Spamdexing (a portmanteau of spamming and indexing) refers to the practice on the World Wide Web of deliberately modifying HTML pages to increase the chance of them being placed high on search engine relevancy lists. People who do this are called search engine spammers. In layman’s terms, spamdexing is using unethical means known as “black hat seo techniques” to unfairly increase the rank of sites in search engines. When a website is optimized to be indexable by a search engine, without trying to deceive its web crawler, this is called search engine optimization. To be sure, there is much gray area between white-hat search engine optimization and black-hat spamdexing.

Blog, wiki, guestbook, and referrer spam

Google’s PageRank system uses the number of links to a page as an index of its “importance”. Ordinarily, very few pages will link to a spammer’s commercial site, because it is of no interest to anyone else, and hence it will have a very low PageRank score. To counter this effect, spammers attempt to create links to their sites on other people’s pages.

The most common targets for this kind of spam are weblogs, the spamming then being known as blog spam, or “blam” for short. In 2003, this type of spam took advantage of the open nature of comments in the blogging software Movable Type by repeatedly placing comments to various blog posts that provided nothing more than a link to the spammer’s commercial web site. [3]

Similar attacks are often performed against wikis and guestbooks, both of which accept user contributions; something that consistantly impresses and confounds critics of Wikipedia is its remarkable lack of spam, in spite of having nearly one million articles and over two million pages.

On January 18, 2005, Google proposed a rel="nofollow" attribute that could be placed on a link; doing so instructs most major search engines to ignore the link, rendering it useless to spammers. Software is then rewritten to add this attribute to any link embedded in a comment. As of April 2005, nofollow has seen expanding usage, but is not yet universal. [4]

As well as comment forms, editable pages and guestbooks, some sites publish a list of the most common referrers to their site in order to show how readers have found it. These lists have also been exploited by spammers with so-called referer spam, in which the spammer makes repeated web site requests using a fake referer URL pointing to a spam-advertised site. That URL will later appear as a link on the site, boosting the PageRank of its target.

This guide is licensed under the GNU Free Documentation License. It uses material from the Wikipedia.

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Google was started by two PhD students at Stanford University, Sergey Brin and Larry Page, and brought a new concept to evaluating web pages. This concept, called PageRank, has been from the start important to the Google algorithm [1]. PageRank relies heavily on incoming links and uses the logic that each link to a page is a vote for that page’s value. The more incoming links a page had the more “worthy” it is. The value of each incoming link itself varies directly based on the PageRank of the page it comes from and inversely on the number of outgoing links on that page.

With help from PageRank, Google proved to be very good at serving relevant results. Google became the most popular and successful search engine. Because PageRank measured an off-site factor, Google felt it would be more difficult to manipulate than on-page factors.

But manipulated it was. Webmasters had already developed link manipulation tools and schemes to influence the Inktomi search engine. These methods proved to be equally applicable to Google’s algorithm. Many sites focused on exchanging, buying, and selling links on a massive scale. PageRank’s reliance on the link as a vote of confidence in a page’s value was undermined as many webmasters sought to garner links purely to influence Google into sending them more traffic, irrespective of whether the link was useful to human site visitors.

It was time for Google—and other search engines—to look at a wider range of off-site factors. There were other reasons to develop more intelligent algorithms. The Internet was reaching a vast population of non-technical users who were often unable to use advanced querying techniques to reach the information they were seeking and the sheer volume and complexity of the indexed data was vastly different from that of the early days. Search engines had to develop predictive, semantic, linguistic and heuristic algorithms.

A proxy for the PageRank metric is still displayed in the Google Toolbar, but PageRank is only one of more than 100 factors that Google considers in ranking pages.

Today, most search engines keep their methods and ranking algorithms secret. A search engine may use hundreds of factors in ranking the listings on its SERPs; the factors themselves and the weight each carries may change continually.

Much current SEO thinking on what works and what doesn’t is largely speculation and informed guesses. Some SEOs have carried out controlled experiments to gauge the effects of different approaches to search optimization.

The following, though, are some of the considerations search engines could be building into their algorithms, and the list of Google patents [2] may give some indication as to what is in the pipeline:

• Age of site
• Length of time domain has been registered
• Age of content
• Regularity with which new content is added
• Age of link and reputation of linking site
• Standard on-site factors
• Negative scoring for on-site factors (for example, a dampening for sites with extensive keyword meta tags indicative of having being SEO-ed)
• Uniqueness of content
• Related terms used in content (the terms the search engine associates as being related to the main content of the page)
• Google Pagerank (Only used in Google’s algorithm)
• External links, the anchor text in those external links and in the sites/pages containing those links
• Citations and research sources (indicating the content is of research quality)
• Stem-related terms in the search engine’s database (finance/financing)
• Incoming backlinks and anchor text of incoming backlinks
• Negative scoring for some incoming backlinks (perhaps those coming from low value pages, reciprocated backlinks, etc.)
• Rate of acquisition of backlinks: too many too fast could indicate “unnatural” link buying activity
• Text surrounding outward links and incoming backlinks. A link following the words “Sponsored Links” could be ignored
• Use of “rel=nofollow” to suggest that the search engine should ignore the link
• Depth of document in site
• Metrics collected from other sources, such as monitoring how frequently users hit the back button when SERPs send them to a particular page
• Metrics collected from sources like the Google Toolbar, Google AdWords/Adsense programs, etc.
• Metrics collected in data-sharing arrangements with third parties (like providers of statistical programs used to monitor site traffic)
• Rate of removal of incoming links to the site
• Use of sub-domains, use of keywords in sub-domains and volume of content on sub-domains… and negative scoring for such activity
• Semantic connections of hosted documents
• Rate of document addition or change
• IP of hosting service and the number/quality of other sites hosted on that IP
• Other affiliations of linking site with the linked site (do they share an IP? have a common postal address on the “contact us” page?)
• Technical matters like use of 301 to redirect moved pages, showing a 404 server header rather than a 200 server header for pages that don’t exist, proper use of robots.txt
• Hosting uptime
• Whether the site serves different content to different categories of users (cloaking)
• Broken outgoing links not rectified promptly
• Unsafe or illegal content
• Quality of HTML coding, presence of coding errors
• Actual click through rates observed by the search engines for listings displayed on their SERPs
• Hand ranking by humans of the most frequently accessed SERPs

This guide is licensed under the GNU Free Documentation License. It uses material from the Wikipedia.

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SEO began in the mid-1990s, as the first search engines were cataloging the early Web. Initially, all a webmaster needed to do was submit a site to the various engines which would run spiders, programs to “crawl” the site, and store the collected data. The search engines then sorted the information by topic, and served results based on pages they had spidered. As the number of documents online kept growing, and more webmasters realized the value of organic search listings, so popular search engines began to sort their listings so they could display the most relevant pages first. This was the start of a search engine versus webmaster game that continues to this day.

At first search engines were guided by the webmasters themselves. Early versions of search algorithms relied on webmaster-provided information such as category and keyword meta tags. Meta tags provided a guide to each page’s content. When some webmasters began to abuse meta tags, causing their pages to rank for irrelevant searches, search engines abandoned their consideration of Meta tags and instead developed more complex ranking algorithms, taking into account factors that were more diverse, including:

• Text within the title tag
• Domain name
• URL directories and file names
• HTML tags: headings, bold and emphasized text
• Keyword density
• Keyword proximity
• Alt attributes for images
• Text within NOFRAMES tags

By relying so extensively on factors that were still within the webmasters’ exclusive control, search engines continued to suffer from abuse and ranking manipulation. In order to provide better results to their users, search engines had to adapt to ensure their SERPs showed the most relevant search results, rather than useless pages stuffed with keywords by unscrupulous webmasters. This led to the rise of a new kind of search engine.

This guide is licensed under the GNU Free Documentation License. It uses material from the Wikipedia.