1 research outputs found
Knowledge Discovery from Social Media using Big Data provided Sentiment Analysis (SoMABiT)
In todays competitive business world, being aware of 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
customer feedback and improves the next generation of products. Accordingly,
the dramatic increase in using social media in 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 that 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