Analyzing User Preferences Using Facebook Fan Pages

With the increasing numbers of Facebook fan-page users, finding information based on their interests has become difficult, and fan-page managers are challenged as they try to understand the needs of these users. To understand their needs and preferences and increase the effectiveness of fan-page marketing, we use two-step clustering to group 42,953 Facebook fan-page users. The results of our study show seven clusters, each with different key characteristics. We label them as lurk, informational, health and beauty, visual lady, intellectual reader, consumption and shopping, and highly active fans. One of our objectives in this paper is to help fan-page managers use our results to target users and to draft management strategies. History: This paper was refereed. This paper has been accepted for the special issue on Applications of Analytics and Operations Research in Big Data Analysis. Keywords: behavior * social network * Information
Introduction Facebook, with 1.366 billion active users each month (Kemp 2015), is the social network with the greatest number of users. The numbers of Facebook users are continually increasing in [...]