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Description A Django-based implementation of the mini-IPIP test for measuring the Big Five personality. Implementation is based on the following paper: Donnellan MB, Oswald FL, Baird BM, Lucas RE(2006). The mini-IPIP scales: tiny-yet-effective measures of the Big Five factors of personality. DOI: 10.1037/1040-3590.18.2.192 Instructions Along with the source code, the software is distributed as a lightweight Docker container. After installing Docker to your machine, to build and run the Docker image, download and uncompress the zip file. Then, from the command line, execute: $ docker-compose up To stop, either kill the process or execute $ docker-compose down For further configuration instructions and alternative execution instructions, please refer to the documentation available on GitHub.
{"references": ["F. Calefato, G. Iaffaldano, F. Lanubile, B. Vasilescu (2018). \"On Developers' Personality in Large-scale Distributed Projects: The Case of the Apache Ecosystem.\" In Proc. Int'l Conf. on Global Software Engineering (ICGSE'18), Gothenburg, Sweden, May 28-29, 2018, DOI:10.1145/3196369.3196372"]}
big five, big 5, ffm, five-factor model, personality, psychometric
big five, big 5, ffm, five-factor model, personality, psychometric
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
views | 21 | |
downloads | 2 |