淡江大學機構典藏:Item 987654321/121283
English  |  正體中文  |  简体中文  |  全文笔数/总笔数 : 64178/96951 (66%)
造访人次 : 10077195      在线人数 : 17329
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜寻范围 查询小技巧:
  • 您可在西文检索词汇前后加上"双引号",以获取较精准的检索结果
  • 若欲以作者姓名搜寻,建议至进阶搜寻限定作者字段,可获得较完整数据
  • 进阶搜寻


    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/121283


    题名: Investigating Taiwan Instagram users' behaviors for social media and social commerce development
    作者: S.H., Liao;R, Widowati;C.J., Cheng
    关键词: Instagram;Social media;Social media for interaction and entertainment;Social commerce;Electronic commerce;Big data analytics
    日期: 2021-09-07
    上传时间: 2021-09-08 12:11:17 (UTC+8)
    摘要: Instagram is a social media which refers to an online media platform that supports users' social behaviors, including parallel communication, interaction, leisure and entertainment. However, the evolution of today's online market and continuous changes in business models are critical factors driving the growth of the social commerce market. This study aims to investigate social media behaviors and social commerce analysis on Taiwan Instagram users on social media/networks and purchase behavioral preferences of different cluster groups in terms of suggesting social media and social commerce development. This study first stage is to develop a big data structure using a relational database approach. Based on an empirical survey in Taiwan, a total of 1,954 valid questionnaires response was incorporated into a database. The second stage is to implements big data analytics methods, including Apriori algorithms and Cluster analysis, to investigate Instagram users’ profiles and their social media and social commerce preferences.
    關聯: Entertainment Computing 40, 100461
    DOI: 10.1016/j.entcom.2021.100461
    显示于类别:[管理科學學系暨研究所] 期刊論文

    文件中的档案:

    档案 描述 大小格式浏览次数
    index.html0KbHTML208检视/开启

    在機構典藏中所有的数据项都受到原著作权保护.

    TAIR相关文章

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - 回馈