Conceptual notion for opinion mining from upcoming big data

The recent era of data driven cloud computing produce enormous amount of complex data which are needed to be analyzed properly. Data acquired from various social media platforms and resources further processed through different mining tools and techniques for different aspects such as sentiment analysis, opinion mining, etc. Owing to the capability of extracting valuable opinions of consumers towards a particular event or product or blogs, this field gained a lot of attention from researchers and opinion computing become an integral part of big data mining. The existing data mining techniques lacks scalability and computational complexity issues, therefore the proposed study subjected to represent a tentative conceptual model planned for news event sentiment and opinion computation. The conceptual model thereby uses words and emoticons to extract and mine opinions from different words. It represents two different types of case study which are expected to be integrated with the futuristic Big Data Mining based applications.