Software tells Bloggers What Readers Want
Blogging often sounds like a great idea: sharing thoughts and expertise, becoming a part of a community, and taking the first few steps to wider recognition as a writer. But many bloggers quickly get disillusioned.
IBM’s internal records show, for example, that only three percent of the company’s employees have posted to a blog at all. Of those who have, 80 percent have posted only five times or fewer. Many of the people interviewed for the study say they stopped blogging–or never got started–because they didn’t think anyone would read their posts.
In an effort to fix this problem, IBM researchers have been experimenting with a tool called Blog Muse, which suggests a topic for a blog post with a ready-made audience.
“We saw this disconnect between readers and writers,” says Werner Geyer, a researcher at IBM’s center for social software in Cambridge who was involved with the work. The writers surveyed often weren’t sure how to interest readers, and many of their posts got little to no response. Readers, on the other hand, couldn’t find blogs on the topics they wanted to read about.
So Geyer and his colleagues built a widget to bring these two halves of the problem closer together. Readers use the widget to suggest topics they want to read about, and they can vote in support of existing suggestions. Those suggestions then get sent to possible writers, matching topics to writers by analyzing his social network connections and areas of expertise.
The researchers found that writers were most likely to post on a topic suggested by a sizeable audience, and that audience members followed up by read posts on requested topics. Blog posts resulting from the system also received about twice as many comments, three times as many ratings, and much more traffic, says Casey Dugan, another researcher at IBM’s Cambridge center.
The effort didn’t substantially increase the quantity of posts however. The researchers speculate that this is because users who planned to write blog posts anyway simply chose suggested topics rather than coming up with their own.
The researchers want to do a larger, longer-term deployment of the original tool (their research was done over four weeks with 1,000 users). And they plan to present their results in April at the ACM Conference on Human Factors in Computing Systems in Atlanta, GA.
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