AI Agent Hub
Back to skills
Bilibili Danmaku and Comment Analyzer icon

Bilibili Danmaku and Comment Analyzer

Data Analysis Updated 2026.08.30

Paste the following prompt into your AI chat to install this skill:

Please follow https://skillhub.cn/install/skillhub.md and install @user_ab5ae6ee/unclecheng-bilibili-analyzer-v2.

About this skill

What problem it solves

Bilibili videos often distribute key opinions across danmaku and comments. View count alone rarely reveals discussion focus, sentiment polarity, or recurring controversy. This skill turns that unstructured interaction data into analyzable text, useful for public-opinion observation, content review, and topic mining.

How it works

It uses Bilibili public APIs with a configured User-Agent, resolves a BV id to cid, then fetches XML danmaku and comment endpoints. The main pipeline parses video metadata, collects danmaku and high-rated comments, groups entries by timestamp and content, extracts frequent terms, estimates sentiment, highlights dense danmaku windows, and writes a Markdown report. For engineers, the value is a reusable flow that combines scraping, cleaning, statistics, and reporting.

Boundaries and notes

Comment retrieval may be limited without login; frequent requests can trigger risk control; empty results may occur if the video lacks danmaku or endpoints change. Complete comment coverage and reliable user profiling require authenticated credentials or a more stable data source. It suits quick public-video analysis, not compliance forensics or large-scale commercial monitoring.

Use Cases

  • Review one Bilibili video for operations by summarizing danmaku and comment keywords, sentiment, and outputting a Markdown report.
  • Research video topics by collecting danmaku time distribution and identifying dense discussion windows such as 4-7 minutes.
  • Compile Bilibili comment samples for sentiment monitoring by extracting top comments, polarity, and keywords into a citable summary.
  • Pre-check video discussion focus before moderation by comparing frequent terms and sentiment distribution against sensitive topics.

Best For

  • Bilibili content operations analyst: needs to identify the real discussion focus of a single video's danmaku and comments.
  • Public opinion researcher: needs to turn public Bilibili interaction data into keyword and sentiment summaries.
  • Video topic editor: wants to know when danmaku are densest in a category of videos.
  • Data engineering reviewer: needs to validate public API returns for danmaku and comments.