Title :
Evaluating the Quality of Social Media Data in Big Data Architecture
Author :
Immonen, Anne ; Paakkonen, Pekka ; Ovaska, Eila
Author_Institution :
VTT Tech. Res. Centre of Finland, Oulu, Finland
fDate :
7/7/1905 12:00:00 AM
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.
Keywords :
Big Data; business data processing; social networking (online); software architecture; big data architecture; big data pipeline; business decision making; customer insight; customer satisfaction; online data; product quality; quality of data; social media data; Big data; Computer architecture; Meta data; Online services; Social network services; Architecture; architecture; big data; metadata; quality attribute; quality of data;
Journal_Title :
Access, IEEE
DOI :
10.1109/ACCESS.2015.2490723