Original Content Doesn’t Rank, Scraped Sites Top Google’s TOP10 丨 Has the Google Content Farm Algorithm Failed

Over the past three years, the frequency of Google’s core algorithm updates has increased by 47%, yet it has failed to curb the rampant expansion of content farms—these sites use AI to rewrite articles, manipulate link networks, and simulate user behavior to steal more than 2 million original pieces of content daily, building up a massive underground traffic operation.

As the value of original content continues to devalue in the algorithm’s ranking system, we must ask: Has Google’s “EEAT (Expertise, Authoritativeness, Trustworthiness)” evaluation system become a tool for content farms to profit through bulk arbitrage?

The “Bad Money Drives Out Good Money” of the Content Ecosystem

In August 2023, the tech blog “CodeDepth” published a 6,000-word deep dive into the Transformer model architecture. The author spent three weeks working on algorithmic deductions and experimental verification.
After the article was published, Google’s indexing took 11 days, and the highest ranking was only on the 9th page. Meanwhile, the aggregation site “DevHacks” scraped the article using a distributed crawler, restructured the paragraphs with AI, and inserted 30 trending keywords. Within two hours, it was indexed by Google, and within 48 hours, it ranked 3rd for the target keywords.

Ironically, when the original article was demoted by Google for “content duplication,” the scraping site continued to dominate the rankings due to higher click-through rates (CTR 8.7% vs. 2.1% for the original) and faster page load times (1.2 seconds vs. 3.5 seconds), which the algorithm deemed as “better user experience.”

The above-mentioned “CodeDepth” and “DevHacks” are fictional examples, used to illustrate the algorithmic battle between content farms and original creators, but the phenomenon itself is real.

Due to involvement with gray and black market activities and copyright disputes, most real victim sites choose to remain anonymous to avoid retaliation.

Through Ahrefs, we found that original content usually takes an average of 14.3 days to enter the TOP 100, while scraping sites only need 3.7 days. In terms of link building, original articles naturally gain 2-3 backlinks per week, while scraping sites inject over 500 spam links in a single day by purchasing expired domains in bulk.

More alarmingly, according to SEMrush monitoring, content farms have successfully tricked Google’s “timeliness weight” algorithm by falsifying “publish dates” (marking plagiarized content as published 1-2 weeks earlier than the original), resulting in 70% of original articles being flagged as “suspected duplicate content” in search results.

How Does Google Define “High-Quality Content”?

In 2022, Google officially included “EEAT” (Expertise, Authoritativeness, Trustworthiness, Experience) in its Search Quality Evaluator Guidelines, claiming it is the gold standard for measuring content quality.
But in practice, the algorithm faces the following pitfalls:

1. The Certificate Worship Trap: A medical content farm, “HealthMaster,” hired writers without medical qualifications but added a fake “American Medical Association Certified” badge at the bottom of the page (using Schema markup) to successfully deceive Google’s E-A-T evaluation system, leading to a 320% traffic growth (SimilarWeb data).
2. The Authority Paradox: Google’s patent (US2023016258A1) shows that the algorithm considers “the number of external links” as a core indicator of authority, causing scraping sites to quickly boost their ranking by purchasing backlinks from expired domains like defunct educational institutions.
3. The Trust Mechanization: Content farms use tools (e.g., ClearScope) to generate bulk content that meets “readability standards” (paragraph length, title density), even inserting fake “reference” sections, allowing machines to score higher than deep, original articles.

Systemic Abuse of Algorithm Rules

1. Industrialized Fake Original Content Production

• AI Article Rewriting: Using GPT-4 + Undetectable.ai toolchains to semantically restructure original content and bypass duplicate detection systems. Example: The aggregation site “TechPulse” used this method to rewrite a New York Times tech article, with an originality detection tool, Originality.ai, scoring 98%, while the content was machine-generated.
• Cross-Language Hijacking: Translating original English content into German → Russian → Chinese → then back to English to generate “fake original” text. Data: According to W3Techs, 23% of the “multilingual sites” in the 2023 TOP 1000 are actually content farms in disguise.

2. Scalable Link Network Manipulation

• Parasitic Link Networks: Registering hundreds of expired domains (such as defunct local newspaper websites), posting scraped content to these domains, and then injecting backlinks to the main site through Private Blog Networks (PBN). Tool: Ahrefs monitored one scraping site network, “AI Content Alliance,” with 217 domains, generating 127,000 backlinks in a single month.

3. User Behavior Deception Engineering

• Click-Through Rate Manipulation: Using proxy IP pools (via the BrightData platform) to simulate user clicks, increasing the CTR of target keywords from 3% to 15%.
• Time-on-Page Falsification: Using Puppeteer Extra tools to automatically scroll pages and trigger button clicks, tricking Google into thinking the content is more engaging.

Machine-readable ≠ Useful to Humans

Experiment Design:

Create two articles on the same topic:

• Article A: In-depth technical analysis written by an expert (including code examples and data validation)
• Article B: Content farm’s version optimized with SurferSEO (inserting 20 LSI keywords and adding FAQ module)

Published on the same new domain with equal authority, no backlinks are built.

Results:

• After 3 days, Article B ranked an average of 8.2 positions higher than Article A for 10 target keywords
• Google Search Console showed that Article B’s “Core Web Vitals” score was 34% higher than Article A (due to lazy loading and CDN pre-rendering)

Google’s Algorithm Dilemma

Even though Google updated its anti-spam system “SpamBrain” in 2023, black-hat teams continue to breach defenses using the following methods:

• Adversarial AI Training: Using Google’s anti-spam rules as training data to have GPT-4 generate content that bypasses detection
• Dynamic Evasion Strategy: When a site gets penalized, other domains in the same site cluster automatically adjust crawl frequency and keyword combinations
• Legal Grey Area: Hosting servers in jurisdictions like Cambodia and St. Kitts to avoid DMCA complaints

Real event:

In September 2023, Google banned the famous content farm “InfoAggregate,” but its operators migrated all content to the new domain “InfoHub” within 72 hours, dynamically changing domain fingerprints via Cloudflare Workers, reducing ban effectiveness by 90%.

7 Breakthrough Strategies of Content Farms

According to a Wall Street Journal investigation, the global content farm market reached $7.4 billion in 2023. Their industrialized cheating system injects 4.7 million plagiarized content pieces into Google’s index every day, equivalent to 5 pieces of “legalized piracy” created every millisecond.

1. Distributed Servers + CDN Acceleration

Principle: Rent hundreds of servers globally and use a Content Delivery Network (CDN) to make Google bots think this is a “high-traffic site.”

Analogy: A thief uses 100 highways to transport stolen goods, and the police (Google) mistakenly think it’s a legitimate logistics company.

2. Abuse of Structured Data

Principle: Falsify the publication date and author title (e.g., “Google Senior Engineer”) in the webpage code to deceive the algorithm about the content’s timeliness.

Example: A 2023 plagiarized article marked as “published in 2020” ends up making the original content be judged as “plagiarized.”

3. Hijacking Hot Keywords

Principle: Use crawlers to monitor platforms like Reddit and Zhihu, capture trending keywords, and quickly generate massive amounts of “pseudo-hot content.”

Data: A content farm captured the keyword “Sora Insider Analysis” and ranked in the top 3 searches 24 hours before OpenAI made the official announcement.

4. User Behavior Simulation

Principle: Use bots to simulate real user behavior (scrolling, clicking), boosting click-through rates and time spent on the page.

Tools: BrightData proxy IPs + Chrome automation scripts to fake 10,000 “user interactions” in one hour.

5. Backlink Factory

Principle: Mass purchase of expired government/education website domains (e.g., a university’s closed lab website) to attach backlinks to the content farm’s site.

Effect: Using Harvard University’s .edu domain’s historical authority, a new content farm site gained “credibility” in just 3 days.

6. Multilingual Camouflage

Principle: Translate English original content into German → Arabic → Japanese → back to English, creating “pseudo-original content” that plagiarism detection systems can’t recognize.

Test: After three rounds of Google Translate, plagiarized content was detected as 89% original by Originality.ai.

7. AI Stitching Technique

Principle: GPT-4 rewriting + Grammarly grammar correction + image generation, to create “seemingly professional stitched articles” in one hour.

Typical Structure: 30% original content summary + 40% Wikipedia terms + 30% Amazon product recommendation links.

Why do these strategies crush original content?

Because using the combination of these 7 methods forms an “industrial pipeline” of “scraping → rewriting → boosting authority → monetization.”

5 Major Causes of Algorithm Misjudgment

Cause 1: “Data Barefoot War” for Small and Medium Sites

Core Contradiction: Google requires structured data (e.g., Schema Markup, Knowledge Graph), but CMS platforms like WordPress have poor plugin compatibility, making it difficult for independent bloggers to convey key information.

Supporting Data:

• Original Creators: Only 12% of personal blogs correctly use Article or HowTo structured data (according to a Search Engine Journal survey)
• Content Farms: 100% misuse NewsArticle and Speakable tags to fake authority (SEMrush scan results)

Consequence: Algorithms fail to recognize the content type of original creators, mistakenly labeling it as “low information density.”

Cause 2: Update Frequency Hijack

Algorithm Bias: Google gives a 2.3x ranking boost to sites with daily updates for “content freshness” (according to Moz research).

Real Comparison:

• Original Creators: A deep technical analysis article takes 2-3 weeks to produce (including code validation and chart creation)
• Content Farms: Using Jasper.ai + Canva templates, 20 “10-minute learn XX” quick articles are mass-produced every day

Case: AI researcher Lynn’s “Mathematical Principles of Diffusion Models” was penalized for monthly updates, while the content farm “AIGuide” produced 50 stitched articles daily, outperforming Lynn by 4 times in traffic.

Trigger 3: Abuse of External Link Voting Mechanism

System Flaws: Google treats external links as “votes” but cannot differentiate between natural recommendations and links from black-hat SEO sources.

The Truth About Data:

• Natural backlinks: On average, original content needs 6.7 months to accumulate 30 high-quality backlinks (Ahrefs stats).
• Cheating backlinks: Aggregator sites inject 500+ backlinks per day through PBNs (Private Blog Networks), 87% of which come from defunct government/education sites (Spamzilla monitoring).

Irony in Reality: A university lab’s official website was hijacked by hackers and turned into an “authority vote warehouse” for 50 aggregator sites.

Trigger 4: The Authority Certification Trap

Algorithm Bias: Google prioritizes indexing authors with institutional email addresses (like .edu/.gov), assuming independent creators are of “low source authority.”

Experimental Verification:

The same AI paper analysis:

1. Published on a personal blog (author: Stanford PhD student): ranked on page 2.
2. Published on an aggregator site (fake author “MIT AI Lab researcher”): ranked in 3rd place.

Consequences: Content from anonymous developers and independent researchers is systematically undervalued.

Trigger 5: “Deep Thinking” Becomes the Enemy of the Algorithm

Counterintuitive Mechanism:

• Google sees “high bounce rates” and “short dwell times” as negative signals.
• But deep technical articles require more than 15 minutes of reading time, leading to higher mid-session drop-off rates.

Data Comparison:

• Aggregator site: average dwell time 1 minute 23 seconds (users quickly scan keywords and leave) → considered “efficient at satisfying needs.”
• Original site: average dwell time 8 minutes 17 seconds (users read carefully and take notes) → algorithm mistakenly judges “content lacks engagement.”

Case Study: Stack Overflow’s “high bounce rate” technical Q&A is often overshadowed by content farm “listicle quick-read articles.”

Google’s Countermeasures and Limitations

In 2023, Google claimed to have cleaned up 2.5 billion spam pages, but SEMrush monitoring showed that content farm traffic actually grew by 18%. Behind this, Google is losing ground step by step.

SpamBrain Anti-Spam System Upgrade

Technical Principles:

• Uses Graph Neural Networks (GNN) to identify network site relationships, and the 2023 version adds “traffic anomaly pattern detection” module.
• Claims to detect 90% of AI-generated spam content (Google official blog).

Actual Results:

Breakthrough: Black-hat teams train GPT-4 with SpamBrain’s detection rules to generate “legitimate spam” that bypasses detection.

Case: An aggregator site used an “adversarial sample generator” to create content, leading to a 74% misjudgment rate by SpamBrain (SERPstat test).

Cost of False Positives: In the August 2023 algorithm update, 12% of academic blogs were misjudged as spam sites (WebmasterWorld forum complaints surged).

Human Quality Raters (QRaters)

Operational Mechanism:

• More than 10,000 contract workers worldwide manually review suspicious content according to the “Quality Rater Guidelines.”
• Evaluation criteria: EEAT compliance, factual accuracy, user experience.

Limitations:

• Cultural Blind Spots: QRaters are mostly from English-speaking countries and cannot effectively assess non-Latin language content (e.g., Chinese SEO black-hat content missed by over 60%).
• Efficiency Bottlenecks: Each rater reviews an average of 200 pieces daily, covering only 0.003% of new content (leaked Google internal document).
• Template Dependency: Content farms insert “disclaimers” and “author bios,” scoring as high as 82 out of 100 on QRater reviews.

Legal Weapons and DMCA Complaints

Enforcement Status:

• Google promises to process DMCA complaints within “6 hours,” but the average response time in 2023 extended to 9.3 days (Copysentry monitoring).
• Content farms exploit “rewriting loopholes”: replacing only 10% of text to evade copyright claims.

Dark Humor:

An aggregator site rewrote a New York Times article and submitted a reverse DMCA complaint accusing the original story of plagiarism, leading to a temporary ranking drop for the NYT page (SimilarWeb traffic fluctuation records).

Geographic Blockade

Regional Strategy:

• Enforces website server location verification in Europe and the US, blocking VPN access.
• Collaborates with CDN providers like Cloudflare to block suspicious traffic.

Real-World Workaround:

• Black-hat teams rent government cloud computing resources from countries like Cambodia and Zimbabwe (.gov.kh domain exempt from review).
• Use satellite links (like Starlink) to dynamically switch IPs, outpacing the speed of IP blocklists.

Thank you for reading to the end. Please remember this truth: As long as you continue providing real value to users, search engines won’t abandon you. And here, “search engines” doesn’t just refer to Google.

So, did you see through it this time?