015, pp. 551-562.
Li, N., and Wu, D.D. (2010). “Using text mining and sentiment analysis for online forums hotspot detection and forecast”. Decision Support Systems, 48, 354-368.
Machado, L. S.; Zanatta, A. L.; Marczak, S.; Prikladnicki, R. “The Good, the Bad and the Ugly: An Onboard Journey in Software Crowdsourcing Competitive Model”. In: 4th International Workshop on CrowdSourcing in Software Engineering (CSI-SE). Collocated with the 39th ICSE, 2017, pp. 2-8.
Messias, J; Diniz, João P.; Soares, E.; Ferreira, M.; Araújo, M.; Bastos, L.; Miranda, M.; Benevenuto, F. (2016). “Towards sentiment analysis for mobile devices”. In: IEEE. Advances in Social Networks Analysis and Mining, 2016. p. 1390–1391.
Nag, S.; Heffan, I.; Saenz-Otero, A.; Lydon, M. “SPHERES Zero Robotics software development: Lessons on crowdsourcing and collaborative competition”. In: Aerospace Conference, 2012 IEEE, pp. 1-17.
Nirmala, K., and Bhaskarn,V., (2012). “Online Forums Hotspot Prediction Based on Sentiment Analysis”. Journal of Computer Science.
Peng, X.; Ali Babar, M.; Ebert, C. “Collaborative Software Development Platforms for Crowdsourcing”. IEEE Software, v. 31, n. 2, 2014, pp. p. 30–36.
Stol, K.-J.; Fitzgerald, B. “Two’s company, three’s a crowd: a case study of crowdsourcing software development”. In: ICSE, ACM Press, 2014, p.p.187.
Tausczik, Y.; Wang. P. “To Share, or Not to Share? Community-Level Collaboration in Open Innovation Contests”. CSCW, 2017.
Yang, Y.; Saremi, R. “Award vs. worker behaviors in competitive crowdsourcing tasks”. In: ESEM, IEEE, 2015, pp. 1-10.
Alamsyah, A., Nuruz, F. (2017). “Measuring Public Sentiment Towards Service Level in Online Forum using Naïve Bayes Classifier Method and Word Cloud”. In CRSForMIND International Conference and Workshop 2017.
Araujo, M.; Reis, J.; Pereira, A.; Benevenuto, F. “An Evaluation of Machine Translation for Multilingual Sentence-level Sentiment Analysis”. In: ACM Symposium on Applied Computing (SAC), 2016, ACM Press, Pisa, Italy.
Bhatia, S., Biyani, P., &Mitra, P. (2012). “Classifying user messages for managing web forum data”. In Fifteenth International Workshop on the Web and Databases, WebDB pp. pp.13-18. Scottsdale, AZ: ACM.
Dubey, A.; Abhinav, K.; Taneja, S.; Virdi, G.; Dwarakanath, A.; Kass, A.; Kuriakose, M.S. Dynamics of software development crowdsourcing. In: ICGSE, 2016, pp. 49-58.
Esuli, A., & Sebastiani, F. (2006). SENTIWORDNET: A Publicly Available Lexical Resource for Opinion Mining. LREC.
Gray, L. Suri, S., Ali, S., Kulkarni, D. (2016) “The crowd is a collaborative network”. In: Proceedings of the 19th CSCW Conference. ACM. p. 134-147.
Karim, M.R.; Saremi, R.; Ruhe, G. “Who should take this task? Dynamic decision support for crowd workers”. In: ESEM ACM/IEEE, 2016, p. 8.
LaToza, T.D.; Chen, M.; Jiang, L.; Zhao, M.; Van Der Hoek, A. “Borrowing from the crowd: A study of recombination in software design competitions”. In: 37th International Conference on Software Engineering, v1, 2015, pp. 551-562.
Li, N., and Wu, D.D. (2010). “Using text mining and sentiment analysis for online forums hotspot detection and forecast”. Decision Support Systems, 48, 354-368.
Machado, L. S.; Zanatta, A. L.; Marczak, S.; Prikladnicki, R. “The Good, the Bad and the Ugly: An Onboard Journey in Software Crowdsourcing Competitive Model”. In: 4th International Workshop on CrowdSourcing in Software Engineering (CSI-SE). Collocated with the 39th ICSE, 2017, pp. 2-8.
Messias, J; Diniz, João P.; Soares, E.; Ferreira, M.; Araújo, M.; Bastos, L.; Miranda, M.; Benevenuto, F. (2016). “Towards sentiment analysis for mobile devices”. In: IEEE. Advances in Social Networks Analysis and Mining, 2016. p. 1390–1391.
Nag, S.; Heffan, I.; Saenz-Otero, A.; Lydon, M. “SPHERES Zero Robotics software development: Lessons on crowdsourcing and collaborative competition”. In: Aerospace Conference, 2012 IEEE, pp. 1-17.
Nirmala, K., and Bhaskarn,V., (2012). “Online Forums Hotspot Prediction Based on Sentiment Analysis”. Journal of Computer Science.
Peng, X.; Ali Babar, M.; Ebert, C. “Collaborative Software Development Platforms for Crowdsourcing”. IEEE Software, v. 31, n. 2, 2014, pp. p. 30–36.
Stol, K.-J.; Fitzgerald, B. “Two’s company, three’s a crowd: a case study of crowdsourcing software development”. In: ICSE, ACM Press, 2014, p.p.187.
Tausczik, Y.; Wang. P. “To Share, or Not to Share? Community-Level Collaboration in Open Innovation Contests”. CSCW, 2017.
Yang, Y.; Saremi, R. “Award vs. worker behaviors in competitive crowdsourcing tasks”. In: ESEM, IEEE, 2015, pp. 1-10.
Publicado
03/10/2019
Como Citar
M. MELO, Ricardo Rodrigo; S. MACHADO, Leticia; R.B. DE SOUZA, Cleidson.
Exploring Sentiment Analysis to understand Software Crowdsourcing Challenges. In: PESQUISAS EM ANDAMENTO - SIMPÓSIO BRASILEIRO DE SISTEMAS COLABORATIVOS (SBSC), 15. , 2019, Rio de Janeiro.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2019
.
p. 75-80.
