Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/61488
Title: Use of a High-Value Social Audience index for target audience identification on Twitter
Contributor(s): Lo, Siaw Ling (author); Cornforth, David (author); Chiong, Raymond  (author)orcid 
Publication Date: 2015
DOI: 10.1007/978-3-319-14803-8_25
Handle Link: https://hdl.handle.net/1959.11/61488
Abstract: 

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.

Publication Type: Conference Publication
Conference Details: ACALCI 2015: Artificial Life and Computational Intelligence, Newcastle, NSW, Australia, 5th - 7th February, 2015
Source of Publication: Artificial Life and Computational Intelligence, First Australasian Conference, ACALCI 2015, Newcastle, NSW, Australia, February 5-7, 2015, Proceedings, p. 323-336
Publisher: Springer
Place of Publication: Switzerland
ISSN: 1611-3349
0302-9743
Fields of Research (FoR) 2020: 4602 Artificial intelligence
Peer Reviewed: Yes
HERDC Category Description: E1 Refereed Scholarly Conference Publication
Series Name: Lecture Notes in Computer Science
Series Number : 8955
Appears in Collections:Conference Publication
School of Science and Technology

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