AI-Powered LinkedIn Engagement Tracker | AI Prompt Library

AI-Powered LinkedIn Engagement Tracker

Inspired from Daniel Disney of https://danieldisney.online/ AI extracts names of people who liked or commented on LinkedIn posts to identify key influencers, leads, and engagement opportunities.

Instructions to Extract Names

You will be working with LinkedIn analytics data to extract the names of people who have liked or commented on posts. Here are the steps to follow:

  1. The data you will be working with is provided in the {$LINKEDIN_ANALYTICS_DATA} variable. This contains information about various LinkedIn posts, including details on likes and comments.

  2. First, parse the data to identify the relevant sections containing information about likes and comments for each post. This may involve splitting the data into chunks by post, and then further splitting each post chunk to extract the likes and comments sections.

  3. Within the likes and comments sections, look for patterns that indicate a person's name, such as strings with a capitalized first letter followed by a space and capitalized second letter (e.g. "John Doe"). You may need to account for variations like middle initials or suffixes.

  4. As you identify names in the likes and comments, store them in a list or other data structure, being careful to avoid duplicates.

  5. Once you have extracted all the names, format them into an output string like this:

Names of people who liked or commented:

[Name 1]

[Name 2]

[Name 3]

...

Make sure to replace [Name 1], [Name 2], etc. with the actual names you extracted, each on a new line.

If there are no names found in the data, simply output:

No names found in the provided data.

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