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.

中文翻译：

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使用大数据提供的情感分析 (SoMABiT) 从社交媒体中发现知识

在当今竞争激烈的商业世界中，了解客户需求和以市场为导向的生产是行业成功的关键因素。为此，使用高效的分析算法可确保更好地了解客户反馈并改进下一代产品。因此，日常生活中使用社交媒体的急剧增加为市场分析提供了有益的来源。但是，传统的分析算法和方法如何针对这种不同的、多结构的数据源进行扩展是这方面的主要挑战。本文介绍并讨论了 SoMABiT 作为使用大数据技术的社交媒体分析平台的技术和科学重点。情感分析已被用于从社交媒体中发现知识。