[Originally posted to the Headshift blog last Friday]
Most owners of social software systems use the data generated through usage in their reporting of metrics. So, alongside the standard metrics such as unique users, page impressions, time spent, etc, social tools often enable actions which can also be counted and reported, such as registrations, content submissions, comments generated by that content, etc. The data generated by social activities can also be useful in identifying key gatekeepers within online communities, or relationships that wouldn't otherwise be apparent. Headshift does this sort of analysis for a growing number of clients, and one of our case studies describes a project we did with the BBC to better understand that people who comment on a BBC Blog is likely to also post comments on other BBC blogs.
Usage data can also make for compelling content. An example that many are likely to be familiar with are Amazon's "Frequently Bought Together" and "What Do Customers Ultimately Buy After Viewing This Item" features, which use data on what users view and purchase to make better recommendation. Many news and media sites are also waking up to the value of exposing data generated by the behaviour and actions of users to, for example, highlight the "most read" and "most emailed" pieces of content.
Today I came across Facebook's Peace Project which turns user behaviour into genuinely interesting content. The project looks at user profile data on location, religion and political stance and ties it to data generated when users add each other as friends to provide in interesting glimpse at friendships that cross unlikely geographic, political or religious boundaries. So, for example, in the graph below we can see that, over the proceeding 24 hours, 5,085 friendships were confirmed by users in Israel and those in Palestine:
- within enterprise systems, behavioural data can be used to better understand how organisations function, and how emergent practice is, or isn't, supported by existing bureaucratic structures
- consumer and audience behaviour can be used, as seen above and as I wrote yesterday in my post about Twitter Times, to make user centred content recommendations or to gauge, as we're finding in a current Headshift project, customer inquiries about products or services so that resources can be better deployed in responding
- public officials could use such data to pinpoint resources at emerging areas of interest or need – google has been doing interesting work on this, creating a swine flu map based on searches
We're only at the tip of the iceberg when it comes to making best use of the data that is generated by user participation using social tools but things are starting to get very interesting indeed.