This post is the first of a two part article addressing the question: How do you know if your influence score is correct? Today, I won’t actually answer this question, but will show you a step-by-step procedure that we will use next time to address this question.
Because nobody actually has any data on influence (i.e. data that explicitly says who actually influenced who, when, where, how, etc.), all influence scores are therefore computed from users’ social activity data based on some models and algorithms of how influence work. However, anyone can create these models and algorithms. So who is right, and who has the best model? More importantly how can we tell and be sure your influence score is correct? In other words, how can we validate the models that influence vendors use to predict people’s influence?
Last time we explained why nobody can actually measures real influence. So influence vendors must build models that predict someone’s influence in order to compute their influence score.
The problem is that most of these influence models focuses on the influencer. Nearly all models are focused on estimating the influencer’s social capital. Therefore an influence score is merely a prediction on the influencer’s potential to influence.