ETL Design Toward Social Network Opinion Analysis

Now-a-days, social networking sites have been created lot of buzz in technologyworld. They are considered as a rich source of information because people share and discuss their opinions about a certain topic freely. Sentiment analysis or opinion mining is used for knowing voice or response of crowd for products, services, organizations, individuals, events, etc. Due to the importance of user's opinions in decisional systems, several Data Warehouse approaches integrate them through a cleaning and transformation processes. However, there is a clear lack of a standard model that can be used to represent the ETL processes. We propose an ETL design approach integrating user's opinion analysis, expressed on the popular social network Facebook. It consists in the extraction of opinion data on Facebook pages (e. g. comments), its pre-processing, sentiment analysis and classification, reformatting and loading into the Data WeBhouse (DWB).