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2019 | OriginalPaper | Chapter

Market Segmentation Using Data Mining Techniques in Social Networks

Authors : Eduin Olarte, Marisa Panizzi, Rodolfo Bertone

Published in: Computer Science – CACIC 2018

Publisher: Springer International Publishing

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Abstract

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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Footnotes
1
Pytweet is a pythonic library that provides a simple interface for the Twitter API. Values ​​are normalized in Python types.
 
2
“Application Programming Interface”. In computer programming, an application programming interface is a set of subroutine definitions, protocols, and tools for creating software applications.
 
3
It is an open source distribution of Python and R programming languages ​​for large-scale data processing, predictive analysis and scientific computing, which aims to simplify package management and deployment.
.
 
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Metadata
Title
Market Segmentation Using Data Mining Techniques in Social Networks
Authors
Eduin Olarte
Marisa Panizzi
Rodolfo Bertone
Copyright Year
2019
Book
Computer Science – CACIC 2018

Print ISBN: 978-3-030-20786-1

Electronic ISBN: 978-3-030-20787-8

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-030-20787-8_16

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