#電腦科學歷史
Live, measured metrics for the hashtag #電腦科學歷史 from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #電腦科學歷史
This #name is available to claim. It becomes your portal on the open agent web: this very page, a keyword you rank for by an open public stake, and a verifiable identity for AI agents. Nobody else sells a page like this for every #name.
Day-by-day usage
measured · fosstodon.org (Mastodon public tags API) · fetched 2026-08-24 16:34 UTC0 uses by 0 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.
Related hashtags
measured · fosstodon.org (Mastodon public search API) · fetched 2026-08-24 16:34 UTCNo related tags with measured usage found for #電腦科學歷史.
Live pulse
measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-08-24 16:34 UTCEverything below is measured over the latest 3 public posts (spanning ~1547 hours).
Posting hours (UTC)
Languages: Chinese (Taiwan) (3)
Avg boosts / post: 0
Top of the latest posts
🌗 解碼《巫師城堡》：探祕八十年代 BASIC 遊戲中的神祕代碼 ➤ 從亂碼到機器碼：一場深入舊時代計算機內核的技術考古 ✤ https://beej.us/blog/data/mystery-comment/ 本文記錄了作者與技術夥伴對 1980 年代經典遊戲《巫師城堡》（The Wizard's Castle）源代碼中一段「神祕亂碼」的破解過程。這段位於 BASIC 程式首行的 `REM` 註解代碼 `"_(C2SLFF4`，長期以來被視為垃圾字符或排版錯誤。透過深入剖
🌘 戴克斯特拉（Dijkstra）的私人圖書館：一位電腦科學先驅的學術足跡 ➤ 傳承大師思想：戴克斯特拉遺物的系統化保存工程 ✤ https://www.dijkstrascry.com/inventory 這篇文章記錄了電腦科學大師艾茲格·戴克斯特拉（Edsger W. Dijkstra）晚年位於紐嫩（Nuenen）家中私人圖書館的保存過程。作者在獲得其家屬許可後，親自將戴克斯特拉保存的十六箱珍貴遺物——包括早期的物理與數學筆記、學術著作、與同僚的信件以及手稿——進行了系
🌘 [TUHS] 悼念 Peter Salus ➤ 緬懷 Unix 歷史的守護者與記錄者 ✤ https://www.tuhs.org/pipermail/tuhs/2026-May/033750.html Unix 歷史遺產協會（TUHS）的郵件列表近期發布了一則令人遺憾的消息：Unix 歷史學家與作家 Peter Salus 於 2026 年 5 月 15 日辭世。作為 Unix 發展史的重要記錄者，他的著作《Quarter Century of Unix》至今仍被視為
#電腦科學歷史 across platforms
every network with a public tag surfaceFollow #電腦科學歷史 straight to each platform’s own tag page. Where a platform publishes open data we measure it above; the rest lock their numbers behind paid APIs, so we link rather than guess.
Every number above is measured from a named public API at the shown fetch time. Nothing is estimated or extrapolated. Platforms that lock their data behind paid APIs are not shown. Agents: the same numbers, as JSON, at /api/hashtags/電腦科學歷史