Supplementary data for the Master Thesis: Inferring Personality from GitHub Communication Data: Promises & Perils
Datacite citation style:
van Mil, Frenk (2020): Supplementary data for the Master Thesis: Inferring Personality from GitHub Communication Data: Promises & Perils. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/uuid:6b648676-26f4-4eb1-89dc-050810909b3bOther citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
This dataset contains the personality scores of participants of the study "Inferring Personality from GitHubCommunication Data:Promises & Perils". Where we investigate unconstitutional methods to infer personality from communication of developers on GitHub. The data contains Big Five personality scores for three psycholinguistic methods (i.e., Yarkoni, Golbeck, and Personality Insights) for more than 83,000 people. The scores are based on comments of people on GitHub, where the comments are converted to personality scores. The data contains personality scores, number of words analyzed per person, whether or not people have indicated to be fluent in English, and whether they have English as their mothertongue.
- 2020-06-25 first online, published, posted
publisher4TU.Centre for Research Data
formatmedia types: text/csv, text/plain