Abstract
Participating in social networks to create and share opinion content has become a ubiquitous part of our everyday life. Understanding social media content is at the top of the agenda for many firms today. Business analysts and quants are trying harder to discover ways in which enterprises can be benefited by comprehending the content generated through social media such as Facebook, Wikipedia, Blogs, Youtube and Twitter. This pioneering work may aid business analysts and data scientists with insights into ways to adapt the stable content analysis (CA) techniques to analyse web page contents containing user-generated data. In this paper, we develop an integrated enterprise framework that defines web content analysis (WCA) as a comprehensive and functional layered architecture, and consequently, this framework can be used in various levels of the decision-making process. Further, a four dimensional view of comparative analysis of various WCA systems is presented. Based on the critical analysis of the literature survey, the study explores many open and challenging issues for further research in this domain.
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