News Patterns Discovery - The Disciplined Enabling of Serendipity

On April 5, 2010 L. Gordon Crovits wrote this article in the Wall Street Journal: The Search for Serendipity. At the time that I read this article I was nodding in agreement with this particular passage in the article:

The challenge for modern information consumers becomes: How do you discover what you don't know you want to know?

Old-time print journalists bemoan the absence of serendipity—the accidental discovery of stories that readers didn't know they were interested in reading. In the words of a recent blog post at the Nieman Journalism's Lab site, "While there is more news on the web, our perspectives on the news are narrower because we only browse the sites we already agree with, or know we already like, or care about." With newspapers, by contrast, readers discover "things we didn't care about, or didn't agree with, in the physical act of turning the page."

Part of the reason that we browse that which we are comfortable is because we as humans have a very low input bandwidth when measuring the amount of information that we can input to our conscious minds by reading. In fact this reading input rate is in the range of 200 bits per second. Consider this 200 bits per second as glacially slow when considering that our minds input graphical information at the rate of 10,000,000 bits per second. There is little wonder why we soon fatigue when exposed to the huge volumes of text news information that are at the other ends of search queries and alerts. By returning to sites that we agree with, as stated by Nieman Journalism lab, we are actually employing a strategy of using scarce information input bandwidth. It takes far less energy to read something with which we agree, than information that challenges our beliefs.

In our News Patterns world, we enable greater serendipity by converting large volumes of news information into graphical patterns. It is the visual pattern that incites the interest of our users. By intention, some patterns look threatening, new, and unexpected. Once a pattern has earned the attention of our users, he/she can easily drill beneath the surface to the actual news articles defining the graphical pattern. Like scanning a news paper, News Patterns users scan large volumes of news data, quickly bypassing some information while focusing on others, all without a forced reading of too many individual article details.

With such a graphical scanning process supported by algorithmic patterning processes that discover patterns of probable interest to our users, we empower them to a superior situational awareness of the here and now, and enable them to transcend comfortable sources with discovery or serendipity.