Use of a High-Value Social Audience Index for Target Audience Identification on Twitter

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• 作者：Siaw Ling Lo (22)
  David Cornforth (22)
  Raymond Chiong (22)
  
• 关键词：Twitter ; topic modelling ; machine learning ; audience segmentation
• 刊名：Lecture Notes in Computer Science
• 出版年：2015
• 出版时间：2015
• 年：2015
• 卷：8955
• 期：1
• 页码：323-336
• 全文大小：305 KB
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  22. Lo, S.L., Cornforth, D., Chiong, R.: Identifying the high-value social audience from Twitter through text-mining methods. In: Proceedings of the 18th Asia Pacific Symposium on Intelligent and Evolution Systems, vol.聽1, pp. 325鈥?39 (2014)
  
• 作者单位：Siaw Ling Lo (22)
  David Cornforth (22)
  Raymond Chiong (22)
  
  22. School of Design, Communication and Information Technology, Faculty of Science and Information Technology, The University of Newcastle, Callaghan, NSW, 2308, Australia
  
• 丛书名：Artificial Life and Computational Intelligence
• ISBN：978-3-319-14803-8
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349

文摘

With the large and growing user base of social media, it is not an easy feat to identify potential customers for business. This is mainly due to the challenge of extracting commercially viable contents from the vast amount of free-form conversations. In this paper, we analyse the Twitter content of an account owner and its list of followers through various text mining methods and segment the list of followers via an index. We have termed this index as the High-Value Social Audience (HVSA) index. This HVSA index enables a company or organisation to devise their marketing and engagement plan according to available resources, so that a high-value social audience can potentially be transformed to customers, and hence improve the return on investment.