Publishers are generally compelled to make their media available and easy to find to everyone, everywhere. Meanwhile each output calls for a different format and tone of voice, and has different user expectations and interests.
Recreating and repackaging content for every possible output – from mobile to desktop, Snapchat to Twitter, digital to print – has become untenable. Turns out distributing content can be a drain.
Publishers need to find a better way of delivering their content to the readers that are going to be most receptive. Enter ‘social graphing’.
This is a tool publishers can use to make their content distribution more intelligent, efficient and effective. The ability to analyse the social graph, directly observing communities that people self-organize into and the clusters of interests and beliefs within them, are powerful weapons for getting the right media and messages to the right people – a core need for publishers and their advertisers.
In the simplest of terms, a social graph is nothing more than an illustration of relationships between people on the internet. You might even think of it as the internet version of a family tree. Social graphing (part the larger practice of social network analysis) uses data science to analyze and map social networks in order to better understand the relationship between users, and further, to illustrate the manifestation of communities.
Due to the many promising applications of social graphing, James Slezak, managing partner and founder of New Economy Lab says data scientists have been working to crack it for years. “And I think it’s starting to show some interesting signs of opportunity for people.”