Python Developer for Bot Detection and Blocking

Title:
Bot Network Detection & Mass Blocking System for X (Twitter) – Python / Data Engineering Expert Needed

Project Overview:
I am looking to hire an experienced developer / data engineer to help identify and neutralize a large-scale bot network (~5,000–50,000 accounts) on X (formerly Twitter).

The goal is NOT manual reporting, but building a semi-automated system that can:

Detect bot clusters starting from a seed list (50–500 known bot accounts)

Expand the network to identify thousands of related bot accounts

Identify controller / hub accounts coordinating these bots

Generate structured outputs for mass blocking and reporting

Scope of Work:

Data Collection

Use X API or scraping tools to extract:

Followers / following data

Tweet activity

Retweet / reply relationships

Account metadata (creation date, bio, etc.)

Bot Detection System

Build logic to detect bots based on:

Account age patterns

Username patterns

Low follower / high following ratio

Duplicate / near-duplicate tweet content

Coordinated activity (timing patterns)

Network Expansion

Start from seed bots and expand to:

Common follow targets

Shared retweet sources

Clustered communities

Graph Analysis

Build a graph model of accounts

Identify:

High-centrality nodes (controllers)

Dense bot clusters

Optional: visualization (Gephi or similar)

Output Deliverables

CSV/JSON of:

Identified bot accounts

Controller / hub accounts

Optional:

Python script to auto-block accounts via API

Report-ready evidence for platform submission

Technical Requirements (Must-Have):

Strong Python experience

Experience with APIs and/or scraping

Familiarity with:

Network analysis (networkx)

Data handling (pandas)

Experience with one or more:

Twarc

snscrape

Understanding of bot detection / spam patterns

Nice to Have:

Experience working with social media data (X/Twitter preferred)

Knowledge of graph visualization tools like Gephi

Experience detecting coordinated inauthentic behavior

Basic ML knowledge (for clustering / classification)

Deliverables:

Working Python scripts / pipeline

Bot detection logic (well documented)

List of identified bots + controllers

Instructions to run the system

Timeline:

Initial prototype: 3–5 days

Full system: 7–10 days

Budget:
Open to proposals (fixed or milestone-based)

Important Notes:

The goal is efficient detection and mitigation, not violating platform policies

Solution should be scalable (5k → 50k+ accounts)

Preference for candidates who have worked on similar anti-spam / OSINT / social graph problems

To Apply:
Please include:

Relevant past work (especially similar projects)

Tools / approach you would use

Estimated timeline

Any ideas to improve detection accuracy