الفهرس 
An integration framework between social media and business intelligence
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Abstract
People{u201F}s opinions are considered as the most powerful source of market research. Popularly, Social Media has become a platform including huge number of users who can share their opinions about products or services and their thoughts about current problems of the society. They can also express their views on political and religious issues in an easy way. Companies invest a lot of money and time in analyzing their customers{u201F} opinions from multiple existing social media platforms. The knowledge extracted from social media contains sentiment data that is not included in corporate database. This extracted data can be used to improve the marketing campaigns to retain customers and meet their needs in a better way. The integration and merging between both social media data and corporate data can lead to better insights that would not have been possible to gain without such integration Our work proposes a framework called Social-Corporate Data Join Framework (SCDJF) that merges between sentiment data extracted from customers{u201F} opinions from different multiple social media platforms after processing and analyzing that data and the corporate data of an organization. This merging is proposed to perform advanced analytical tasks and answer queries that would not have been possible without the integration. The proposed framework uses any social media platform and applies feature based level sentiment analysis on opinionated sentences including opinions about a specific product or service of a specific organization. The research discusses three different ways to extract (feature/opinion) pairs from each text including: Normal Tokenization, N-gram Modeling Extraction, and Noun Chunking Extraction