Douyin Comment Sentiment Analysis

Problem

Ops and data engineers often receive Douyin comments that are hard to turn into a usable conclusion: the text may come from videos, products, or campaigns, and it may contain spam, empty comments, sarcasm, and complaints. Manual review can miss negative hotspots, while screenshots are not enough for a consistent report. This skill converts authorized comment exports into a stable sentiment summary, risk flags, and importable CSV records.

How It Works

• Data source: Supports local CSV and JSON exports, or an authorized API endpoint with the token in an environment variable.
• Field mapping: Recognizes common aliases such as content, comment_text, aweme_id, create_time, and digg_count.
• Analysis output: Returns total comments, valid comments, removed empty or spam-like records, positive/negative/neutral distribution, a sentiment score from -100 to 100, and dominant emotions such as joy, anger, sadness, fear, support, and doubt.
• Reporting and import: Produces key positive and negative excerpts with hashed user identifiers only, shows per-video or per-hour hotspots when available, and exports canonical CSV records for the sentiment_system pipeline.

Boundaries

The skill does not scrape Douyin pages, reverse private mobile APIs, bypass login, captcha, or rate limits, or process unauthorized comments. If the user only provides a share URL, the skill should ask for an authorized export, Open Platform API, or local file. In production, tokens should be stored in secret management or environment variables, while raw exports and reports should follow lifecycle retention rules.