Exploring content virality in facebook: A semantic based approach

Abstract

In the current era of digitization specifically with the advent of Web 2.0, social media has become an imposing force in shaping up the way people perceive and react to the information around them. Social media platforms have empowered people to share almost instant feedback on the content posted by individuals and organizations facilitating two way interaction and better engagement among them. This continuous interaction among individuals and organizations creates huge amount of user-generated content (UGC) and associated tokens. This study attempts to understand various semantics that might affect the virality of Facebook posts. Several pages have been identified and shortlisted from domains including e-commerce, manufacturing, services and media. A total of 53,340 Facebook posts comprising of 37, 38, 168 words have been extracted using Facebook Graph API from each of the mentioned domains and subsequently analyzed using NOSQL databases. Further, the derived tokens are semantically grouped and used to gather insights by mapping to existing virality frameworks for identifying and ranking the ones that might be affecting the virality of a post. Findings indicate the virality of content shared has positive correlation with direct brand engagement, promotional offers, freebies and direct user mentions.