Monitoring Short Video Public Opinion: Building a Brand Reputation Tracking System with the Douyin API

2025-04-29

In today’s world where “traffic equals public sentiment and video is the battlefield,” a brand’s reputation can rise or fall based on a single short video. Whether it's a careless comment triggering mass ridicule or a successful co-branding campaign sparking organic hype, brands need one key capability: the ability to anticipate, monitor dynamically, and respond quickly to shifts in public sentiment on Douyin.

1. Why Do You Need Short Video Reputation Tracking?

Compared to traditional news reports or Weibo posts, Douyin videos spread faster, carry stronger emotional influence, and easily become meme material. A single negative video might:

Reach millions of views within hours
Trigger remixes, imitations, and escalate rapidly
Be linked to brand tags, causing long-term search association

Most brands only become aware of issues after media reports or customer complaints appear—missing the golden window for response. By building a Douyin data monitoring system, you can:

Identify viral videos related to your brand in real time
Extract dominant sentiments and hot topics from video comments
Continuously track keyword or hashtag popularity trends
Receive early warnings for abnormal content propagation

2. System Architecture Overview

The core components of the reputation monitoring system include:

Keyword Monitoring: Create keyword groups around brand names, products, ambassadors
Video Data Collection: Use APIs to regularly fetch relevant video data
Sentiment & Semantic Analysis: Use NLP to analyze comment tendencies
Trend Modeling: Analyze heat curves and content spread paths
Alert Mechanism: Trigger warnings on traffic spikes or negative sentiment surges
Visualization Dashboard & Reports: Help teams make fast, informed decisions

3. Keyword Monitoring: From Brand to Ambassadors

Suggested keyword categories:

Brand Keywords: e.g., “Xiaohongshu Collaboration,” “Honor Phone,” “Naixue Tea”
Ambassadors/Spokespersons: e.g., “Wang Yibo endorsement,” “Luo Yonghao livestream”
Sensitive Combinations: e.g., “XXX backlash,” “XXX poor service,” “XXX false advertising”

Example: Generate a Keyword Search List

brand_keywords = ["Honor", "Honor Magic6", "Honor Phone", "Zhao Liying Honor"]

You can loop through keywords regularly and construct API request URLs to fetch videos.

4. Video Crawling & Sentiment Detection: Building a Reputation Perception Engine

LuckData offers stable data interfaces for fast integration. Below is the basic workflow for fetching videos and extracting sentiment from comments.

1. Fetch Videos Related to a Keyword

import requests
def search_douyin_videos(keyword):
url = f'https://luckdata.io/api/douyin-API/get_xv5p?type=search&keyword={keyword}&page_size=10'
headers = {'X-Luckdata-Api-Key': 'your_key'}
resp = requests.get(url, headers=headers)
return resp.json()['data']

2. Extract Comments and Analyze Sentiment

Assuming the API returns a list of comment texts:

from snownlp import SnowNLP
def analyze_comment_sentiment(comments):
pos, neg = 0, 0
for comment in comments:
score = SnowNLP(comment).sentiments
if score > 0.6:
pos += 1
elif score < 0.4:
neg += 1
return {'positive': pos, 'negative': neg}

By aggregating sentiment scores over time, you can detect “positive-to-negative” shifts or negative sentiment outbreaks.

5. Build Trend Models & Alert Mechanisms

Brands fear unseen crises the most. A heat trend model with alert thresholds enables early detection.

Example: Set a Popularity Spike Threshold

def detect_hot_spike(today_hot, yesterday_hot, threshold=3.0):
if yesterday_hot == 0:
return False
ratio = today_hot / yesterday_hot
return ratio > threshold

When a keyword-related video count triples within 24 hours, trigger alerts:

Push notifications to Slack or enterprise messaging
Summarize alerts via email
Auto-generate briefs for the PR team

6. Build a Reputation Dashboard: One Screen, Full Control

Use tools like Metabase, Superset, or Grafana to build visualization dashboards including:

Keyword Trend Charts: Track daily video volumes over time
Sentiment Pie Charts: Show ratios of positive, neutral, and negative comments
Negative Viral Video List: Include play counts, publish time, and comment stats
Abnormal Event Timeline: Record each sentiment or traffic anomaly with video links

These tools support daily or weekly reporting and help guide data-informed PR actions.

7. Expansion: Competitor Benchmarking & Industry Reports

Once matured, the system can scale beyond your brand:

Monitor Competitor Reputation: Benchmark against rivals and understand market dynamics
Track Industry Events: Follow key trends like food safety, influencer scandals, price wars
Generate Monthly Reports: Summarize reputation insights for leadership and stakeholders

8. How LuckData Helps You Deploy the System Quickly

LuckData provides full-stack support for building reputation tracking systems:

APIs for keyword search, comment extraction, popularity rankings with comprehensive coverage
Transparent, credit-based billing suitable for prototypes and scaling
High-concurrency pull support for real-time crisis tracking
Well-documented and multilingual SDKs for fast and flexible integration

You don’t need to write your own crawlers or worry about API stability—LuckData delivers robust, long-term data solutions for brand intelligence.

Conclusion

In the era of short videos, brand reputation management is no longer a reactive task—it demands real-time monitoring, predictive insights, and data-driven strategies. With the Douyin API and platforms like LuckData, brands can regain control of public sentiment, mitigate crises early, and build intelligent PR systems.

If you’re a brand manager, marketing agency, or data analyst, now is the best time to deploy this capability. Visit the LuckData website to apply for a Douyin API trial and take the first step toward intelligent brand reputation monitoring : https://luckdata.io/