Influences of Social Media on Consumer Purchasing

The social_media_impulse_buying_500.csv dataset comprises 500 entries designed to support machine learning tasks that predict whether a user is likely to make an impulse purchase. It includes a total of 14 variables—13 input features and 1 target variable. The target variable, impulse_purchase, is binary, indicating impulsive buying behaviour (1 for yes, 0 for no). The dataset contains demographic attributes such as age, gender, education level, and monthly income. It also features social media usage metrics like time_spent_on_social_media, platform_most_used, and follow_influencers. Additional variables such as ad_frequency and social_media_ads_clicks measure the user’s exposure and interaction with advertisements. Psychological aspects are captured through perceived_discount, emotional_trigger_score, and peer_influence_score, while online_purchase_frequency reflects shopping habits.