Personal ProjectCASE STUDY // INSTAGRAM-UNFOLLOW-TRACKER

Instagram Analytics & Follower Graph Engine

Engineered a personal Python automation tool to monitor, parse, and analyze Instagram social graph relationships and follower mutations over time.

Role: Creator / EngineerPersonal Engineering Project

Automated

Data Processing

O(N) Graph Match

Diff Detection

Structured JSON / CSV

Output

Problem & Engineering Context

Native social interfaces provide no historical visibility into social graph changes, follower churn, or accounts that don't reciprocate follows without relying on untrusted third-party mobile apps that require credential sharing.

Built as a lightweight, secure personal automation tool to practice graph diffing algorithms, local data privacy, and automated data extraction without compromising account security.

Strategic Approach

Implemented a Python script that ingests GDPR/data export packages or authorized API payloads, parses complex nested JSON structures, and computes bidirectional set differences to identify follower changes.

Technical Architecture

Graph Mutation Analysis Pipeline

Ingests snapshot files, parses relationships into hash sets, and computes set intersections and differences to generate delta reports.

Zero-credential leakage design operating purely on local filesystem data packages.
Efficient Python set operations comparing timestamped snapshots.
Formatted terminal reporting and structured JSON export for long-term analytics.

Implementation Details

01.Developed modular Python scripts parsing followers, following, and pending request datasets.
02.Implemented set difference calculations: (Following - Followers) and (Followers - Following).
03.Added formatted terminal output tables and timestamped historical log files.

Key Challenges & Resolutions

Handling variations in export formats across different social platform schema versions.

Ensuring zero risk of account flags by avoiding unofficial reverse-engineered API scraping and adhering strictly to data exports.

Measurable Outcomes

Clean, working personal automation tool providing complete privacy-first follower tracking.

Demonstrated practical software development, data parsing, and algorithmic diffing capabilities.

Key Engineering Takeaways

💡 Privacy-first architecture running locally on user data eliminates the security risks of third-party credential aggregators.

TECHNOLOGIES EMPLOYED

PythonREST APIsJSON TelemetryAutomationData Analytics

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