Content Will Always Be King Among News Creators

News Patterns has been a pioneer in the realm of discovery for over eight years. In my next blog I will give a detailed description of discovery versus search. This blog post will first set the stage defining the different types of news content creators.

Expert and Community Content are obvious to most information professionals.  Simply stated, Expert Content is created by authors and organizations whose business is to professionally inform target audiences either as subscriptions or advertising driven business models.  Community Content is the socially driven content that creators write or record as part of relationships with other community members.

Machine Content is often not considered, but nonetheless invaluable in the news content universe.  Machine content essentially synthesizes new content with algorithms and database processes out of original content from Experts and Communities.  Here are some examples of machine content:

• Search indices with built in relevancy  (made famous by Google and "page rank")
• Aggregation pioneered by LexisNexis and Factiva
• Low latency feeds that supply instant stock trading black boxes
• Media monitoring dash boards that track public relations interests
• News Patterns Discovery - algorithmic pattern seeking of trends or events of competitive interest  (More on this in next blog addition.)

The above venn diagram illustrates that there are many overlaps among the news content categories.  Here are some examples:

• Expert journalists often search machine Google as part of researching articles.
• Members of community Twitter often notify their followers of interesting expert articles.
• Public relations professionals use their machine media monitoring dashboards of expert and community content to research their next press release.
• Expert journalist use community Facebook as an alternative mode of article distribution.
• Community LinkedIN redistributes expert articles in an attempt to increase site page views
• etc.

I have several concluding thoughts:

• Expert and Community content could operate as viable, and independent categories.
• Machine Content is completely dependent on Expert and Community Content.
• Simple forms of machine content (as in better searches and monitoring analytics) can easily be adopted by expert and community content creators; whereas the reverse of expert or community content cannot be readily created by the machine content category.  Therefore for machine content creators to maintain their market viability, they must be increasingly innovative in the user value that they add to the "content is king" news universe.