Tamer Abdelaziz · 2026 · arXiv (Cornell University)
DOI: 10.5281/zenodo.23551228 · cited by 0 works (OpenAlex) · open-access PDF
Pada dasarnya, pertukaran Ethereum Stack Exchange (ESE) mencatat apa yang mereka minta tanpa disadari, dan apakah ada yang memecahkannya. Kami mempelajari setiap pertanyaan yang diposting ke ESE dari Januari 2016 hingga Desember 2025, dan penilaian manual dari setiap kasus yang dipertanyakan menempatkan akurasi mereka di 87.9 hingga 93.5%, karena korpusnya adalah tingkat sampel yang lengkap, tidak membawa kesalahan. Kami meminta apa yang para pengembang minta bantuan dari 22 topik yang diminta ke 19. Komite tiga penyedia model bahasa menyaring label, dan penilaian manual dari setiap kasus yang dipertanyakan menempatkan akurasi mereka di 87.9 hingga 93.5%. Karena korpusnya adalah tingkat sampel yang lengkap, tidak membawa kesalahan sampel. Kami meminta apa yang para pengembang minta bantuan, dari saham ke 16, apakah lokasi sebelumnya masih mengajukan pertanyaan, dan di
Machine translation (Meta M2M100); the English original follows.
The Ethereum community learns where developers struggle through surveys and interviews, which record what developers say when asked about a chosen theme. Ethereum Stack Exchange (ESE) records what they ask for unprompted, and whether anyone resolves it. We study every question posted to ESE from Jan 2016 to Dec 2025, 54,637 in all, and label each with a prompt-based topic pipeline seeded with eight Ethereum-specific topics and open to new ones (22 topics in all). A three-provider committee of language models screens the labels, and manual adjudication of every disputed case puts their accuracy at 87.9 to 93.5%. Because the corpus is the complete record, no rate carries sampling error. We ask what developers ask for help with, whether the venue still resolves it, and, where it does not, whether the questions changed or their resolution did. Demand is concentrated on writing, deploying, and debugging contracts; the toolchain is the second-largest topic and growing, while security, consensus, and scaling are thin. Supply has weakened, and unevenly: answers still arrive, closure falls further. Across five estimators of the decade, the share of questions drawing any answer fell by 9.5 to 18.6 percentage points, but among answered questions the share reaching an accepted answer fell by 16.2 to 24.5. Rebuilding the later acceptance rate at the earlier topic mix moves the fall only from 9.40 to 9.32 points, so the topic mix does not explain it. Who asks separates outcomes far more sharply than what is asked: acceptance runs from 19.8% for askers below 10 reputation to 66.8% at 10k and above, a 47- point spread with a gradient in every year, against 17 across topics, and a shift toward newer askers accounts for up to 59% of the acceptance fall. The largest of seven properties an asker controls accompanies 5 points. The record places the support gap in the toolchain and among newcomers.
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