A Semantics Extraction Framework for Decision Support in Context-Specific Social Web Networks

We are now part of a networked society, characterized by the intensive use and dependence of information systems that deals with communication and information, to support decision-making. It is thus clear that organizations, in order to interact effectively with their customers, need to manage their communication activities at the level of online channels. Monitoring these communications can contribute to obtain decision support insights, reduce costs, optimize processes, etc. In this work, we semantically studied the discursive exchanges of a Facebook group created by a strawberries’ seller, in order to predict, through Social Network Analysis (SNA) and semantic analysis of the posts, the quantities to be ordered by customers. The obtained results show that the unstructured data of the Web’s speech can be used to support the decision through SNA.