Market Segmentation Using Data Mining Techniques in Social Networks
Social networks have gained great popularity during the last decade, due to the advance of new technologies and people’s growing interest in generating content and sharing it with their contacts. This makes data generated in social networks grow exponentially over time. These generated data contain...
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Published in | Computer Science – CACIC 2018 pp. 221 - 231 |
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Main Authors | , , |
Format | Book Chapter |
Language | English |
Published |
Cham
Springer International Publishing
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Series | Communications in Computer and Information Science |
Subjects | |
Online Access | Get more information |
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Summary: | Social networks have gained great popularity during the last decade, due to the advance of new technologies and people’s growing interest in generating content and sharing it with their contacts. This makes data generated in social networks grow exponentially over time.
These generated data contain information that can be analyzed, in order to discover patterns that can be of help in multiple disciplines. Marketing is one of these disciplines that is closely linked to understanding people’s behaviors, tendencies and tastes. The aim of this study is to apply data mining (DM) to discover patterns in data coming from social networks. Obtaining patterns will enable to carry out different types of segmentations to help the marketing professionals direct their campaigns. |
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ISBN: | 3030207862 9783030207861 |
ISSN: | 1865-0929 1865-0937 |
DOI: | 10.1007/978-3-030-20787-8_16 |