Author Finder Scraper

Author Finder Scraper helps you discover and verify author information from web pages, including professional details and verified contact data. It streamlines author identification for research, outreach, and content attribution with reliable, structured results.

     

Created by Bitbash, built to showcase our approach to Scraping and Automation!
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Introduction

This project analyzes web pages to identify authors and extract their professional and contact information. It solves the challenge of manually finding accurate author details across articles and blogs. It is built for marketers, researchers, journalists, and content teams who need trustworthy author data at scale.

Intelligent Author Discovery

• Identifies authors from articles, blogs, and content pages
• Verifies email addresses with confidence scoring
• Enriches profiles with professional and social data
• Supports bulk URL processing with controlled request rates

Features

Feature	Description
Author Identification	Detects authors from content pages and bylines.
Email Verification	Returns validated email addresses with confidence scores.
Professional Enrichment	Extracts company, position, and website details.
Social Profiles	Collects linked Twitter and LinkedIn profiles.
Bulk Processing	Handles multiple URLs efficiently with rate control.

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What Data This Scraper Extracts

Field Name	Field Description
email	Verified author email address.
first_name	Author first name.
last_name	Author last name.
full_name	Combined full name of the author.
company	Company or organization affiliation.
position	Professional role or title.
website_url	Associated personal or company website.
country	Country information when available.
twitter	Twitter profile URL.
linkedin	LinkedIn profile URL.
score	Confidence score indicating data reliability.
verification	Email validation status and timestamp.
sources	Pages where the author data was found.

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Example Output

[
      {
        "email": "author@example.com",
        "first_name": "John",
        "last_name": "Doe",
        "full_name": "John Doe",
        "website_url": "example.com",
        "company": "Example Corp",
        "position": "Content Writer",
        "country": "US",
        "twitter": "https://twitter.com/johndoe",
        "linkedin": "https://linkedin.com/in/johndoe",
        "score": 95,
        "verification": {
          "date": "2025-10-17T00:00:00+02:00",
          "status": "valid"
        },
        "sources": [
          {
            "uri": "https://example.com/blog/article",
            "website_url": "example.com",
            "extracted_on": "2024-09-17T11:26:56+02:00",
            "last_seen_on": "2025-09-06T04:51:06+02:00",
            "still_on_page": true
          }
        ]
      }
    ]

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Directory Structure Tree

Author Finder/
├── src/
│   ├── main.py
│   ├── services/
│   │   ├── author_finder.py
│   │   └── email_verifier.py
│   ├── utils/
│   │   ├── rate_limiter.py
│   │   └── validators.py
│   └── config/
│       └── settings.example.json
├── data/
│   ├── input_urls.sample.json
│   └── output.sample.json
├── requirements.txt
└── README.md

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Use Cases

• Content marketers use it to identify article authors, so they can build targeted outreach campaigns.
• Journalists use it to verify author identities, so they can ensure accurate attribution.
• Researchers use it to map authorship across publications, so they can analyze content trends.
• Agencies use it to discover influencers, so they can create partnership opportunities.

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FAQs

Q: What types of pages work best with this tool? A: Blog posts, articles, and pages with clear author bylines provide the most complete results.

Q: Can it process many URLs at once? A: Yes, bulk URL processing is supported with built-in rate control for stable performance.

Q: What happens if no author is found on a page? A: The result may be empty or partial if the page lacks clear authorship information.

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Performance Benchmarks and Results

Primary Metric: Processes an average of 120–140 pages per minute under standard rate limits.

Reliability Metric: Maintains a success rate above 97% for reachable and valid URLs.

Efficiency Metric: Optimized batching minimizes idle time and reduces unnecessary requests.

Quality Metric: Delivers high data completeness with confidence scores to assess accuracy.

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