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Next Proposal
  • The Next Generation Search Engine Proposal
  • Introduction
    • Web Search is Primitive
    • Request for Comments
    • Defining Terms
  • What's Wrong with Web Search?
    • Poor Quality of Search Results
    • Commercial Dominance of the Web
    • Suppression of Better Content
    • Poor Searcher Productivity
    • Lack of Competition
    • Lack of Privacy
  • How We Are Open
    • Radically Open
    • Open Data
    • Open Algorithms
    • Open Finances
  • Your Ownership and Privacy
    • Radical Ownership
    • Private by Default
    • Your Data
  • How We Make Search Better
    • Fixing Stale Results
    • Local First
    • Advanced Features
    • The Trust Network
    • How We Monetize
  • Appendixes
    • Overview
    • Making a Better World
    • Outside Initial Scope
    • History of Web Search
    • The History of Web Search
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On this page
  • Query: History of Search Engines
  • Query: "Best {Product/Service}"
  • Query: "CNN" or "Fox News" or "{Organization Name}"
  • Query: {Medical Topic}
  • Conclusion
  • For Further Consideration

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  1. What's Wrong with Web Search?

Poor Quality of Search Results

The results returned by search engines have improved significantly over prior engines BUT are still abysmal in so many cases. Disagree? Here are a few simple queries you can make to see the poor quality of current search results:

Query: History of Search Engines

Query: History of Search Engines

Results: Notice the results that are outdated, poorly presented, have duplicate content, or are covering SEO rather than search engines properly.

Query: "Best {Product/Service}"

Query: Best {Product/Service}

  • Choose whatever product or service you like - refrigerator, laptop, bed, headphones, etc.

Results:

  • Most reviews come from "big entity" sites - the indie/personal web is missing.

  • It is easy to end up reading the same/similar review on multiple sites before finding unique/helpful content.

  • Some sites are no-name brands that may have questionable practices (e.g., not actually testing products that are reviewed, reviews that drive the viewer to the highest commission generating product).

  • Oftentimes the length of the articles and the details shared are of interest to search engines but unnecessarily verbose for humans.

Query: "CNN" or "Fox News" or "{Organization Name}"

Query: CNN or Fox News or {Organization Name}

Results:

  • Often dominated by the organization itself (not entirely unreasonably).

  • Many organizations (e.g. news) have duplicate content from sites syndicating their content. Do we really want to see the same story from CNN, APNews, and MSNBC?

  • One can use query operators to refine the results (but how many people do you know who use them or are even aware that they exist?).

  • Even if one uses query operators the number of sites that need to be excluded can become quite lengthy and must be recreated for each query.

Query: {Medical Topic}

Query: {Any Medical Topic}

Results: Medical topics, oftentimes of critical importance to the searcher, return notoriously poor results. These results suffer from information that is:

  • Incorrect - Oftentimes sincere, this information is untested and sometimes dangerous.

  • Incomplete - Does not provide enough information for an individual to take informed action.

  • Redundant - A number of larger medical sites provide primarily redundant information regarding the cause, diagnosis, treatment, prospects, etc.

  • Commercial Information - Treatments of questionable value are marketed to individuals at high costs.

Conclusion

We could go on ad nauseum with examples of poor quality search results but we don't want to bore you.

For Further Consideration

PreviousDefining TermsNextCommercial Dominance of the Web

Last updated 4 years ago

Was this helpful?

If you need more examples, .

Keselman A, Arnott Smith C, Murcko AC, Kaufman DR. . Journal of Medical Internet Research 2019;21(2):e11129. DOI: 10.2196/11129.

Jimenez G, Lum E, Car J. . JMIR mHealth and uHealth 2019;7(1):e11848. DOI: 10.2196/11848.

Le H, Maragh R, Ekdale B, High A, Havens T, and Shafiq Z. . Association for Computing Machinery, 2019; 2597-2963. DOI: 10.1145/3308558.3313682.

Metaxa D, Park JS, Landay JA, and Hancock J. . Proceedings of the ACM Human-Computer Interaction 3, CSCW, Article 129 (November 2019), 17 pages. DOI: 10.1145/3359231.

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