Just as the gravediggers were readying Digg on their to-do list, Facebook came to the company’s rescue, adding a Digg Social Reader application to Timeline. January saw Facebook referral traffic for the company increase 67 percent, while Digg’s pageviews also jumped 35 percent.
The company saw its highest traffic numbers since January of 2010, Digg’s software engineer Will Larson reported in a blog post recently.
Digg also introduced the Open Graph application in December, which works similar to the Yahoo Social Bar or the Washington Post Social Reader. Hooking into Facebook Twitter and Timeline, the app enables automatic sharing of Digg-reading activities with friends.
Though Digg was once a revered site for sharing news stories throughout the blogosphere at its launch in 2004, the company has suffered greatly these last several years due to competition from online news readers such as Reddit and users simply sharing on social networks like Facebook and LinkedIn.
Whether users really need a particular site to “Digg” when social networks are turning the web into a virtual sandcastle as endless as the beach remains to be seen. Nevertheless, the geeks at Digg took the opportunity of increased traffic to analyze what people are sharing and what they actually read.
“Stories that readers add to their Facebook Timeline closely resemble what you might talk about at a party or when grabbing a drink with your co-workers,” Larson wrote. “Headlines are usually pretty safe topics— not politics, religion or anything that might cause debate. In order, they’re most likely about technology, offbeat news and world events.”
People tend to read politics and fluff entertainment more than they’re likely to share, Digg found.
“Entertainment stories were 14 percent of all stories read but less than 4 percent of those added to the Timeline,” Larson wrote. “Likewise, political stories comprise less than 2 percent of those added to a user’s Timeline but close to 10 percent of what people read. The differences are significant enough to begin to predict a new type of reading behavior.”