On the Personality Traits of StackOverflow Users
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In the last decade, developers have been increasingly sharing their questions with each other through Question and Answer (Q&A) websites. As a result, these websites have become valuable knowledge repositories, covering a wealth of topics related to particular programming languages. This knowledge is even more useful as the developer community evaluates both questions and answers through a voting mechanism. As votes accumulate, the developer community recognizes reputed members and further trusts their answers. In this paper, we analyze the community's questions and answers to determine the developers' personality traits, using the Linguistic Inquiry and Word Count (LIWC). We explore the personality traits of Stack Overflow authors by categorizing them into different categories based on their reputation. Through textual analysis of Stack Overflow posts, we found that the top reputed authors are more extroverted compared to medium and low reputed users. Moreover, authors of up-voted posts express significantly less negative emotions than authors of down-voted posts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it