In today's competitive business world, being aware of the customer needs and market oriented production is a key success factor for industries. To this aim, the use of efficient analytic algorithms ensures a better understanding of the customer feedback and improves the next generation of products. Accordingly, the dramatic increase of using social media in the daily life provides beneficial sources for market analytics. But how traditional analytic algorithms and methods can scale up for such disparate and multi-structured data sources is the main challenge in this regard. This paper presents and discusses the technological and scientific focus of the SoMABiT as a social media analysis platform using big data technology. Sentiment analysis has been employed in order to discover knowledge from social media. The use of MapReduce and developing a distributed algorithm towards an integrated platform which can scale for any data volume and provide a social media driven knowledge is the main novelty of the proposed concept in comparison to the state-of-the-art technologies.
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