Social Media Usage and Emotional Well-Being

Dataset link: https://www.kaggle.com/datasets/emirhanai/social-media-usage-and-emotional-well-being?select=train.csv

[UPDATE] Identify tasks:

• See the average value of daily_usage_time in various age ranges, and genders
• Explore the correlations between (dominant_emotion, daily_usage_time), (dominant_emotion, Posts_Per_Day), (dominant_emotion, Likes_Received_Per_Day), (dominant_emotion, Comments_Received_Per_Day), and (dominant_emotion, Messages_Sent_Per_Day)
• Show the distribution of number of user in each dominant_emotion, in each platform
• Show the distribution of age range and gender in each platform
• Show the distribution of dominant_emotion in different age ranges and genders

This unique dataset was meticulously researched and prepared by AI Inventor Emirhan BULUT. It captures valuable information on social media usage and the dominant emotional state of users based on their activities. The dataset is ideal for exploring the relationship between social media usage patterns and emotional well-being.

Here's an explaination of the columns:

• User_ID: Unique identifier for the user.
• Age: Age of the user.
• Gender: Gender of the user (Female, Male, Non-binary).
• Platform: Social media platform used (e.g., Instagram, Twitter, Facebook, LinkedIn, Snapchat, Whatsapp, Telegram).
• Daily_Usage_Time (minutes): Daily time spent on the platform in minutes.
• Posts_Per_Day: Number of posts made per day.
• Likes_Received_Per_Day: Number of likes received per day.
• Comments_Received_Per_Day: Number of comments received per day.
• Messages_Sent_Per_Day: Number of messages sent per day.
• Dominant_Emotion: User's dominant emotional state during the day (e.g., Happiness, Sadness, Anger, Anxiety, Boredom, Neutral).