Instagram Recommendations: Case Study

Download the dataset below to solve this Data Science case study on Instagram Recommendations. (Dataset Source: Instagram)

Instagram Recommendations: Case Study

A recommendation system is one of the applications of data science used by almost every platform to recommend products and content to its users. Instagram uses recommendation systems to recommend content and accounts to its users.

To recommend content and accounts to its users, Instagram analyzes the kind of content you engage with daily. Here’s the Instagram account data we collected. Below are all the features in the dataset:

  1. Impressions: Number of impressions in a post (Reach)
  2. From Home: Reach from home
  3. From Hashtags: Reach from Hashtags
  4. From Explore: Reach from Explore
  5. From Other: Reach from other sources
  6. Saves: Number of saves
  7. Comments: Number of comments
  8. Shares: Number of shares
  9. Likes: Number of Likes
  10. Profile Visits: Numer of profile visits from the post
  11. Follows: Number of Follows from the post
  12. Caption: Caption of the post
  13. Hashtags: Hashtags used in the post

You are required to find similarities in content and create a recommendation system to recommend more content.

References to Solve this Data Science Case Study