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Social Network Analysis and Mining

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01.12.2021 | Original Article

Big data analytics of social network marketing and personalized recommendations

verfasst von: Shu-Hsien Liao, Ching-An Yang

Erschienen in: Social Network Analysis and Mining | Ausgabe 1/2021

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Abstract

A fan page is a kind of a social network. Social network marketing (SNM) is a form of Internet marketing involving the creation and sharing of content on social media networks to achieve marketing and selling goals. In addition, precise SNM requires sufficient data and analysis in terms of making accurate online recommendations. This study examines the experience of various Taiwanese fan page users utilizing a market survey, a total of 1032 valid questionnaire data, and the questionnaire is divided into five sections with 33 items in terms of a big data structure based on a relational database on the first research stage. All questions use nominal and ordinal scales. In the second stage, this study develops a personalized recommendation system (PRS) using big data analytics approach, including cluster analysis and association rules. This study shows how the research results can obtain fans behavior knowledge by examining different group profiles and develop rule-based recommendation approach to generate personalized recommendations for building a SNM mechanism.

Vorheriger Artikel A study of cluster hypergraphs and its properties

Nächster Artikel Security aspects in modern service component-oriented application logic for social e-commerce systems

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Titel: Big data analytics of social network marketing and personalized recommendations
verfasst von: Shu-Hsien Liao
Ching-An Yang
Publikationsdatum: 01.12.2021
Verlag: Springer Vienna
Erschienen in: Social Network Analysis and Mining / Ausgabe 1/2021
Print ISSN: 1869-5450
Elektronische ISSN: 1869-5469
DOI: https://doi.org/10.1007/s13278-021-00729-z

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