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Understanding User Behavior Through Their Videos: How to Use the TikTok API to Get User Post Videos
In the age of short video platforms like TikTok, analyzing a user's content is one of the most intuitive ways to understand their preferences, engagement level, and content strategy. Whether you are a brand looking for influencers, a researcher studying social behavior, or a developer building content analytics systems, user-published videos are a core data source.
With the get user post videos endpoint provided by LuckData's TikTok API, you can easily fetch a TikTok user’s video list for data mining, behavioral profiling, and content insight. This article will explore how to leverage this API from practical, technical, and analytical perspectives.
1. The Business Value of User-Published Videos
A user's published video list reveals not only the themes they care about but also their style and activity level on the platform. Common use cases include:
Influencer Identification
Brands can review a creator's video topics, interaction rate, and upload frequency to assess partnership value.Competitor Analysis
Analyze the posting trends and content topics of competitors to understand their marketing strategies.Automated Recommendation Systems
Use video themes and hashtags to recommend creators or content to target audiences.Fake Account Detection
Detect accounts with high-frequency posting but low interaction, indicating bots or fake users.Content Categorization
Use video captions and tags to label creators by genre (e.g., fashion, dance, travel).Campaign Participation Monitoring
Identify high-engagement creators participating in specific challenges or hashtags.
2. API Usage and Parameter Explanation
LuckData's TikTok API is developer-friendly and supports both user_id and unique_id as inputs for identifying users.
Here is the basic Python code for using get user post videos:
import requestsheaders = {
'X-Luckdata-Api-Key': 'your_luckdata_key'
}
response = requests.get(
'https://luckdata.io/api/tiktok-api/ckR6u4Ni7aNG?count=0&cursor=0&user_id=107955&unique_id=@tiktok',
headers=headers,
)
data = response.json()
print(data)
Key Parameters:
user_id: Unique TikTok user IDunique_id: User’s TikTok handle (e.g., @tiktok)count: Number of videos to fetch (set to 0 to fetch all)cursor: For pagination, allows batch data retrieval
3. Sample Output and Key Fields
A single video object returned by the API includes various metadata fields:
{"video_id": "7214789212345678901",
"desc": "OOTD fashion of the day~",
"create_time": 1681002345,
"play_count": 19876,
"digg_count": 1550,
"comment_count": 236,
"share_count": 78,
"duration": 35,
"music_title": "original sound - tiktokuser",
"is_ad": false,
"cover": "https://somecdn.com/video_cover.jpg"
}
Key fields for business or technical analysis include:
desc: Caption text, useful for NLP and topic analysiscreate_time: Video post time, for frequency and recency trackingplay_count,digg_count,comment_count,share_count: Engagement metricsduration: Video length—short = viral content, long = educational/tutorialmusic_title: Sound or music used, which reflects trend affinitycover: Thumbnail, useful for computer vision or visual browsing
4. Advanced Techniques and Data Strategy
With the structured data returned, developers and analysts can apply multiple strategies:
1. Engagement Scoring Model
You can define a score based on engagement for each video:
Engagement Score = views * 0.4 + likes * 0.3 + comments * 0.2 + shares * 0.1Rank videos by score to identify a user’s top-performing content.
2. Automatic Content Style Classification
Using NLP to classify desc captions into categories like "fashion", "dance", "travel", etc., combined with video length and music types.
3. Time-Series Behavior Analysis
Convert create_time into weekly or monthly trends to analyze posting frequency or seasonal behavior.
4. Enrich Data with Video Details
Use the get video info API for deeper metadata on each video (e.g., hashtags, mentions) and combine with comment analysis via get comment list by video.
5. Music and Trend Discovery
Aggregate music_title across all videos to identify popular or recurring sounds used by the user, indicating trend participation or musical preference.
5. Strategic API Pairing Suggestions
To build a more complete user profile or content analytics system, consider combining:
search userto get user_idget user post videosto fetch the contentget video infofor detailed metadataget comment list by videofor sentiment or engagement analysisget follower listorget following listfor relationship mapping
This multi-endpoint approach is ideal for building dashboards, user research tools, or content intelligence platforms.
6. Practical Advice for Developers
Implement caching and rate limiting to stay within quota
Use cursor-based pagination to iteratively load all user content
Schedule batch jobs (e.g., using Airflow) for automated sync
Implement retry logic for error handling
Store results in a database for analysis and connect to BI tools like Metabase or Tableau
7. Conclusion
Analyzing a TikTok user’s post video list provides a rich dataset that reflects their activity, content themes, and popularity. With LuckData’s easy-to-use TikTok API, you can extract this valuable information in a structured and scalable way—enabling everything from influencer discovery to competitive research.
Whether you're building an analytics tool, researching creator trends, or automating social media insights, the get user post videos endpoint offers a powerful starting point. As part of a wider API suite, it allows for comprehensive social intelligence gathering that’s both flexible and developer-friendly.
