7,050 instances of Facebook engagement data from Thai fashion sellers across 12 feature columns. The dataset categorizes posts into four types—video, photo, status, and link—and records specific reaction counts including likes, loves, and wows.
Use Cases
- Perform K-means clustering to segment seller profiles based on engagement metrics like num_shares and num_comments
- Analyze the correlation between content format in the status_type column and high-intensity reactions such as num_loves or num_wows
- Predict the total num_reactions based on the time of posting found in the status_published column
Strengths
- 7,050 rows of social media interaction data from Thai retail pages
- Categorizes content into four status_type values: video, photo, status, and link
- Tracks nine distinct engagement metrics including num_comments, num_shares, and six emoji-based reactions