The Science Behind Inbox Influencer

Posted in Inbox Influencer, Influence, Social Influence Marketing by Chris Selland on February 2nd, 2012
 

As our base of Inbox Influencer users continue to grow, we are getting many questions regarding how we drive relevance – and make suggestions based on not just how generally ‘influential’ someone is, but also what they communicate about and to whom.

Toward that end, we thought we’d share this post from our own Tim Hastings – Reputation (trust) vs. User Interest (ego) (TagWalk blog) who talks about the concept of deriving relevance from social media.

“When trying to find interesting people online, it is useful to be able to differentiate between somebody who is very interested in a particular subject from somebody who has a good reputation for that subject.”

Inbox Influencer leverages algorithms used in our flagship product, Optimizer for Twitter, for finding “who to follow” in Twitter. It is based on the same concept of combining relevance with reputation using qualitative (keywords, hashtags, links, etc.) and quantitative (number of influential followers, frequency of relevant posts, whether they follow relevant profiles, etc.) data sets to produce the most relevant and actionable recommendations.

If you haven’t already signed up for Inbox Influencer, do so today – it’s quick and 100% free.

And if you have signed up, keep that feedback coming!

Also make sure to rate us on CatchFree – thanks!

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