Investigating online social media users’ behaviors for social commerce recommendations

Shu-Hsien Liao, Retno Widowati and Yu-Chieh Hsieh

Technology in Society, 2021, vol. 66, issue C

Abstract: Online social media create virtual communities and network platforms that people use to create, share, and exchange opinions, views and experiences. With social networks, social commerce not only relies on commerce, but online social media can also promote the sale of goods or services online. Many online operators have begun to use recommendation systems to analyze customer purchase history and identify individual products that customers may purchase. This enables the company to send product information to consumers to attract their attention. In addition, consumers have a higher purchase rate for recommended products based on consumer data. Based on a survey in Taiwan society, this study uses the questionnaire survey method to collect data on a relational database. This study investigates Taiwan online social media users’ behaviors using data mining methods, including clustering analysis and association rules. Clustering analysis is to investigate possible profiles of users and association rules are to find knowledge patterns and rules of user profiles, online social media usage motivation/preferences and social commerce behavior in order to generate social commerce recommendations in terms of social technology development in the modern society.

Keywords: Online social media; Social commerce; Electronic commerce; Data mining; Knowledge discovery; Recommendation systems (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:teinso:v:66:y:2021:i:c:s0160791x21001305

DOI: 10.1016/j.techsoc.2021.101655

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