Python Developer for Bot Detection and Blocking

@quan9824

With my extensive experience as a Full-Stack Python Developer, I am well-equipped to take on the unique challenges your project poses. Having worked in diverse environments, ranging from web scraping to AI systems like Machine Learning and Deep Learning, I've honed my skills in data processing, visualization, and analysis – exactly what your project requires. Additionally, my proficiency with important tools such as networkx and pandas makes me adept at handling large-scale data sets efficiently. I understand that your aim is to build a not-so-simple bot detection system, but I'm all about tackling complex problems in creative ways. Given the scale of the task at hand and my understanding of bot behavior patterns, I believe I can provide you with an exceptional solution that not only detects the bots but also identifies their controllers adeptly. My past work reflects similar anti-spam and OSINT-focused projects that involved detecting coordinated inauthentic behavior - giving me an upper hand for this critical project. With my technical prowess combined with my propensity for output perfection and on-time delivery, your project is set up for success with me on your team. Allowing me the honor of being a part of your venture will ensure a meticulously crafted system that abides by platform policies while streamlining the detection process at scale

@Joelite17

I’m interested in building your bot network detection and analysis system for X. I have strong experience in Python-based data pipelines, social graph analysis, and automation systems that scale from small seed datasets to large network expansions while maintaining accuracy and performance. For data collection, I would combine official API access (where available) with tools like Twarc or snscrape to gather follower/following relationships, tweet histories, and engagement patterns. The pipeline will normalize this data into structured formats using pandas, with efficient storage (PostgreSQL or Parquet) to handle tens of thousands of accounts without performance bottlenecks. I have other setup to allow me achieve this. I am looking forward to hearing from you.

@abdf2010

Hey, your project, Python Developer for Bot Detection and project looks like a great fit for my skills. I've worked on similar Python projects and can deliver solid results. Let me know if you'd like to chat about the approach.

@Hemantt841

I see you need a Python developer to build a semi-automated bot detection and mass blocking system for X, focusing on expanding from a seed list to identify thousands of related bot accounts and their controllers. You want a scalable solution that uses network analysis and outputs structured data suitable for mass blocking and reporting. Your project requires extracting detailed follower, tweet, and metadata via the X API or scraping, then applying bot detection logic based on patterns like account age, follower ratios, and coordinated activity. The challenge to model the graph identifying high-centrality nodes and dense clusters aligns well with your goal of efficient and scalable bot network neutralization. I have built similar systems using Python with pandas and networkx to analyze social network graphs and detect coordinated bot behavior, integrating Twarc for Twitter data collection. I developed pipelines that expanded from seed accounts to identify bot clusters and controllers, producing JSON outputs for automated blocking, which directly matches your requirements. I can deliver an initial prototype within 4 days and the full system in 9 days, including documentation and instructions. Let’s discuss how to refine detection accuracy and ensure the solution fits your scalability needs.

@Algokage

Hello, I can deliver a semi-automated bot detection and blocking system for X (Twitter) as per your requirements. I'll use Python, leveraging the X API and tools like networkx and pandas to collect data, detect bot patterns, and expand the network. My approach includes graph analysis to identify controllers and clusters, ensuring scalability for 5k-50k+ accounts. With 5+ years of experience in Python, data engineering, and social media analysis, I've worked on similar anti-spam projects. I can provide a prototype within 3-5 days and the full system in 7-10 days. Message me for samples of past work or to discuss further. Thanks, Adegoke. M

@anilptk

Dear Undefined, I am excited to submit my proposal for the Bot Network Detection & Mass Blocking System project on X (Twitter). With my expertise in Python, Data Processing, Machine Learning, and Twitter API, I am confident in my ability to help identify and neutralize the bot network effectively. Using my strong Python experience and knowledge of APIs and scraping, I can assist in building a semi-automated system to detect bot clusters, expand the network, and generate structured outputs for mass blocking and reporting. My familiarity with network analysis, data handling, and bot detection patterns makes me well-equipped for this task. In terms of approach, I plan to utilize Twarc and snscrape for data collection, alongside networkx and pandas for analysis. I aim

@umarabbasi095

I can build a scalable Python system to detect and map bot networks starting from your seed accounts. I’ll use tools like snscrape/Twarc, pandas, and networkx to collect data, expand clusters, and identify high-centrality controller accounts. The system will detect bots using patterns like account age, activity timing, content similarity, and network behavior. You’ll receive clean CSV/JSON outputs with bot lists, clusters, and hub accounts, plus optional graph visualization. The code will be well-structured, documented, and easy to run or extend. I can deliver an initial prototype in 3–5 days and the full system within 7–10 days.

@tamannarajput18

As a seasoned Full Stack Developer with a specific focus on MEAN and MERN stack development, building anti-spam and OSINT solutions are right up my alley. My expertise in Python, coupled with data engineering skills, makes me an ideal candidate for your project. In line with your requirements, I'm well-versed in detecting bot patterns by analyzing account age, follower/following ratios, tweet contents and identifying coordinated activities. Not only can I visualize the detected clusters and high-centrality nodes (if need be) using tools like Gephi, but deliver comprehensive outputs such as CSV/JSON that include identified bots along with hub accounts. I have a reputation for delivering quality results. I prioritize clean coding standards and scalable system designs ensuring that efficiency is maintained while keeping user privacy intact. Having worked extensively with APIs and executing thorough testing protocols to ensure compliance to platform policies, I am confident in my ability to build a solid bot detection and blocking system for you.

@muhammadz0779

Hi, I can build a scalable Python system to detect and map bot networks from your seed accounts. I’ll use API/scraping + pandas and networkx to: Detect bots (patterns, ratios, duplicate content, timing) Expand network clusters Identify controller/hub accounts Deliver clean CSV/JSON outputs + optional auto-block script Timeline: Prototype: 1–2 days Full system: 5–6 days Clean, well-documented, and ready to run locally. Ready to start immediately. Best regards, Zohaib

@alexbuilds7

Hi, I came across your project "Python Developer for Bot Detection and Blocking" and I'm confident I can deliver exactly what you need. I have hands-on experience with Python, Data Processing, Twitter and have built similar solutions. Here's what I bring: - Python development (5+ years) - Web scraping & browser automation (Playwright, Selenium, BeautifulSoup) - AI/ML model integration (OpenAI, Anthropic, local LLMs) My approach: 1. Review your requirements in detail and clarify any questions 2. Build a clean, well-documented solution 3. Test thoroughly and deliver within 21 days 4. Provide revisions until you're satisfied I've included a competitive bid of $29250 reflecting the scope of work. I'm available to start immediately. Would you like to discuss the project details? I'm happy to jump on a quick call to align on scope. Best regards, Ali

@usmansharif362

Hi, I can build a scalable bot detection and mass-blocking system for X using Python and graph-based analysis. ➤ Data collection pipeline using APIs/scraping (followers, tweets, metadata) ➤ Bot detection logic (account patterns, activity timing, content similarity, ratios) ➤ Network expansion from seed accounts to uncover clusters and hidden links ➤ Graph analysis (networkx) to identify bot clusters and controller/hub accounts ➤ Output CSV/JSON datasets + optional auto-block script and report-ready evidence Approach: I’ll combine rule-based detection + network clustering to improve accuracy and scalability (5k → 50k+ accounts), with clean, well-documented code. Timeline: ➤ Prototype: 3–5 days ➤ Full system: 7–10 days Portfolio: https://www.freelancer.com/u/usmansharif362 Happy to discuss your seed data and build a robust, production-ready detection system.

@Kavita9166

I am Rajesh, a Full-Stack Developer with 10+ years of experience in Python data engineering and network analysis. You’re not just extracting accounts—you’re mapping coordinated behavior at scale and isolating controller nodes behind bot amplification. I’ve built similar pipelines that start from seed accounts, expand via retweet/follow graphs, and surface high-centrality clusters using networkx with pandas-backed processing. I will implement a semi-automated system combining snscrape/Twarc for data collection, pattern-based heuristics (account age, ratios, content similarity), and graph-based clustering to identify dense bot communities and hub controllers. Outputs will be structured (CSV/JSON) with optional auto-block scripting and evidence-ready reporting. This will be optimized for 5k–50k scalability and rapid iteration within your 3–10 day window. I can start immediately and deliver a clean, reliable solution. Thanks, Rajesh Jangid Full-Stack Developer | 10+ Years Experience

@wirework

I have built X/Twitter analysis pipelines using their API and have experience with bot network detection and graph-based clustering. Here is how I would approach this: • Data collection layer using X API v2 — pull follower graphs, tweet timelines, retweet chains, and account metadata from your seed list. Handles rate limits automatically with queuing • Bot scoring engine — multi-signal detection: account age patterns, username entropy, follower/following ratios, tweet timing analysis (coordinated bursts), content similarity (TF-IDF on tweet text for near-duplicates) • Network expansion — from seed bots, map shared follow targets and retweet sources. Use community detection algorithms (Louvain) to find clusters. Identify hub/controller accounts by betweenness centrality • Graph visualization — NetworkX + Pyvis for interactive bot network maps showing clusters and controller nodes • Output — structured CSV/JSON for mass blocking via X API, plus visual report of network topology The system will be modular so you can re-run it as bots evolve or new seeds are identified. How are you currently identifying the initial seed accounts — manual review or do you have a starting list ready?

@zarminagull189

⭐BOT NETWORK DETECTION & NEUTRALIZATION SYSTEM — PYTHON & DATA ENGINEERING⭐ Hey, ➤ I understand you need a scalable system to detect and map bot networks on X (Twitter) starting from a seed list, identify controllers, and produce structured outputs for reporting or mitigation. ✅How I will help: ↪️ Collect account & activity data via X API / snscrape / Twarc ↪️ Detect bots using account metadata, activity patterns, content duplication, and coordination signals ↪️ Expand the network from seed bots to uncover related accounts ↪️ Build graph-based analysis to identify hub accounts and dense clusters ↪️ Export structured CSV/JSON outputs of bots + controllers ↪️ Optionally provide visualization (Gephi) and instructions for automated reporting/blocking ✅DELIVERABLES: ✔️ Working Python scripts / modular pipeline ✔️ Well-documented bot detection logic ✔️ List of identified bots + controllers ✔️ Instructions to run & scale the system ?Estimated Price: 25000 INR (prototype in 3–5 days, full system in 7–10 days) ?Portfolio / Similar Work: https://www.freelancer.pk/u/zarminagull189 ⚫Quick Questions: ❓ Do you want automated blocking included in the first prototype? ❓ Any rate-limiting constraints or preferred API approach (official X API vs scraping)? ✨Scalable, accurate bot detection system ready to map networks and provide actionable outputs. Regards, Zarmina

@Aaron7C

Hi - software engineer with strong Python, data analysis, and API experience. My approach: 1) Collect seed data via X API or twarc/snscrape 2) Score accounts using your heuristics (age, username patterns, follower ratios, timing, duplicate content) 3) Expand network with networkx - shared connections and retweet sources 4) Identify controllers via centrality analysis 5) Deliver CSV/JSON with confidence scores plus optional auto-block script. Important: what X API tier do you have? Free tier makes 5K-50K accounts impractical via API alone. Basic/Pro makes collection straightforward. This significantly affects approach. Being transparent: I have not built a Twitter bot detection system before, but the core components (Python pipelines, pattern classification, graph analysis, API work) are well within my experience. Timeline: 10 days. Happy to discuss.