The Algorithm Chasers

When the Fort Hood, Texas shooting rampage hit the news, a small staff of news folks were trying to determine which words to use for their online news stories on the topic. The goal was to get Google News to find and rank their article higher than their competition. They struggled with the difference of […]

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When the Fort Hood, Texas shooting rampage hit the news, a small staff of news folks were trying to determine which words to use for their online news stories on the topic. The goal was to get Google News to find and rank their article higher than their competition.

They struggled with the difference of the impact on web site readers for words like “hurt” vs. “injured,” “shot” vs. “shooting,” “deaths vs. “fatalities,” “Fort Hood” vs. “Ft. Hood” and “Texas” vs. “TX”. Would the Google News search engine agree with their choices? What might the reader response be to the words they used to describe the event?

For that feedback, they fired up Twitter to observe trending words. Within five minutes of the actual event itself, Google was not only tracking and ranking social media signals left by internet conversations, but web users themselves were guiding writers towards the correct words to use when they retweeted stories they liked. They linked to those stories in social web sites such as Facebook or forums and blogs related to military news.

Whoever already had an image from Fort Worth got the best prize on Google News, as a picture accompanying an article can increase its chances of ranking higher. As it turned out, the image that was found wasn’t even from the USA where the tragedy occurred. Without a properly optimized image, Google was left on its own to find something based on its own algorithm.

That adrenaline rush, with phone calls and text messages flying out to copy editors and a team following Twitter, researching keyword trends in Google Insights, re-writing headlines and debating word choices is repeated every day. This research brought back archived stories related to the topic. When their coverage was knocked down to a lower spot in search results, they sought out a new angle to try. A news reporter discovered a local person was involved, and that began their new, more exclusive angle for their story. It paid off when they saw their story shoot into the top 3 spots. Even if it didn’t stay there for very long, this was proof to them the power of algorithm chasing.

Semantics vs. emotional factors

Algorithm chasers rely on analytical tools to help understand searcher behavior. They are equipped with keyword data, target market information and demographics. But are they able to determine the emotional power of the written word on web pages? Why is content so vital to search results?

Consider first that search engines do not see colors used in your links, text, or page backgrounds. Web designers put much thought into color choices because they are taught that we react emotionally and physically to color. Perhaps someday search engines may be able to take color codes from cascading style sheets and match the color with known human reactions to them. If so, the algorithms would also need to factor in cultural differences and how that relates to color response. For now, search algorithms are as blind as anyone using assistive technology to read back the words on the screen.

“Semantic reaction” is a term used in Social Intelligence, The New Science of Success by Karl Albrecht. The news team quickly learned that social networking tracking on the web can be a tricky, but fascinating discovery tool. How do you monitor online reactions? As experienced writers, they knew their word choices could be used against them or interpreted in ways they did not intend. This is why headlines are fussed over. We live in a semantic environment, Albrecht points out, filled with shared language habits, traditions, symbols, meanings, implications and countless ways of interacting to make ourselves understood.

Relevancy and user language

In her wonderfully clear and easy to read book When Search Meets Web Usability, Shari Thurow brings up a good point about relevancy. “Reflecting the users’ language in the text of a web page in the areas commonly scanned and also on the search engine results pages will help users,” she wrote.

Designers use boldface, italics, larger fonts, color choices, borders and much more to attract attention to words, but user motivation is focused on the meaning, relevancy and emotion behind those words. The incentive behind algorithm chasers is to drive traffic to revenue generating web pages and to know that, search engines seek out what’s relevant to users and what motivates them to click, read or link. Not only are articles and headline writers interested in finding searchable phrases, but so too are those who write text ads and call to action links.

The excitement of watching Google News respond in near “real time” with each page refresh opened the eyes of the news people. They had no idea that their headlines, archives, headlines and page copy were so important to search engines, social networking sites and web users who stay on top of the latest news. The battle for the best story was not only being fought by them but also by other news teams who understand search engine optimization and how user experience assists them. Their tools consisted of keyword research, traffic data and listening for hot topics from social conversation signals found on the web.

They learned that today’s search engine algorithms are more complex than their mathematical equations. From now on, how, where and what web site visitors respond to counts as well.

Contributing authors are invited to create content for Search Engine Land and are chosen for their expertise and contribution to the search community. Our contributors work under the oversight of the editorial staff and contributions are checked for quality and relevance to our readers. The opinions they express are their own.

About the author

Kim Krause Berg
Kim Krause Berg is the SEO/Usability Consultant for Cre8pc. Her work combines website and software application usability testing with a working knowledge of search engine optimization.

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