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📱 How Instagram's Algorithm Works (Simplified)

Instagram uses machine learning and user behavior to decide what content shows up in your feed, Reels, and Explore tab. Here's a simplified version of how the algorithm might work, explained in code.

🧠 Key Factors Considered:

• User Activity – What posts you like, comment on, share, or save.
• Post Engagement – Likes, comments, shares, and saves on the post.
• Interaction History – Your past behavior with that content creator.
• Content Type – Reels, Stories, Videos, Photos.
• Session Watch Time – How long you interact with a post.

💻 Simplified Python-style Code:

class Post:
    def __init__(self, author, likes, comments, saved, shared, post_type):
        self.author = author
        self.likes = likes
        self.comments = comments
        self.saved = saved
        self.shared = shared
        self.post_type = post_type

class User:
    def __init__(self, interactions, interests):
        self.interactions = interactions  # {author: score}
        self.interests = interests        # e.g. ["video", "reel"]

def calculate_engagement(post):
    return post.likes * 1 + post.comments * 2 + post.saved * 3 + post.shared * 4

def rank_posts(posts, user):
    ranked = []
    for post in posts:
        engagement = calculate_engagement(post)
        interaction_score = user.interactions.get(post.author, 0)
        interest_boost = 1 if post.post_type in user.interests else 0

        score = (engagement * 0.4) + (interaction_score * 0.4) + (interest_boost * 0.2)
        ranked.append((post, score))

    ranked.sort(key=lambda x: x[1], reverse=True)
    return [post for post, score in ranked]

📌 Summary

This is a basic simulation of Instagram's algorithm. The real algorithm is much more complex and powered by AI. But this gives you an idea of how engagement + personal preferences shape what you see.