MétaCan
Menu
Back to cohort
Record W2057710186 · doi:10.1145/2491411.2494585

Toward understanding the causes of unanswered questions in software information sites: a case study of stack overflow

2013· article· en· W2057710186 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicExpert finding and Q&A systems
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsComputer scienceStack (abstract data type)Data scienceSoftwareSoftware engineeringWorld Wide WebProgramming language

Abstract

fetched live from OpenAlex

Stack Overflow is a highly successful question-answering website in the programming community, which not only provide quick solutions to programmers’ questions but also is considered as a large repository of valuable software engineering knowledge. However, despite having a very engaged and active user community, Stack Overflow currently has more than 300K unanswered questions. In this paper, we perform an initial investigation to understand why these questions remain unanswered by applying a combination of statistical and data mining techniques. Our preliminary results indicate that although there are some topics that were never answered, most questions remained unanswered because they apparently are of little interest to the user community.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.269
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.076
GPT teacher head0.282
Teacher spread0.205 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Quick stats

Citations41
Published2013
Admission routes1
Has abstractyes

Explore more

Same topicExpert finding and Q&A systemsFrench-language works237,207