Analyzing Programmer Psychological Traits Using Code and Sentiment Analysis

Martinez-Gil, Jorge Analyzing Programmer Psychological Traits Using Code and Sentiment Analysis., 2024 [Preprint]

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English abstract

Our research introduces a novel framework for analyzing programmer psychological traits by combining automated code analysis and sentiment assessment. Our contribution is in the form of a framework that can identify key behavioral traits such as attention to detail, collaboration orientation, and problem-solving tendencies. Unlike traditional survey-based methods, this approach offers objectivity and applicability across diverse programming contexts. Experimental results demonstrate its potential to contribute to software engineering, developer productivity research, and cognitive profiling of programmers.

Item type: Preprint
Keywords: Software Engineering, Code Analysis, Sentiment Analysis, Developer Traits, Natural Language Processing
Subjects: G. Industry, profession and education. > GB. Software industry.
L. Information technology and library technology > LK. Software methodologies and engineering.
Depositing user: Dr Jorge Martinez-Gil
Date deposited: 21 Jan 2025 07:50
Last modified: 21 Jan 2025 07:50
URI: http://hdl.handle.net/10760/46253

References

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[8] Martinez-Gil, J. (2024). Augmenting the interpretability of graphcodebert for code similarity tasks. arXiv preprint arXiv:2410.05275

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[10] Martinez-Gil, J. (2024). Source code clone detection using unsupervised similarity measures. In P. Bludau, R. Ramler, D. Winkler, & J. Bergsmann (Eds.), Software Quality as a Foundation for Security - 16th International Conference on Software Quality, SWQD 2024, Vienna, Austria, April 23-25, 2024, Proceedings (pp. 21–37). Springer volume 505 of Lecture Notes in Business Information Processing.

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