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Record W7132534285

Bilibili: From Niche to Mainstream?

Yu 张宇, 薛文婷

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

VenueCEIBS Institutional Repository · 2021
Typeother
Language
Field
Topic
Canadian institutionsCentre Casa
Fundersnot available
KeywordsNicheEctothermContext (archaeology)Population
DOInot available

Abstract

fetched live from OpenAlex

本案例描述了哔哩哔哩(又称“B站”)如何在强敌环伺的在线娱乐产业成功突围并取得蓬勃发展。中国人口红利犹存,在线娱乐产业(包括视频、手机游戏和直播)继续呈现规模大、速度快的发展态势。玛丽·米克尔发布的《2019年互联网趋势报告》显示,2018年,中国移动互联网用户数量达到了8.17亿人,同比上涨9%,移动数据使用量同比增长189%,高于2017年的162%的增幅。[ https://www.bondcap.com/report/itr19/] 出生于90年代末-20世纪初的“Z世代”已然成为数字时代的消费主力军。这些数字原住民便是B站瞄准的主要客户群。为捕获年轻人的芳心,B站开发并定制了一系列特色服务。对比爱奇艺(百度旗下)、腾讯视频(腾讯旗下)和优酷(阿里巴巴旗下)等视频和流媒体服务头部平台,B站凭借独有的注册答题考试和弹幕文化,以及对其特有生态系统的持续管理【尤其是内容创作者(UP主)激励方案)】,成功建立起一个极具黏性的在线社区。 然而,B站的高歌猛进有可能因为收入来源不稳定等风险遭遇“急刹车”。除这些风险外,B站最大的挑战仍然源自其对核心竞争力的认知及把控:是坚守做小众社区的初心,拒绝铺天盖地的广告;还是增加更多主流内容,以吸纳更多的用户、投资者和广告主?

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.431
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0020.003
Scholarly communication0.0010.000
Open science0.0020.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0350.043

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 head0.018
GPT teacher head0.255
Teacher spread0.236 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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