Abstract
The use of freely available online data is rapidly
increasing, as companies have detected the possibilities
and the value of these data in their businesses. In
particular, data from social media are seen as
interesting as they can, when properly treated, assist in
achieving customer insight into business decision making.
However, the unstructured and uncertain nature of this
kind of big data presents a new kind of challenge: how to
evaluate the quality of data and manage the value of data
within a big data architecture? This paper contributes to
addressing this challenge by introducing a new
architectural solution to evaluate and manage the quality
of social media data in each processing phase of the big
data pipeline. The proposed solution improves business
decision making by providing real-time, validated data
for the user. The solution is validated with an
industrial case example, in which the customer insight is
extracted from social media data in order to determine
the customer satisfaction regarding the quality of a
product.
Original language | English |
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Pages (from-to) | 2028-2043 |
Journal | IEEE Access |
Volume | 3 |
DOIs | |
Publication status | Published - 2015 |
MoE publication type | A1 Journal article-refereed |
Keywords
- architecture
- big data
- computer architecture
- meta data
- online services
- social network services