Project risk analysis using text data mining of comments in project management system JIRA

Authors

  • Anna A. Liednikova Educational and Scientific Complex “Institute for Applied System Analysis” of the National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Kyiv, Ukraine
  • Danylo V. Shypik Educational and Scientific Complex “Institute for Applied System Analysis” of the National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Kyiv, Ukraine https://orcid.org/0000-0002-7667-4701
  • Petro I. Bidyuk Educational and Scientific Complex “Institute for Applied System Analysis” of the National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Kyiv, Ukraine https://orcid.org/0000-0002-7421-3565

DOI:

https://doi.org/10.20535/SRIT.2308-8893.2020.2.09

Keywords:

project risk analysis, probabilistic latent semantic analysis, latent Dirichlet allocation model, natural language processing, sentiment analysis

Abstract

During the study, a methodology was developed, and a software product was developed for project risk assessment based on developer communications, as well as the results of the program work on the data of the real project CASSANDRA of Apache Software Foundation. The methodology is implemented based on already well-known algorithms for determining the emotional components in the text of the VAD and matrix methods for project risk analysis using their developments that allow combining these different approaches. Obtaining the names of potential risks is performed using the model of constructing the LDA themes. The results allow us to determine the importance of the task by the communications and rank them in the middle of the project by the importance and need for additional attention that will allow project managers to understand and solve problems more quickly in the context of the product.

Author Biographies

Anna A. Liednikova, Educational and Scientific Complex “Institute for Applied System Analysis” of the National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Kyiv

Anna Liednikova,

a graduate student at Educational and Scientific Complex “Institute for Applied System Analysis” of the National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Kyiv, Ukraine.

Danylo V. Shypik, Educational and Scientific Complex “Institute for Applied System Analysis” of the National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Kyiv

Danylo Shypik,

a Ph.D. student at Educational and Scientific Complex “Institute for Applied System Analysis” of the National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Kyiv, Ukraine.

Petro I. Bidyuk, Educational and Scientific Complex “Institute for Applied System Analysis” of the National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Kyiv

Petro Bidyuk,

Dr. of Eng. Sci., a professor at the Department of the Mathematical Methods of System Analysis of Educational and Scientific Complex "Institute for Applied System Analysis" of the National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Kyiv, Ukraine.

References

PMI. Success Rates Rise 2017 9th Global Project Management Survey. Pulse of the Profession, 2017. Available: https://www.pmi.org//media/pmi/documents/public/ pdf/learning/thought-leadership/pulse/pulse-of-the-profession2017.pdf.

A. Murgia, P. Tourani, B. Adams, and M. Ortu, Do Developers Feel Emotions? An Exploratory Analysis of Emotions in Software Artifacts, 2014. Available: https://alessandromurgia.files.wordpress.com/2014/03/emotionanalysis.pdf.

The Top 20 Most Popular Project Management Software, 2018. Available: https://www.capterra.com/project-managementsoftware /#infographic.

System Dashboard. Available: https://issues.apache.org/jira/secure/ Dashboard.jspa.

Teamwork. Right tools, right people, and right practices. Available: https://www.atlassian.com/teamwork.

R.Colomo-Palacios, C. Casado-Lumbreras, P. Soto-Acosta, and A. García-Crespo, Using the Affect Grid to Measure Emotions in Software Requirements Engineering, 2011. Available: http://www.jucs.org/jucs_17_9/using_the_affect_grid/ jucs_17_09_ 1281_1298_colomo.pdf.

L. Jun, Human factors in agile software development, 2015. Available: https://arxiv.org/ftp/arxiv/papers/1502/1502.04170.pdf.

M. Ortu et al., The JIRA Repository Dataset: Understanding Social Aspects of Software Development, 2015. Available: http://mcis.polymtl.ca/publications/2015/ ortu_promise.pdf.

R. Jongeling, P. Sarkar, S. Datta, and A. Serebrenik, On negative results when using sentiment analysis tools for software engineering research, 2017. Available: https://doi.org/10.1007/s10664-016-9493-x.

M. Mäntylä et al., Mining Valence, Arousal, and Dominance – Possibilities for Detecting Burnout and Productivity?, 2016. Available: https://arxiv.org/pdf/1603. 04287.pdf.

M. Ortu et al., “Arsonists or Firefighters? Affectiveness in Agile Software Development”, Lecture Notes in Business Information Processing, issue 251, 2016.

A.B. Warriner, V. Kuperman, and M. Brysbaert, Norms of valence, arousal, and dominance for 13,915 English lemmas. Behavior Research Methods, 2013. Available: https://doi.org/10.37.

T. Hofmann, Probabilistic latent semantic indexing, 1999. Available: https://www. researchgate.net/publication/2941307_Probabilistic_Latent_Semantic_Indexing.

D. Blei, A. Ng, and M. Jordan, Latent Dirichlet Allocation, 2003. Available: http://www.jmlr.org/papers/volume3/blei03a/blei03a.pdf.

E. Guzman, Visualizing emotions in software development projects, 2013. Available: https://doi.org/10.1109/VISSOFT.2013.6650529.

D. Hoffman, M. Blei, and B. Francis, Online Learning for Latent Dirichlet Allocation, 2010. Available: https://www.di.ens.fr/~fbach/mdhnips 2010.pdf.

M. Röder, A. Both, and A. Hinneburg, Exploring the Space of Topic Coherence Measures, 2015. Available: https://svn.aksw.org/papers/2015/WSDM_Topic_ Evaluation/public.pdf.

D. Mimno et al., Optimizing semantic coherence in topic models, 2011. Available: http://dirichlet.net/pdf/mimno11 optimizing.pdf.

jira-social-repository. Available: https://github.com/marcoortu/jira-social-repository.

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Published

2020-09-25

Issue

No. 2 (2020)

Section

Theoretical and applied problems of intelligent systems for decision making support

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