bilibili-sentiment-dashboard

What This Skill Does

The bilibili-sentiment-dashboard is an advanced AI-powered analytics agent designed for content creators, marketers, and researchers. It bridges the gap between raw viewer feedback and actionable insights by processing Bilibili video data. This skill extracts comments and danmaku (bullet screen comments) from any Bilibili video using its URL or ID (AV/BV). It utilizes a three-step workflow to parse, analyze, and deliver a comprehensive sentiment report. The result is a multi-dimensional analysis that breaks down emotional responses, categorizes feedback, and identifies key opinion trends, enabling users to understand their audience's pulse with precision.

Installation

To integrate this skill into your OpenClaw environment, simply execute the following command in your terminal or command-line interface: clawhub install openclaw/skills/skills/allinherog-star/bilibili-sentiment-dashboard Once installed, ensure you have a valid API key from the provider (ai-skills.ai) configured in your environment to access the task processing endpoints.

Use Cases

• Video Performance Tracking: Quickly assess how viewers reacted to a newly uploaded video by measuring the balance of positive and negative sentiment.
• Market Research: Analyze competitor videos to identify what features or topics the audience loves or dislikes, informing your own content strategy.
• Crisis Management: Monitor sudden spikes in negative sentiment in the comment section to identify potential controversies or PR issues before they escalate.
• Audience Engagement: Understand the specific emotions triggered by your content, such as 'excitement', 'confusion', or 'agreement', to tailor future production style.

Example Prompts

1. "Analyze the comments for this Bilibili video: https://www.bilibili.com/video/BV1xx411c7mD. I want to know if the audience liked the pacing."
2. "Can you give me a sentiment report on the bullet screens of the latest video by [UP Name]? I'm worried the feedback is turning negative."
3. "Is the audience sentiment for this video positive or negative? Please summarize the main criticisms and top emotional keywords."

Tips & Limitations

• Quotas: This tool relies on external API credits. If you encounter errors, ensure your account has sufficient balance at ai-skills.ai.
• Data Accuracy: Analysis is based on current available public data. Heavy traffic videos may require slightly longer processing times during the Step 3 polling phase.
• Context Awareness: AI sentiment analysis is highly effective but should be combined with qualitative human review for nuances like irony or sarcarsm, which are occasionally misinterpreted in complex internet slang.