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SLOD-BI: An Open Data Infrastructure for Enabling Social Business Intelligence
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Author(s): Rafael Berlanga (Universitat Jaume I, Spain), Lisette García-Moya (Universitat Jaume I, Spain), Victoria Nebot (Universitat Jaume I, Spain), María José Aramburu (Universitat Jaume I, Spain), Ismael Sanz (Universitat Jaume I, Spain)and Dolores María Llidó (Universitat Jaume I, Spain)
Copyright: 2016
Pages: 30
Source title:
Big Data: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-4666-9840-6.ch083
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Abstract
The tremendous popularity of web-based social media is attracting the attention of the industry to take profit from the massive availability of sentiment data, which is considered of a high value for Business Intelligence (BI). So far, BI has been mainly concerned with corporate data with little or null attention to the external world. However, for BI analysts, taking into account the Voice of the Customer (VoC) and the Voice of the Market (VoM) is crucial to put in context the results of their analyses. Recent advances in Sentiment Analysis have made possible to effectively extract and summarize sentiment data from these massive social media. As a consequence, VoC and VoM can be now listened from web-based social media (e.g., blogs, reviews forums, social networks, and so on). However, new challenges arise when attempting to integrate traditional corporate data and external sentiment data. This paper deals with these issues and proposes a novel semantic data infrastructure for BI aimed at providing new opportunities for integrating traditional and social BI. This infrastructure follows the principles of the Linked Open Data initiative.
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