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What It Does

  • Fetch LinkedIn Comments: Retrieves comments from a person’s LinkedIn profile using LinkedIn RapidAPI.
  • Engagement Metrics: Provides detailed engagement data including the number of likes, comments, empathy reactions, and more.
  • Comment Content: Fetches the actual comment text, along with metadata such as author and timestamp.
  • Batch Processing: Supports batch processing via template variables to process multiple profiles at once.
  • Pagination Handling: Automatically handles pagination for up to 250 comments.
  • Metadata: Includes metadata such as the total number of reactions and whether a post was reshared.

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🏁 Getting Started

Get Comments By Person Node config screenshot
1

Add the Get Comments By Person Node

Drag and drop the node into your workflow to fetch LinkedIn comments.
2

Provide LinkedIn Profile URL

Add the LinkedIn profile URL and define the limit for comments to fetch.
3

Run the Workflow

Execute the workflow to fetch LinkedIn comments based on the provided settings.
4

Review the Output

The output will include the comments, engagement metrics, and associated metadata in the DataFrame.

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Inputs

Input NameTypeRequiredDescription
input_df_s3_urlOptional[str]Yes, if template variables are usedS3 URL to an input DataFrame (CSV/Parquet). Required when using template variables in settings for batch processing

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Outputs

The node returns a List[Dict[str, Any]] where each dictionary contains:
Output NameTypeDescription
s3_output_urlstrS3 URL of the output DataFrame (Parquet format)
s3_output_url_csvstrS3 URL of the output DataFrame (CSV format)
file_infoDictContains metadata: rows_count (int), columns_count (int), columns (List[str])
handle_conditionstrAlways returns "default" for this node

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Output DataFrame Structure

The output DataFrame will contain the following LinkedIn comment fields:
  • person_comments: Boolean indicating if the comment is highlighted (mapped from highlighted_comments)
  • urn: LinkedIn URN identifier for the comment
  • posted: Timestamp when the comment was posted
  • post_author: LinkedIn URL of the comment author (mapped from poster_linkedin_url)
  • poster: Author information object containing name and other details
  • post_url: URL of the original post where the comment was made
  • text: The actual comment text content
  • num_appreciations: Number of appreciations on the comment
  • num_comments: Number of replies to this comment
  • num_empathy: Number of empathy reactions
  • num_entertainments: Number of entertainment reactions
  • num_interests: Number of interest reactions
  • num_likes: Number of likes on the comment
  • num_praises: Number of praise reactions
  • num_reactions: Total number of reactions
  • num_reposts: Number of reposts
  • reshared: Boolean indicating if the post was reshared
  • resharer_comment: Comment text if the post was reshared
Note: When input data is provided, all original columns are preserved and merged with the LinkedIn comment fields. Column name conflicts are resolved automatically using the column name resolution strategy.

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How It Works

  1. Data Loading: Loads input data if provided using data_loading_helper.
  2. Processing:
    • Single or batch processing mode based on input.
    • Template variables in LinkedIn URL are resolved and processed.
  3. API Interaction: Calls LinkedIn RapidAPI for comment data fetching.
  4. Pagination: Handles pagination automatically based on the specified limit (up to 250 comments).
  5. Credit Management: Tracks credit consumption per page (5 credits per page).
  6. Output Generation:
    • Merges LinkedIn comment data with original input columns.
    • Saves results in both Parquet and CSV formats to S3.

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🚀 Example Use Cases & Prompts

Use CaseSetup or Prompt Example
Social Media AnalysisTrack engagement metrics for comments on a profile
Competitor ResearchFetch and analyze comments on competitor’s posts
Influencer EvaluationAnalyze comments to gauge the influence of a person
Sentiment AnalysisAssess sentiment through comments and reactions

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✨ Pro Tips

Use template variables in linkedin_url to process multiple LinkedIn profiles in batch mode.
Keep an eye on API rate limits to avoid hitting credit limits. Consider limiting the number of comments fetched.

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⚠️ Important Considerations

Requires LinkedIn RapidAPI credentials for authentication and data access.
Comments are fetched based on the limit setting (max 250 comments). If the limit exceeds 250, only the first 250 comments will be returned.

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🛠 Troubleshooting & Gotchas

SymptomLikely CauseQuick Fix
API Rate Limit ReachedToo many requests in a short periodWait for the rate limit reset or reduce the number of requests
Invalid LinkedIn URLMalformed or incorrect URLDouble-check the LinkedIn URL format and ensure it’s valid
Missing CommentsInsufficient public commentsCheck if the LinkedIn profile has public comments available

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📝 FAQ

Currently, only the linkedin_rapid_api vendor is supported for fetching LinkedIn comments.
Yes, by using template variables in the LinkedIn URL setting, you can fetch comments for multiple profiles in batch mode.

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💰 Pricing

The Get Comments By Person Node incurs 5 credits per page fetched from LinkedIn RapidAPI.
ActionCredit Cost
Fetching comments5 credits per page
Credits are consumed based on the number of pages fetched. A single page can return up to 50 comments.

Start scraping LinkedIn comments and track engagement effortlessly! 🚀