Finding the Key Users in Facebook Fan Pages via a Clustering Approach

The Service of Facebook Fan Pages is one of the most popular social network platform for various organizations. Companies can interact with their own fans through the Fan Pages. The interactions include sending direct advertisement, gathering user meetings, and promoting electronic word of mouth (eWoM). For companies that use social network to gather customers´ information, to identify the opinion leaders on the internet is very important, since opinion leaders are active persons and have influence on other potential customers. Based on clustering algorithm, we proposed a system that can find the opinion leaders and test our method on the Facebook Fan Pages. The data set includes 410,045 comments from 173,988 users that we gathered from October 2013 to September 2014. We also use classification methods to evaluate our system and find promising result.